JP5067539B2 - Image processing apparatus, image forming apparatus, image forming system, and image processing program - Google Patents

Description

The present invention relates to an image processing apparatus, an image forming apparatus, an image forming system, and an image processing program .

  An image forming apparatus such as a printer includes an image output apparatus having means for performing an electrophotographic process, such as a charging device, an exposure device, a developing device, and a transfer device.

  In such an image forming apparatus, a ghost such as a charging ghost, a photoreceptor ghost, a transfer residual ghost, or a transfer injection ghost may occur.

  The frequency and level of occurrence of these ghosts may greatly depend on the surrounding environment of the image output apparatus, the paper quality on which the result of the image forming process is printed, the temporal characteristics of the image output apparatus, the image data to be printed, and the like. Are known.

  For this reason, in the conventional image forming apparatus, parameters related to the image output apparatus, such as a development bias, according to the environment around the image output apparatus, the quality of the paper on which the result of the image forming process is printed, and the temporal characteristics of the image output apparatus. The parameter relating to the voltage and the parameter relating to the transfer bias voltage are changed. Thereby, for example, the development bias voltage and the transfer bias voltage are changed in accordance with the changed parameter values.

As an image forming apparatus that has taken ghost countermeasures, for example, the one described in Patent Document 1 is known.
JP 2002-72583 A

  The present invention relates to an image processing apparatus and image processing capable of suppressing the occurrence of an image defect event even when the image located upstream and the image located downstream in the sub-scanning direction have different color density information. The purpose is to provide a program.

  In addition, the present invention outputs a print processing result in which the occurrence of an image defect event is suppressed even when the image located upstream and the image located downstream in the sub-scanning direction have different color density information. An object of the present invention is to provide an image forming apparatus and an image forming system capable of performing the above.

  In order to solve the above problem, an image processing apparatus according to a first aspect of the present invention includes a predetermined image including a first image and a second image positioned downstream in the sub-scanning direction from the first image. Regarding image data, at least a part of an image corresponding to the first image is based on the color density information of the first image and the color density information of the second image. Prediction means for predicting that an image defect event will occur due to being included in the image, and when the prediction means predicts that the image defect event will occur, from among a plurality of element information relating to image quality And determining means for determining element information to be updated, and updating means for updating element contents of the element information determined by the determining means to predetermined element contents.

  According to a second aspect of the present invention, in the first aspect of the present invention, the predicting unit includes a length of a circumference in the rotation direction of an image carrier on which an electrostatic latent image corresponding to the predetermined image data is formed. The first image and the second image located at a distance corresponding to a length that is a positive integer multiple of the length are included in the predetermined image data, and are included in at least a part of the first image. When the position information indicating the position in the main scanning direction related to the second image is included in the position information indicating the position in the main scanning direction related to the second image, the image defect event is determined based on the color density information of the two images. It is predicted that it will occur.

  According to a third aspect of the present invention, in the invention according to the first or second aspect, the prediction means includes color density information of the first image included in a first allowable range, and the second When the color density information of the image is included in the second allowable range, the image defect event is predicted to occur.

  According to a fourth aspect of the present invention, in the invention according to the first or second aspect, the predicting unit is configured such that the area of the first image area or the area of the second image area is greater than or equal to a predetermined threshold value. In this case, it is predicted that the image defect event will occur.

According to a fifth aspect of the present invention, in the invention according to any one of the first to fourth aspects of the present invention, the predicting means determines a difference between the contrast of the first image and the contrast of the second image. When the value is equal to or greater than a predetermined specified value, it is predicted that the image defect event will occur.

Invention according to claim 6, in the invention described in any one of the claims 1-5, wherein the predicting means, of the image forming means for performing image formation processing around and inside of at least one of the environment At least one of information relating to information, information relating to paper quality on which a result of image forming processing by the image forming means is printed, information relating to temporal characteristics of the image forming means, information relating to the first image, The occurrence of the image defect event is predicted based on information on the second image.

According to a seventh aspect of the present invention, in the invention according to any one of the first to sixth aspects, the element information to be updated includes a component related to image processing and element information related to image forming processing. It is at least one element information.

In order to solve the above problems, an image forming apparatus according to an eighth aspect of the present invention includes the image processing apparatus according to the first to seventh aspects, and forms an image for output data output from the image processing apparatus. Processing is performed.

In order to solve the above problems, an image forming system according to a ninth aspect of the present invention includes a communication line between the image forming apparatus according to the eighth aspect and a processing apparatus that outputs predetermined image data to the image forming apparatus. And the image forming apparatus performs an image forming process on the acquired predetermined image data.

In order to solve the above-described problem, an image processing program according to a tenth aspect of the present invention includes a predetermined image including a first image and a second image positioned downstream in the sub-scanning direction from the first image. Regarding image data, at least a part of an image corresponding to the first image is based on the color density information of the first image and the color density information of the second image. A prediction process for predicting that an image defect event will occur due to being included in the image, and when the image defect event is predicted to occur by the prediction process, A determination processing step for determining element information to be updated from the inside, and an update processing step for updating the element content of the element information determined by the determination processing step to a predetermined element content. You .

  According to the first aspect of the present invention, the predetermined image data including the first image and the second image positioned downstream in the sub-scanning direction with respect to the first image is positioned upstream in the sub-scanning direction. Even when the first image and the second image located downstream have different color density information, the occurrence of an image defect event can be suppressed.

  According to the second aspect of the present invention, the first image positioned upstream and the second image positioned downstream have a distance corresponding to a length that is a positive integer multiple of the peripheral length in the rotation direction of the image carrier. Even if the image is included in the image data to generate an image defect event, the image defect event is generated based on the color density information of the first image and the color density information of the second image. Can be suppressed.

  According to the third aspect of the invention, when the color density information of the first image is included in the first allowable range, and the color density information of the second image is included in the second allowable range. Can suppress the occurrence of image defect events.

  According to the fourth aspect of the present invention, when the area of the first image area or the area of the second image area is equal to or larger than the predetermined threshold, occurrence of an image defect event can be suppressed.

According to the fifth aspect of the present invention, when the difference between the contrast of the first image and the contrast of the second image is equal to or greater than a predetermined specified value, occurrence of an image defect event can be suppressed.

According to the sixth aspect of the present invention, at least one of information relating to the environment, information relating to paper quality, and information relating to the temporal characteristics of the image forming means, information relating to an image located upstream, and information relating to an image located downstream. Based on the above, the occurrence of an image defect event can be suppressed.

According to the seventh aspect of the invention, the element content of at least one of the element information related to the image processing and the element information related to the image forming process is updated when it is predicted that an image defect event will occur. The occurrence of an image defect event can be suppressed based on the element information related to the updated image processing and the element information related to the image forming process.

According to the eighth aspect of the present invention, the predetermined image data including the first image and the second image located downstream in the sub-scanning direction with respect to the first image is positioned upstream in the sub-scanning direction. Even when the first image and the second image located downstream have different color densities, it is possible to output a print processing result in which the occurrence of an image defect event is suppressed.

According to the ninth aspect of the present invention, the predetermined image data including the first image and the second image positioned downstream in the sub-scanning direction with respect to the first image is positioned upstream in the sub-scanning direction. Even when the first image and the second image located downstream have different color density information, it is possible to output a print processing result in which the occurrence of an image defect event is suppressed.

According to the tenth aspect of the present invention, the predetermined image data including the first image and the second image located downstream in the sub-scanning direction with respect to the first image is positioned upstream in the sub-scanning direction. Even when the first image and the second image located downstream have different color density information, software for suppressing the occurrence of an image defect event can be provided.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Note that components having the same function are denoted by the same reference symbols throughout the drawings for describing the embodiment, and the repetitive description thereof will be omitted.

  (Embodiment 1)

  FIG. 1 shows a functional configuration of a printer to which an image forming apparatus having an image processing apparatus according to Embodiment 1 of the present invention is applied.

  As shown in FIG. 1, the printer 10 includes an image processing apparatus 100 and an image output apparatus 200. When print data is received from the computer 20, the printer 10 performs image processing and image formation processing based on the print data. To do.

  The image processing apparatus 100 includes a data reception unit 110, storage units 120 and 150, a PDL interpretation unit 130, a drawing unit 140, an image data analysis unit 160, and an image processing unit 170.

  The data receiving unit 110 receives (acquires) print data from the computer 20, for example, data described in a page description language (PDL), that is, page description language (hereinafter referred to as “PDL”) data, and this PDL data. Is stored in the storage unit 120.

  The print data from the computer 20 is image data, that is, print data expressed in any one of the RGB color space, L * a * b * color space, CMY color space, and CMYK color space, for example. .

  The RGB color space means a color space composed of each color of red (Red), green (Green), and blue (Blue).

  L * a * b * color space, a color space that does not depend on devices such as an image output device (uniform color space), and means a color space of the CIE L * a * b * color system. CIE stands for International Lighting Mark Committee.

  The CMY color space means a color space composed of each color of cyan, magenta, and yellow.

  The CMYK color space means a color space composed of each color of cyan, magenta, yellow, and black.

  The PDL interpretation unit 130 interprets the PDL data stored in the storage unit 120 and outputs the interpreted result to the drawing unit 140.

  The drawing unit 140 performs drawing processing for each processing unit (for example, page) related to drawing based on the interpretation result of the received PDL data, and stores the result of the drawing processing in the storage unit 150. In addition, the drawing unit 140 notifies the image data analysis unit 160 and the image processing unit 170 that the drawing processing for each processing unit has been completed. The result (drawing data) of the drawing process by the drawing unit 140 is data (image data) in bitmap format (raster format).

  Note that in the present embodiment, the storage unit 150 stores a prediction process by the image data analysis unit 160 (to be described later) on the result (drawing data) of the drawing process related to the PDL data corresponding to the page (one page) as a processing unit. Until the process ends, the result (drawing data) of the drawing process related to the PDL data corresponding to the next page is not saved.

  In the first embodiment, the rendering unit 140 performs the rendering process based on the interpretation result of the PDL data so as to conform to the data format related to the image data analysis process by the image data analysis unit 160 described later. It has become.

  For example, when the interpretation result of the received PDL data means image data expressed in the RGB color space, the drawing unit 140 indicates that the data format related to the image data analysis processing is L * a * b * color space. (Hereinafter referred to as “L * a * b * data”), data expressed in CMY color space (hereinafter referred to as “CMY data”), and data expressed in CMYK color space (hereinafter referred to as “CMYK data”). ”) Is converted into image data expressed in the color space as the data format (color). Conversion) and drawing processing is performed.

  On the other hand, when the interpretation result of the received PDL data means image data expressed in the RGB color space, the data format related to the image data analysis processing is interpreted as the data format of RGB data. When the color space in the result and the color space in the data format related to the image data analysis processing are the same, color conversion is not performed.

  The image data analysis unit 160 has functions of a prediction unit, a determination unit, and an update unit. Upon receiving a notification that the drawing process has been completed, the image data analysis unit 160 receives drawing data (bitmap data) stored in the storage unit 150. ) According to a preset data format (data format of data expressed in a predetermined color space) related to the image data analysis processing, image data analysis is performed to determine whether or not an image defect event described later occurs, and image defect Predict the occurrence of an event.

  The data format set in advance for the image data analysis process includes, for example, the data format of any one of RGB data, L * a * b * data, CMY data, and CMYK data.

  In the first embodiment, the image data analysis unit 160 performs the prediction process on the drawing data stored in the storage unit 150, but the drawing data is stored in the storage unit 150. After development (save) to a storage area different from the storage area in which the drawing data is stored, the prediction process may be performed on the development (save) drawing data.

  Now, the functions of the image data analysis unit 160 prediction means, determination means, and update means will be described.

  For the predetermined image data including the first image and the second image located downstream of the first image in the sub-scanning direction, the predicting means includes the color density information of the first image and the first image. Based on the color density information of the second image, it is predicted that an image defect event will occur due to at least a part of the image corresponding to the first image being included in the second image It has a function to do.

  Further, the predicting means is located at a distance corresponding to a length corresponding to a positive integer multiple of the circumference in the rotation direction of the image carrier on which the electrostatic latent image corresponding to the predetermined image data is formed. One image and the second image are included in the predetermined image data, and position information indicating a position in the main scanning direction related to at least a part of the first image is related to the second image. When it is included in the position information indicating the position in the main scanning direction, it has a function of predicting the occurrence of the image defect event based on the color density information of the two images.

  Further, the predicting means includes information relating to at least one environment around and inside the image forming means for performing the image forming process, information relating to paper quality of a sheet on which a result of the image forming process by the image forming means is printed, and Based on at least one piece of information relating to the temporal characteristics of the image forming means, information relating to the first image (color density information, etc.), and information relating to the second image (color density information, etc.), It has a function of predicting that an image defect event will occur.

  In the first embodiment, “the position information indicating the position in the main scanning direction related to at least a part of the first image is included in the position information indicating the position in the main scanning direction related to the second image”. Are pixels indicating the position of the first pixel (position in the X direction) and the position of the last pixel (position in the X direction) in one line of data corresponding to at least a part of the first image. This means position information indicating a range of pixel positions between the positions (a range of pixel positions related to a plurality of pixels in one line, that is, a range of pixel positions in the X direction).

  The “peripheral length in the rotation direction of the image bearing member” is, for example, “a circle of an outer circle (surface on which an electrostatic latent image is formed) of a photosensitive member (photosensitive drum) that is a cylindrical rotating member. "Perimeter".

  Here, the first image and the second image have a distance corresponding to a positive integer multiple of the circumferential length of the image carrier in the rotation direction (hereinafter referred to as “peripheral length of the image carrier”). A case where the image data is included in the predetermined image data will be described with reference to specific examples in FIGS.

  As shown in FIG. 2, the predetermined image data 300 is expressed by 8-bit data (256 gradations), an image 301 having a high density (for example, black 256 gradation values = 100%), and a low density (for example, 256 gradation values). And a black 76 gradation value = 30%) image 302.

  An image 302 corresponding to the second image is located downstream of the image 301 corresponding to the first image in the sub-scanning direction. Further, the image 301 and the image 302 are located at a distance corresponding to a length that is a positive integer multiple (1 in this example) of the circumference of the image carrier. Further, position information (position information in the X direction) indicating the position in the main scanning direction related to the image 301 is included in position information (position information in the X direction) indicating the position in the main scanning direction related to the image 302.

  As shown in FIG. 3, the predetermined image data 310 is expressed by 8-bit data (256 gradations), an image 311 of white characters and a high-density background (for example, 256 gradation values of black = 100%) , An image 312 having a low density (for example, black 76 gradation value = 30%).

  An image 312 corresponding to the second image is located downstream in the sub-scanning direction from an image 311 corresponding to the first image. Further, the image 311 and the image 312 are located at a distance corresponding to a length that is a positive integer multiple (1 times in this example) of the circumference of the image carrier. Further, position information (position information in the X direction) indicating the position in the main scanning direction related to the image 311 is included in position information (position information in the X direction) indicating the position in the main scanning direction related to the image 322.

  As shown in FIG. 4, the predetermined image data 320 is expressed by 8-bit data (256 gradations), an image 321 having a high density (for example, black 256 gradation values = 100%), and a low density (for example, 256 gradation values). The image 322 of black 128 gradation value = 50% and the image 323 of low density (for example, black 76 gradation value = 30%) are included.

  The image 322 and the image 323 corresponding to the second image are located downstream in the sub-scanning direction from the image 301 corresponding to the first image. Further, the image 321 and the image 222 are located with a distance corresponding to a length that is a positive integer multiple (1 in this example) of the circumference of the image carrier, while the image 321 and the image 223 are the image It is located at a distance corresponding to a length that is a positive integer multiple (in this example, twice) of the circumference of the carrier. Further, position information (position information in the X direction) indicating the position in the main scanning direction related to the image 321 is position information (position information in the X direction) indicating the position in the main scanning direction related to each of the image 322 and the image 323. include.

  As shown in FIG. 5, the predetermined image data 330 is expressed by 8-bit data (256 gradations), and image data 331 corresponding to the first page and image data 332 corresponding to the second page. It is assumed that it consists of

  The image data 331 includes an image 331a having a high density (for example, black 256 gradation value = 100%), an image 331b having a low density (for example, black 76 gradation value = 30%), and a high density (for example, 256 gradation for blue). An image 331c having a gradation value = 100%) is included.

  An image 331b corresponding to the second image is located downstream of the image 331a corresponding to the first image in the sub-scanning direction. The image 331a and the image 331b are positioned with a distance corresponding to a positive integer multiple (1 in this example) of the circumference of the image carrier.

  The image data 332 includes an image 332a having a low density (for example, blue gradation value = 30%).

  By the way, in the first embodiment, the gap between the trailing edge of the sheet corresponding to the preceding page and the leading edge of the sheet corresponding to the immediately following page, that is, the gap between the sheets is preset by the image output device 200. It is controlled to be a gap.

  Therefore, the image based on the image data 331 corresponding to the first page and the image based on the image data 332 corresponding to the second page are in a state of being separated by the gap G between sheets as shown in FIG. It can be said that it is equivalent to an image.

  Therefore, the image 332a corresponding to the second image is located downstream in the sub-scanning direction from the image 331c corresponding to the first image. Further, the image 332a and the image 331c are located at a distance corresponding to a length that is a positive integer multiple (1 times in this example) of the circumference of the image carrier in a state including the gap G between the sheets. Yes.

  As can be seen with reference to FIGS. 2 to 5, when attention is paid to the positional relationship between the first image and the second image, the first image is an image located upstream in the sub-scanning direction, It can be said that the second image is an image located downstream in the sub-scanning direction.

  As described above, the prediction means having a function of predicting the occurrence of a ghost predicts that a ghost will occur when it meets at least one of the following conditions (1) to (4).

  (1) The color density information relating to the first image (the image located upstream) is included in the first allowable range, and the color density information relating to the second image (the image located downstream) is included in the first image. 2 tolerances are included. Note that the information indicating the first allowable range and the information indicating the second allowable range are stored in a storage unit such as a ROM (Read Only Memory), for example, and are stored in the storage unit by the image data analysis unit 160. Read out.

  (2) When the area of the area of the first image (image located upstream) or the area of the area of the second image (image located downstream) is equal to or greater than a predetermined threshold. Information indicating the predetermined threshold value is stored in a storage unit such as a ROM, and is read from the storage unit by the image data analysis unit 160.

  (4) When the difference between the contrast of the first image (image located upstream) and the contrast of the second image (image located downstream) is equal to or greater than a predetermined specified value. Information indicating the predetermined specified value is stored in a storage unit such as a ROM, and is read from the storage unit by the image data analysis unit 160.

  When the predicting unit predicts that an image defect event will occur, the determining unit determines element information to be updated from among a plurality of pieces of element information regarding image quality.

  The updating unit updates the element content of the element information determined by the determining unit to a predetermined element content.

  In the first embodiment, “image defect event” means “ghost” which is one of image defects (defects and defects). In the following description, the image defect event will be described as a ghost.

  The “plurality of element information related to image quality” refers to “element information related to image processing and element information related to image forming processing”, that is, “parameters (element information) related to image forming processing and parameters (element information) related to image processing” Information) ”.

  Further, “updated element information” means “at least one element information (parameter) of parameters (element information) related to image processing and parameters (element information) related to image forming processing”. .

  In the following description, element information relating to image processing and element information relating to image forming processing will be described as parameters.

  The parameters related to image processing include, for example, a color parameter related to color conversion, a gradation parameter related to gradation, and a halftone dot (screen) parameter related to halftone dot (screen).

  On the other hand, the parameters relating to the image forming process include, for example, a charging parameter related to charging, an exposure parameter related to exposure, a development parameter related to development, and a transfer parameter related to transfer.

  In the first embodiment, “information indicating whether or not a ghost (image defect event) occurs” is defined as “defect occurrence prediction flag information”. This defect occurrence prediction flag information can be expressed by a plurality of flag values (a plurality of levels) such as “0”, “1”, and “2”. The defect occurrence prediction flag information indicating any one of these flag values is given to a parameter related to image processing and a parameter related to image forming processing.

  The flag value “0” indicates that no ghost is generated, and the flag value “1” or flag value “2” indicates that a ghost is generated. The flag value “2” is a predicted result that is more likely to cause a ghost than the flag value “1”. Therefore, when the flag value is “2”, the flag value is “1”. The change amount (displacement amount) of the corresponding parameter is set to be larger than That is, the relationship of “parameter change amount when flag value is“ 2 ”>“ parameter change amount when flag value is “1” ”is established.

  In the first embodiment, “update the element content of the element information determined by the determining means to a predetermined element content” means “information indicating whether or not a ghost occurs, that is, a flag value of defect occurrence prediction flag information Is updated from “0” indicating that no ghost is generated to “1” or “2” indicating that a ghost is generated, for example.

  This can be said to mean that the setting content of the parameter to be updated is updated based on the flag value “1” or the flag value “2” of the defect occurrence prediction flag information meaning that a ghost is generated.

  The image data analysis unit 160 having the functions of the prediction unit, the determination unit, and the update unit performs the prediction process of the occurrence of the ghost (image defect event) as described above, and determines the defect according to the result of the prediction process. The occurrence prediction flag is output toward the image processing unit 170 and the image output apparatus 200.

  Defect occurrence prediction flag information (hereinafter referred to as “first defect occurrence prediction flag information”) corresponding to parameters related to image processing is output to the image processing unit 170. On the other hand, defect occurrence prediction flag information (hereinafter referred to as “second defect occurrence prediction flag information”) corresponding to parameters related to the image forming process is output to the image output apparatus 200.

  Here, details of the first and second defect occurrence prediction flag information will be described with reference to FIG.

  Since the first and second defect occurrence prediction flag information is a flag for instructing the change of each parameter described above, it can be said that it is parameter change instruction flag information.

  Therefore, in the first embodiment, defect occurrence prediction flag information set corresponding to a parameter is defined as parameter change instruction flag information.

  As shown in FIG. 6, the first defect occurrence prediction flag information 1610 corresponds to a color parameter, corresponds to a color parameter change instruction flag 1611 indicating whether or not it is a parameter to be changed, and a gradation parameter, A gradation parameter change instruction flag 1612 indicating whether or not the parameter is a change target parameter and a halftone dot parameter change instruction flag 1613 corresponding to the halftone parameter and indicating whether or not the parameter is a change target parameter are included. .

  On the other hand, as shown in FIG. 7, the second defect occurrence prediction flag information 1620 corresponds to the charging parameter, and corresponds to the charging parameter change instruction flag 1621 indicating whether or not it is a parameter to be changed, and the exposure parameter. An exposure parameter change instruction flag 1622 indicating whether the parameter is an update parameter, a development parameter change instruction flag 1623 corresponding to the development parameter and indicating whether it is a parameter to be changed, and a transfer parameter, It includes a transfer parameter change instruction flag 1624 indicating whether or not it is a parameter to be changed.

  When each of the parameter change instruction flags described above is expressed by 1-bit data, the flag is, for example, “no parameter change” when “0” and “parameter change” when “1”. , And change content ”.

  When each parameter change instruction flag is expressed by data of a plurality of bits, the flag is, for example, “no parameter change” when “0” and “parameter change” when “1”. When there is “first change contents” and “2”, it means “parameter change and second change contents”.

  Again, a description will be given with reference to FIG. In the image processing apparatus 100, the image processing unit 170 includes a color conversion unit 171, a gradation correction unit 172, and a halftone dot generation unit 173, and first defect occurrence prediction flag information 1610 from the image data analysis unit 160. The color parameter, gradation parameter, and screen (halftone dot) parameter are changed based on the color, and the color for the received image data (drawing data) based on the color parameter, gradation parameter, and halftone dot parameter after the change processing Conversion processing, gradation correction processing, and halftone generation processing are performed.

  In addition, the image processing unit 170 outputs the image data that has been subjected to the image processing to the image output apparatus 200. Details of the image processing unit 170 will be described later.

  The image output apparatus 200 includes an image output apparatus control unit 210, a parameter setting unit 220, and an image forming unit 230.

  Based on the second defect occurrence prediction flag information 1620 from the image processing unit 170 of the image processing device 100, the image output device control unit 210 sets the parameter corresponding to the flag that means the parameter to be changed. The parameter setting unit 220 is controlled so as to change the contents of.

  In addition, the image output device control unit 210 outputs the image data from the image processing unit 170 to the image forming unit 230, and there is no change in the parameters related to the image formation processing, or there is a parameter to be changed. In this case, when a notification to the effect that the changing process has been completed is received from the parameter setting unit 220 described later, a command to start the image forming process (image forming process start command) is output to the image forming unit 230.

  The image output device control unit 210 also prints information on at least the surrounding environment of the image forming unit 230 that functions as an image forming unit that performs the image forming process, and the result of the image forming process performed by the image forming unit 230. At least one piece of information regarding the paper quality of the image and information regarding the temporal characteristics of the image output apparatus 200 (specifically, information regarding the temporal characteristics of the image forming unit 230) is output to the image data analyzing unit 160 of the image processing apparatus 100. To do.

  Further, the image output apparatus control unit 210 sets a gap between the trailing edge of the sheet corresponding to the preceding page and the leading edge of the sheet corresponding to the immediately following page, that is, the gap between the sheets, as a preset gap. To control.

  In this specification, information on at least the surrounding environment of the image forming unit 230 that functions as an image forming unit that performs the image forming process is defined as “environment information”, and the result of the image forming process by the image forming unit 230 is printed. Information on the paper quality of the paper to be printed is defined as “paper quality information”, information on the temporal characteristics of the image output apparatus 200, specifically, information on the temporal characteristics of the image forming unit 230 is defined as “temporal characteristics information”.

  The parameter setting unit 220 has a function of managing parameters related to the image forming process. The parameter setting unit 220 changes the parameters related to the image forming process to be changed in accordance with the control of the image output apparatus control unit 210, and the changing process ends. The image output device control unit 210 is notified of the fact. Details of the parameter setting unit 220 will be described later.

  The image forming unit 230 has a function of an image forming unit, and in accordance with the image forming process start instruction, an image is formed based on parameters related to the image forming process managed by the parameter setting unit 220 and received image data. A forming unit process is executed, and a print output result (paper on which an image is printed) is output as a result of the image forming process.

  FIG. 8 shows a detailed configuration of the image processing unit 170 of the image processing apparatus 100 and the parameter setting unit 220 of the image output apparatus 200.

  In the image processing unit 170 shown in FIG. 8, the color conversion unit 171 includes a color parameter setting unit 171a and a color parameter storage unit 171b, and the gradation correction unit 172 includes a gradation parameter setting unit 172a and a gradation parameter storage unit 172b. Furthermore, the halftone dot generating unit 173 has a halftone dot parameter setting unit 183a and a halftone dot parameter storage unit 173b.

  The color parameter storage unit 171b, the gradation parameter storage unit 172b, and the halftone dot parameter storage unit 173b store color parameters, gradation parameters, and halftone parameters as default values, respectively. As default values, parameter values are set so that high-quality images (image quality including high definition and high gradation) are output.

  Each of the color conversion unit 171, the gradation correction unit 172, and the halftone generation unit 173 refers to the first defect occurrence prediction flag information 1610, and determines whether or not the parameter managed by itself is the parameter to be changed. When it is determined that the parameter is the parameter to be changed, the storage content (parameter) of the subordinate parameter storage unit is changed.

  In each of the parameter storage units, when it is determined that the parameter is not a parameter to be changed, the storage contents (parameters) of the subordinate parameter storage unit remain unchanged (parameters are not changed).

  That is, the color conversion unit 171 refers to the color parameter change instruction flag 1611 in the first defect occurrence prediction flag information 1610, determines whether or not the color parameter is a change target parameter, and determines the change target parameter. If it is determined that the parameter is a parameter, the color parameter setting unit 171a is requested to change the color parameter.

  The color parameter setting unit 171a changes the stored content of the color parameter storage unit 171b based on a preset change amount when a parameter change process is requested.

  The color conversion unit 171 performs color conversion processing on the image data from the drawing unit 140 based on the storage contents (color parameters) of the color parameter storage unit 171b, 1 defect occurrence prediction flag information 1610 is output to the gradation correction unit 172.

  Incidentally, when the received image data is expressed by RGB data or L * a * b * data, the color conversion unit 171 is suitable for printing out the image data in the color space based on the color parameter. Conversion (color conversion) into image data expressed in the color space, that is, the CMY color space or the CMYK color space. On the other hand, when the received image data is expressed by CMY data or CMYK data, the color conversion unit 171 outputs the image data to the next gradation correction unit 172 without performing color conversion.

  The gradation correction unit 172 refers to the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610, determines whether the gradation parameter is a parameter to be changed, and changes Is determined, the tone parameter setting unit 172a is requested to change tone parameters.

  The tone parameter setting unit 172a changes the storage content of the tone parameter storage unit 172b based on a preset change amount when a parameter change process is requested.

  The gradation correction unit 172 performs gradation processing on the image data (image data after color conversion processing) from the color conversion unit 171 based on the storage contents (gradation parameters) of the gradation parameter storage unit 172b. In addition, the image data after gradation processing and the first defect occurrence prediction flag information 1610 are output to the halftone generation unit 173.

  The halftone dot generation unit 173 refers to the halftone dot parameter change instruction flag 1613 in the first defect occurrence prediction flag information 1610, determines whether or not the halftone dot parameter is a parameter to be changed, and If it is determined that the color parameter is, the color parameter changing process is requested to the halftone dot parameter setting unit 173a.

  The halftone dot parameter setting unit 173a changes the stored content of the halftone dot parameter storage unit 173b based on a preset change amount when a parameter change process is requested.

  The halftone dot generation unit 173 generates halftone dots based on the storage contents (halftone dot parameters) of the halftone dot parameter storage unit 173b for the image data (image data after gradation processing) from the gradation correction unit 172. In addition to performing processing (screen processing), the image data after the halftone dot generation processing is output to the image output device controller 210 of the image output device 200.

  In the image output apparatus 200, as shown in FIG. 8, the parameter setting unit 220 includes a charging parameter setting unit 221a and a charging parameter storage unit 221b, a development parameter setting unit 222a and a development parameter storage unit 222b, and a transfer parameter setting unit 223a. And a transfer parameter storage unit 222b.

  The charging parameter storage unit 221b, the development parameter storage unit 222b, and the transfer parameter storage unit 223b store charging parameters, development parameters, and transfer parameters as default values, respectively. As default values, parameter values are set so that high-quality images (image quality including high definition and high gradation) are output.

  By the way, the image output device control unit 210 refers to the second defect occurrence prediction flag information 1620 to determine whether or not there is a parameter to be changed. Request the parameter setting process related to the parameter to change the parameter.

  Here, when the flag (a flag representing a 1-bit or multi-bit data expression) indicates, for example, “0”, it is determined that the parameter corresponding to this flag is not a parameter to be changed. Is a value other than “0”, for example, “1”, it is determined that the parameter corresponding to this flag is a parameter to be changed.

  That is, the charging parameter setting unit 221a changes the stored content of the charging parameter storage unit 221b based on a preset change amount when a parameter changing process is requested, and when the changing process ends. This is notified to the image output device controller 210.

  The exposure parameter setting unit 222a changes the stored content of the exposure parameter storage unit 222b based on a preset change amount when a parameter change process is requested, and when the change process is completed, This is notified to the image output device control unit 210.

  The development parameter setting unit 223a changes the stored content of the development parameter storage unit 223b based on a preset change amount when a parameter change process is requested, and when the change process is completed, This is notified to the image output device control unit 210.

  The transfer parameter setting unit 224a changes the stored content of the transfer parameter storage unit 224b based on a preset change amount when a parameter change process is requested, and when the change process is completed, This is notified to the image output device control unit 210.

  In each of the parameter storage units, when it is determined that the parameter is not a parameter to be changed, the stored content (parameter) remains as it is (the parameter is not changed).

  When the image output device control unit 210 receives a notification that the change processing has been completed from all the parameter change units that have requested the parameter change processing, the image output device control unit 210 of the image processing device 100 (the network of the image processing unit 170). The image forming process start command is output to the image forming unit 230 together with the image data from the point generating unit 173) (image data for which color conversion processing, gradation processing, and halftone generation processing have been completed).

  The image forming unit 230 that has received the image forming process start command receives the parameters stored in the charging parameter storage unit 221b, the exposure parameter storage unit 222b, the development parameter storage unit 223b, and the transfer parameter storage unit 224b of the parameter setting unit 220. Based on the received image data, an electrophotographic process including a charging process, an exposure process, a developing process, and a transfer process, that is, a so-called image forming process is performed.

  FIG. 9 shows a detailed configuration of the image forming unit 230.

  As shown in FIG. 9, the image forming unit 230 includes a photosensitive member 231 as an image carrier, a charging device 232 as a charging unit that charges the surface of the photosensitive member 231 to a potential of a predetermined polarity, and a charged photosensitive member 231. An exposure device 233 as an exposure unit that irradiates exposure light corresponding to image data toward the image development unit 234, and a development unit 234 as a development unit that applies a developer (toner) to the electrostatic latent image formed on the photoreceptor 231 and develops it. A transfer device 235 serving as a transfer unit that transfers the toner image formed on the photosensitive member 231 to a sheet, and a fixing unit 236 serving as a fixing unit that fixes the toner image by applying heat and pressure to the sheet onto which the toner image is transferred. And a cleaning device 237 as a cleaning means for removing residual toner on the peripheral surface of the photosensitive member 231.

  The image forming unit 230 includes an image formation control unit 241 and a plurality of power supply units 242, 243, and 244.

  The power supply unit 242, the power supply unit 243, and the power supply unit 244 supply predetermined power supply voltages (bias voltages) to the charging device 232, the developing device 234, and the fixing device 235, respectively.

  The image formation control unit 241 reads parameters from the charging parameter storage unit 221b, the exposure parameter storage unit 222b, the development parameter storage unit 223b, and the transfer parameter storage unit 224b of the parameter setting unit 220, and in accordance with the read parameters. Control relating to charging to the charging device 232, control relating to exposure to the exposure device 233, control relating to development to the developing device 234, and control relating to transfer to the transfer device 235 are performed.

  For example, the image forming control unit 241 determines the power supply voltage (bias voltage) that the power supply unit 242 should supply to the charging device 232 as control related to development based on the development parameters read from the development parameter storage unit 222b. Then, the power supply unit 242 is controlled so that the power supply voltage (bias voltage) is based on the charging parameter.

  Similarly, the image forming control unit 241 also supplies the power supply voltage (bias voltage) to be supplied to the power supply unit 243 and the power supply unit 244 to the power supply voltage (bias voltage) based on the corresponding parameter. To be controlled.

  In the first embodiment, in the image processing apparatus 100, the PDL interpretation unit 130, the drawing unit 140, the image data analysis unit 160, and the image processing unit 170 (the color conversion unit 171, the gradation correction unit 172, and the halftone dot generation) The unit 173) controls a predetermined program (image processing program) including a program (software) for realizing each function and a program (software) corresponding to a processing procedure described later, such as a central processing unit and a processor. This is realized by executing the means.

  However, the color parameter storage unit 171b, the gradation parameter storage unit 172b, and the halftone dot parameter storage unit 173b are realized by a memory such as a RAM (Random Access Memory).

  Further, the data receiving unit 110 is realized by a communication device such as a communication interface, for example, a data transmission / reception function.

  In the following description, the circumferential length of the image carrier, such as the circumferential length of the photoconductor 231, is defined as “drum pitch”.

  Next, printing processing by the printer 10 will be described with reference to FIG.

  FIG. 10 is a flowchart showing the processing procedure of the printing process.

  In the printer 10, the rendering unit 140 of the image processing apparatus 100 first performs rendering processing of PDL data corresponding to a processing unit (page) based on the interpretation result of the PDL data from the PDL interpretation unit 130, and the page. Is stored in the storage unit 150, the drawing data (image data) is output to the image processing unit 170, and the image data analysis unit 160 is notified that the drawing processing has been completed. Notice.

  The image data analysis unit 160 that has received the notification that the drawing process has been completed analyzes the image data of the corresponding processing unit (page) stored in the storage unit 150 and analyzes the image data. Image data analysis processing such as ghost generation prediction processing based on the result is performed (step S10).

  Based on the result of the ghost occurrence prediction process, the image data analysis unit 160 corresponds to the first defect occurrence prediction flag information 1610 (see FIG. 6) corresponding to the parameters related to the image processing and the parameters related to the image forming process. At least one defect occurrence prediction flag information is generated from the second defect occurrence prediction flag information 1620 (see FIG. 7).

  When generating the first defect occurrence prediction flag information 1610, the image data analysis unit 160 outputs the flag information to the image processing unit 170, while generating the second defect occurrence prediction flag information 1620. If it is, the flag information is output to the image output device controller 210 of the image output device 200.

  Further, when the first defect occurrence prediction flag information 1610 or the second defect occurrence prediction flag information 1620 is not generated, the image data analysis unit 160 performs predetermined processing based on the parameter corresponding to the flag information that has not been generated. The image processing unit 170 or the image output device control unit 210 that performs the processing is notified that there is no parameter change.

  The image processing unit 170 changes parameters related to image processing based on the received first defect occurrence prediction flag information 1610.

  Specifically, among the color parameter setting unit 171a, the gradation parameter setting unit 172a, and the halftone dot generation unit 173a, a flag indicating a value other than “0” in the first defect occurrence prediction flag information 1610. The parameter setting unit that manages the corresponding parameter uses the stored content of the parameter storage unit that stores the parameter to be changed based on the corresponding parameter change instruction flag in the first defect occurrence prediction flag information 1610. Change to parameter contents.

  On the other hand, when the image processing unit 170 receives a notification that “there is no parameter change”, the storage contents (parameters) of each parameter storage unit are not changed and remain as they are.

  Next, the image processing unit 180 that has finished the parameter changing process as described above, stores the contents (parameters) read from the color parameter storage unit 171b, the gradation parameter storage unit 172b, and the halftone parameter storage unit 173b. Then, image processing is performed based on the received image data (step S20), and the image data after the image processing is output to the image output device control unit 210 of the image output device 200.

  In the image output device 200, the image output device control unit 210 controls the parameter setting unit 220 so as to change the parameter for the parameter to be changed based on the received second defect occurrence prediction flag information 1620, The received image data is output to the image forming unit 230.

  In accordance with the control of the image output device control unit 210, the parameter setting unit 220 uses the stored content of the parameter storage unit in which the parameter to be changed is stored as the corresponding parameter in the second defect occurrence prediction flag information 1620. Change the parameter contents based on the change instruction flag.

  Specifically, among the charging parameter setting unit 221a, the exposure parameter setting unit 222a, the development parameter setting unit 223a, and the transfer parameter setting unit 224a, the parameter setting unit that is requested to change the parameter sets the third defect occurrence prediction flag. Based on the parameter change instruction flag information delivered from the image output device control unit 210 in the information 1620, the storage contents (parameters) of the subordinate parameter storage unit are changed.

  On the other hand, when the image output apparatus control unit 210 receives a notification “no parameter change”, the storage contents (parameters) of each parameter storage unit are not changed and remain as they are.

  On the other hand, the image forming unit 230 is based on parameters read from the parameters relating to the image forming process, that is, the charging parameter storage unit 221b, the exposure parameter storage unit 222b, the development parameter storage unit 223b, and the transfer parameter 224b, and the received image data. An image forming process is performed (step S30). As a result of the image forming process, that is, a printing result, a sheet on which an image is printed is output (step S40).

  Next, image data analysis processing by the image data analysis unit 160 will be described with reference to FIG.

  FIG. 11 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 160 is performed under the following preconditions (1) to (7).

  (1) Analysis in units of one pixel.

  (2) The drawn image (image data) is sequentially analyzed from the first line.

  (3) The image data corresponding to one surface (one page) is analyzed.

  (4) Analyze with RGB data.

  (5) For each pixel, the flag is set primarily based on the color range G1 on the ghost generation side and the color range R1 on the ghost receiving side, the flags in one page are cumulatively counted, and the flag is finally set.

  (6) The flag value of the defect occurrence prediction flag information is “0” and “1”, and the defect occurrence prediction flag is at two levels.

  (7) A storage unit such as a ROM stores color allowable range information 1200 shown in FIG. 12 that is referred to by the image data analysis unit 160. Image data analysis processing is performed based on the color tolerance range information 1200 and the pixel value (gradation value) of the pixel to be analyzed.

  In FIG. 12, the color range G1 of the image on the ghost occurrence side indicates the above-described first allowable range, and the color range R1 of the image on the ghost reception side indicates the above-described second allowable range.

  The color range G1 (first allowable range) is R (red) when each color of RGB data, that is, R (red), G (green), and B (green) is expressed by 8-bit data (256 gradations). ), G (green) and B (green) colors (hereinafter referred to as “RGB colors”) values (tone values) are set to “0” to “50”.

  On the other hand, in the color range R1 (second allowable range), the values (tone values) of the RGB colors of the RGB data (256 tones) are set to “100” to “200”.

  Note that the color range R1 and the color range G1 are adopted in the image data analysis process because the density (gradation) of the image on the ghost occurrence side is higher than the first threshold (eg, “50”). In addition, since the ghost is generated when the density of the image on the ghost receiving side is lower than the second threshold (for example, “200”), the color information (gradation value) of the color relating to the image (pixel) to be analyzed This is because the color range R1 and the color range G1 are compared to predict whether or not a ghost occurs.

  Now, the image data analysis unit 160 obtains drawing data (image data) of a processing unit (page) stored in the storage unit 150, and performs RGB data on the drawing data (RGB data) corresponding to the obtained one page. According to the data format of data, scanning is performed in units of pixels sequentially from the first line (step S101), and image data analysis is performed.

  The image data analysis unit 160 defines the result of analyzing the pixel data related to the analysis target pixel, that is, the pixel value (gradation value or density value) as “Gdata”, and then reads the color allowable range information 1200 from the storage unit. In addition, based on the pixel data Gdata of the pixel to be analyzed and the color range G1 in the color tolerance range information 1200 (tone values “0” to “50” of each color of RGB colors), the relational expression “Gdata ≧ G1” Whether or not is established is determined (step S102).

  In step S102, the color information of the pixel data related to the image related to the first image (pixel data related to the image on the ghost occurrence side) is analyzed.

  If the image data analysis unit 160 determines that the above relational expression is established in step S102, the pixel value (scale) of the pixel located downstream in the sub-scanning direction by the drum pitch from the pixel position that is the object of the analysis process. (Tone value) is analyzed (step S103).

  In step S103, the color information of the pixel data relating to the image relating to the second image (pixel data relating to the image on the ghost receiving side) is analyzed.

  The image data analysis unit 160 defines the result of the image data analysis processing in step S103, that is, the pixel value (gradation value or density value) as “Rdata”, and then the image data Rdata of the pixel to be imaged, and the above-mentioned Whether or not the relational expression “Rdata ≧ R1” is satisfied is determined based on the color range R1 (tone values “100” to “200” of the RGB colors) in the color allowable range information 1200 (step S104). ).

  If the image data analysis unit 160 determines that the above relational expression is established, the defect occurrence prediction flag is set to a flag value “1” (primary setting) corresponding to the pixel data Rdata to be analyzed (step S105). The number of flag values “1” is counted (step S106).

  Here, the flags set (determined) based on the allowable color range information 1200, the pixel data Gdata, and the pixel data Rdata shown in FIG. 12 are the contents of the primary setting flag information 1300 shown in FIG. 13 for each color of RGB, for example. It becomes.

  For example, when the pixel data Gdata indicates a gradation value “50” and the pixel data Rdata indicates a gradation value “50”, the flag has a flag value “0”. Further, when the image data Gdata indicates a gradation value “50” and the pixel data Rdata indicates a gradation value “150”, the flag has a flag value “1”.

  When the image data analysis unit 160 determines that the relational expression is not established in step S102 or determines that the relational expression is not established in step S104, the image data analysis unit 160 generates a defect corresponding to the pixel data Rdata to be analyzed. The prediction flag is set to the flag value “0” (primary setting) (step S107), and then the process proceeds to step S106. In step S106, the number of set lag values “0” is counted, in other words, the number of pixels set with the flag value “0” is counted.

  The image data analysis unit 160 that has finished step S106 determines whether or not it is the analysis end position (step S108). If it is determined that it is not the analysis end position, the next pixel (next line) is determined. ) To return to step 101 to perform the image data analysis process.

  On the other hand, the image data analysis unit 160 that has determined that it is the analysis end position in step S108 has a cumulative count number (cumulative count value) of the flag value “1” equal to or greater than a predetermined count number N set in advance. It is determined whether or not there is (step S109). If the cumulative count number of the flag value “1” is less than the predetermined count number N, the flag value “0” is set in the second defect occurrence prediction flag information 1620. On the other hand, if the cumulative count number of the flag value “1” is equal to or greater than the predetermined count number N, the flag value “1” is set in the second defect occurrence prediction flag information 1620 (step S110). S111).

Here, the final flag determined based on the correspondence between the flag value “0” of the flag that is primarily set and the cumulative count number related to the flag value, and the flag value “1” of the flag that is primarily set The final flag determined by the correspondence with the cumulative count number related to the flag value is, for example, the content of the final setting flag information 1400 shown in FIG. In this example, the predetermined count number N is set to 1 × 10 ⁶ .

  In the first embodiment, the ghost is generated when the area of the image on the ghost generation side or the area of the image on the ghost receiving side is larger than a predetermined area, and therefore corresponds to the cumulative count number (that is, the flag value “1”). The cumulative count number of pixels) is employed as the “area size”, and the “predetermined count number N” is employed as the “predetermined area”.

  Then, the image data analysis unit 160 outputs the defect occurrence prediction flag having the flag value “0” set in step S110 or the defect occurrence prediction flag having the flag value “1” set in step S111. It outputs toward the apparatus control part 210 (step S112).

  In this case, for each pixel, the charging parameter change instruction flag 1621, the exposure parameter change instruction flag 1622, the development parameter change instruction flag 1623, and the transfer parameter change instruction flag 1624 of the second defect occurrence prediction flag information 1620 shown in FIG. In addition, the flag value “0” or the flag value “1” is set.

  When the flag value “0” becomes the final flag in step S110, the flag value “0” is set in each parameter change instruction flag of the defect occurrence prediction flag information 1620. On the other hand, when the flag value “1” becomes the final flag in step S111, the flag value “1” is set to at least one parameter change instruction flag among the parameter change instruction flags of the defect occurrence prediction flag information 1620. Is set.

  For example, when the transfer parameter is changed when a ghost is predicted to occur, the flag value “” is set in each of the charge parameter change instruction flag 1621, the exposure parameter change instruction flag 1622, and the development parameter change instruction flag 1623. 0 ”is set, and a flag value“ 1 ”is set in the transfer parameter change instruction flag 1624.

  Defect occurrence prediction flag information 1620 in which such a flag value is set is output toward the image output device controller 210 of the image output device 200 as shown in FIG.

  FIG. 15 shows an overview of the flow of the first defect occurrence prediction flag information 1620 in the printer 10 shown in FIG. 1 and an overview of how the parameters are changed.

  In the image output device 200, the transfer parameter setting unit 224 a updates the transfer parameter storage unit 224 b based on the transfer parameter change instruction flag 1624 under the control of the image output device control unit 210. The other parameter setting units 222a, 223a, and 224a do not update the storage contents of the subordinate parameter storage units.

  Next, the image data analysis process described above will be described with reference to FIGS.

  FIG. 16 shows image data to be analyzed (image data to be printed) 1600 in page units.

  As shown in FIG. 16, the drawing area related to the image data 1600 includes the XY coordinate values (0, 0), (Xmax, 0), (0, Ymax) of the upper left corner, the upper right corner, the lower left corner, and the lower right corner, and This is a region formed by (Xmax, Ymax).

  In FIG. 16, the values of Xa, Yb, Xc, and Yd are arbitrary coordinate values in the drawing area, and Ydum indicates the drum pitch.

  In the image data 1600, the range from the (0, 0) coordinate value to (Xmax, “Ymax−Ydum”) is the region for image data analysis. That is, in the image data 1600, the area 1601 in the sub-scanning direction is an area for image data analysis, and the area 1602 in the sub-scanning direction is not influenced by ghosts, and thus is an area that does not require image data analysis (scanning). is there.

  The image data analysis unit 160 sequentially analyzes the image data 1600 to be analyzed from the first line in the range of image data analysis, that is, the range from (0, 0) coordinate values to (Xmax, “Ymax−Ydum”) in units of pixels. Scan (that is, image data analysis).

  FIG. 17 shows a state of image data analysis processing by the image data analysis unit 160.

  As shown in FIG. 17, the image data analysis unit 160 scans the image data 1600 sequentially from the first line in units of pixels, analyzes the image data (see P101, step S101 in FIG. 11), and the pixel data Gdata becomes ghost. When it is detected that it is within the color range G1 of the image on the generation side (see P102, “YES” in step S101 in FIG. 11), the sub-scanning direction is the drum pitch (Ydrum) more than the position (XY coordinate value) of the pixel data Gdata. The pixel data located downstream is scanned (P103, see step S103 in FIG. 11).

  In this example, pixel data Rdata that is located downstream in the sub-scanning direction by the drum pitch (Ydrum) from the pixel data Gdata located at the (Xa, Yb) coordinate value, that is, at the (Xa, “Yb + Ydrum”) coordinate value, is scanned. Is done.

  Next, when the image data analysis unit 160 detects that the pixel data Rdata is within the color range R1 of the image on the ghost receiving side (see P104, “YES” in step S104 in FIG. 11), the pixel data Rdata. Corresponding to the defect occurrence prediction flag “1” is set primarily (see P105, step S105 in FIG. 11).

  When the defect occurrence prediction flag “1” is primarily set in this way, the image data analysis unit 160 counts the number of defect occurrence prediction flags “1” each time the flag value “1” is set corresponding to the pixel data. Count.

  When the image data analysis unit 160 determines that the pixel data Rdata located at the (Xa, “Yb + Ydrum”) coordinate value is not the analysis end position, the next pixel of the pixel data Gdata located at the (Xa, Yb) coordinate value That is, image data analysis is performed on the pixel data Gdata located at the (Xa + 1, Yb) coordinate value (see P106, “NO” in step S108 in FIG. 11).

  Here, image data analysis processing is performed on a plurality of lines including the pixel data Gdata located at the (Xa + 1, Yb) coordinate value, and the pixel data Gdata currently located at the (Xc, Yd) coordinate value is, for example, Assume that the pixel data to be analyzed is reached.

  The image data analysis unit 160 performs processing similar to the processing of P102 and P103 corresponding to the pixel data Gdata located at the (Xc, Yd) coordinate value, and the pixel data Gdata located at the (Xc, Yd) coordinate value. The pixel data Rdata located at the downstream of the sub-scanning direction by the drum pitch (Ydrum), that is, the pixel data Rdata located at the coordinate value (Xc, “Yd + Ydrum”) is scanned.

  When the image data analysis unit 160 detects that the pixel data Rdata located at the (Xc, “Yd + Ydrum”) coordinate value is outside the color range R1 of the image on the ghost receiving side (P107, step S104 “NO” in FIG. 11). The defect occurrence prediction flag “0” is primarily set corresponding to the pixel data Rdata (see P108, step S107 in FIG. 11).

  When the defect occurrence prediction flag “0” is primarily set in this way, the image data analysis unit 160 counts the number of defect occurrence prediction flags “0” every time the flag value “0” is set corresponding to the pixel data. Count.

  When the image data analysis unit 160 determines that the pixel data Rdata located at the (Xc, “Yd + Ydrum”) coordinate value is not the analysis end position, the image data analysis unit 160 is located at the (Xc, Yd) coordinate value as in the process of P106. Image data analysis is performed on the pixel data Gdata located at the (Xc + 1, Yd) coordinate value relating to the next pixel of the pixel data Gdata (see P109, “NO” in step S108 in FIG. 11).

  Further, image data analysis processing is performed for a plurality of lines, and pixel data Rdata currently located at, for example, (Xmax, “Ymax−Ydrum”) coordinate values becomes pixel data to be analyzed, and an image corresponding to the pixel data Rdata is displayed. Assume that the data analysis process is completed.

  In this case, when the image data analysis unit 160 determines that the XY coordinate value of the pixel data Rdata has reached the analysis end position (see P110, step S108 “YES” in FIG. 11), the defect occurrence prediction flag “ It is determined whether or not the cumulative count number of “1” is equal to or greater than the predetermined count number N (see P111, step S109 in FIG. 11). As a result of this determination, the cumulative count number of the defect occurrence prediction flag “1” Is equal to or greater than the predetermined count number N, the defect occurrence prediction flag “1” is confirmed (finally set) (see P112, step S111 in FIG. 11).

  Then, the image data analysis unit 160 outputs the defect occurrence prediction flag having the flag value “1” to the image output device control unit 210 of the image output device 200 (see P113, step S112 in FIG. 11).

  (Embodiment 2)

  Next, a functional configuration of a printer to which the image forming apparatus having the image processing apparatus according to the second embodiment is applied will be described.

  The printer of the second embodiment has the same configuration and functions as the printer 10 of the first embodiment shown in FIGS. Further, the printer 10 according to the second embodiment performs a printing process similar to the printing process performed by the printer 10 according to the first embodiment illustrated in FIG.

  Next, image data analysis processing by the image data analysis unit 160 of the image processing apparatus 100 of the printer 10 according to the second embodiment will be described with reference to FIG.

  FIG. 18 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 160 is performed under the following preconditions (1) to (7).

  (1) Thinning analysis is performed in units of, for example, 16 pixels (0.68 mm pitch at 600 dpi) in both the main scanning direction and the sub-scanning direction.

  It should be noted that, for example, thinning scanning is performed with, for example, 16 pixels in both the main scanning direction and the sub-scanning direction, and the image data analysis is performed because the area relating to the ghost generation side image and the area relating to the ghost receiving side image are somewhat wide. Otherwise, a ghost does not occur. Therefore, even if a defect occurrence prediction flag is determined by performing a thinning scan, there is no problem in the ghost generation prediction process.

  (2) The drawn image (image data) is sequentially analyzed from the first line.

  (3) The image data corresponding to one surface (one page) is analyzed.

  (4) Analyze with CMYK data.

  (5) A flag is primarily set based on the color range G1 on the ghost generation side and the contrast difference between the color information on the ghost generation side and the color information on the ghost reception side, and the flag within one page is cumulatively counted. Final setting.

  (6) The flag value of the defect occurrence prediction flag information is “0”, “1”, and “3”, and the defect occurrence prediction flag is at three levels.

  (7) Flag setting information 1900 shown in FIG. 19 that is referred to by the image data analysis unit 160 is stored in a storage unit such as a ROM. Image data analysis processing is performed based on the flag setting information 1900 and the pixel value (gradation value) of the pixel to be analyzed.

  As shown in FIG. 19, the flag setting information 1900 includes “ghosting side color range G1” for each color of cyan (C), magenta (M), yellow (Y), and black (K). Each condition of “contrast difference ΔC <C1”, “C1 ≦ contrast difference ΔC <C2” and “contrast difference ΔC ≧ 2” is set.

  In addition, the flag value of the defect occurrence prediction flag (in this example, “0” corresponding to the three conditions “contrast difference ΔC <C1”, “C1 ≦ contrast difference ΔC <C2”, and “contrast difference ΔC ≧ 2”). ”,“ 1 ”,“ 2 ”).

  Here, the contrast difference Δ is a result obtained by calculating “pixel data Gdata relating to the image on the ghost occurrence side−pixel data Rdata relating to the image on the ghost receiving side”.

  For each color of the color material, the contrast difference ΔC meets any of the three conditions of “contrast difference ΔC <C1”, “C1 ≦ contrast difference ΔC <C2”, and “contrast difference ΔC ≧ 2”. In this case, the flag value of the defect occurrence prediction flag corresponding to the matched condition is adopted corresponding to the pixel data to be analyzed.

  In the second embodiment, the predetermined prescribed value indicating the difference between the contrast of the first image (ghost generation side image) and the second image (ghost reception side image) is “contrast difference ΔC <C1”. “> 20%”, “C1 ≦ Contrast Difference ΔC <C2”, “20 to 79%”, and “Contrast Difference ΔC ≧ 2”, “≧ 80”.

  As shown in FIG. 18, the image data analysis unit 160 acquires drawing data (image data) of a processing unit (page) stored in the storage unit 150, and draws data corresponding to the acquired one page. For (CMYK data), in accordance with the data format of CMYK data, thinning scanning is sequentially performed from the first line, for example, in units of 16 pixels (step S201), and image data analysis is performed.

  The image data analysis unit 160 defines the result of analyzing the pixel data related to the analysis target pixel, that is, the pixel value (gradation value or density value) as “Gdata”, and then reads the color allowable range information 1200 from the storage unit. At the same time, based on the pixel data Gdata of the pixel to be analyzed and the color range G1 in the flag setting information 1900 (tone values “0” to “50” of each color of CMYK colors), the relational expression “Gdata ≧ G1” is obtained. It is determined whether or not it is established (step S202).

  In step S202, the color information of the pixel data related to the image related to the first image (pixel data related to the image on the ghost occurrence side) is analyzed.

  If the image data analysis unit 160 determines in step S202 that the above relational expression is satisfied, the pixel value of the pixel located downstream in the sub-scanning direction by the drum pitch from the position of the pixel that was the object of the previous analysis process. (Tone value) is analyzed (step S203).

  The image data analysis unit 160 obtains a contrast difference ΔC between the pixel data Gdata relating to the ghost generation side image and the pixel data Rdata relating to the ghost receiving side image, and the obtained contrast difference ΔC is expressed as “contrast difference ΔC <C1”. ], “C1 ≦ contrast difference ΔC <C2”, or “contrast difference ΔC ≧ 2” is determined (step S204).

  If the image data analysis unit 160 determines that the relational expression “contrast difference ΔC <C1” is established, the defect occurrence prediction flag is set to the flag value “0” corresponding to the pixel data Rdata to be analyzed ( If it is determined that the relational expression “contrast difference ΔC ≧ 2” is established, the defect occurrence prediction flag is set to the flag value “1” corresponding to the pixel data Rdata to be analyzed. Is set (primary setting) (step S206), and if it is determined that the relational expression “C1 ≦ contrast difference ΔC <C2” holds, the defect occurrence prediction flag corresponding to the pixel data Rdata to be analyzed is determined. Is set to the flag value “2” (primary setting) (step S207).

  When step S205 is finished, step S206 is finished, or step S207 is finished, the image data analysis unit 160 counts the number of flag values for each set flag value, in other words, the flag value is The number of set pixels is counted (step S208).

  The image data analysis unit 160 that has finished step S208 determines whether or not the position is the analysis end position (step S209). If it is determined that the position is not the analysis end position, the next pixel (next line) is determined. ) To return to step 201 to execute the image data analysis process.

  On the other hand, the image data analysis unit 160 that has determined that it is the analysis end position in step S209 is predetermined when the cumulative count number (cumulative count value) of the flag value “2” is greater than or equal to a predetermined count number M set in advance. Whether the first relational expression of “M ≦ cumulative count number <N” is satisfied, or is the cumulative count number equal to or greater than a predetermined count number N set in advance? That is, it is determined whether or not the second relational expression of “cumulative count number ≧ N” is satisfied (step S210).

  If the image data analysis unit 160 determines in step S109 that both the first relational expression and the second relational expression are not established, the image data analysis unit 160 sets the flag value “0” in the second defect occurrence prediction flag information 1620. If it is determined that the first relational expression is satisfied (step S211), a flag value “1” is set in the second defect occurrence prediction flag information 1620 (step S212). When it is determined that the second relational expression is established, the flag value “2” is set in the second defect occurrence prediction flag information 1620 (step S213).

  Here, the final defect occurrence prediction flag determined based on the pixel data Gdata on the ghost occurrence side and the contrast difference ΔC is, for example, the content of the final setting flag information 2000 shown in FIG.

  Then, the image data analysis unit 160 sets the defect occurrence prediction flag having the flag value “0” set in step S211, the defect occurrence prediction flag having the flag value “1” set in step S212, or the flag value “set in step S213”. 2 ”is output to the image output device controller 210 of the image output device 200 (step S214).

  In this case, for each pixel, the charging parameter change instruction flag 1621, the exposure parameter change instruction flag 1622, the development parameter change instruction flag 1623, and the transfer parameter change instruction flag 1624 of the second defect occurrence prediction flag information 1620 shown in FIG. In addition, a flag value “0”, a flag value “1”, or “2” is set.

  When the flag value “0” becomes the final flag in step S211, the flag value “0” is set in each parameter change instruction flag of the defect occurrence prediction flag information 1620. On the other hand, when the flag value “1” becomes the final flag in step S212 or the flag value “2” in step S213, at least one parameter change among the parameter change instruction flags in the defect occurrence prediction flag information 1620 is changed. A flag value “1” or a flag value “2” is set in the instruction flag.

  For example, when the transfer parameter is changed when a ghost is predicted to occur, the flag value “” is set in each of the charge parameter change instruction flag 1621, the exposure parameter change instruction flag 1622, and the development parameter change instruction flag 1623. 0 ”is set, and a flag value“ 1 ”or a flag value“ 2 ”is set in the transfer parameter change instruction flag 1624.

  The defect occurrence prediction flag information 1620 in which such a flag value is set is output toward the image output device control unit 210 of the image output device 200.

  In the image output device 200, the transfer parameter setting unit 224 a updates the transfer parameter storage unit 224 b based on the transfer parameter change instruction flag 1624 under the control of the image output device control unit 210.

  In the second embodiment, for example, as shown in FIG. 21, when the flag parameter correspondence information 2100 indicating the correspondence between the flag and the parameter change content is stored in a storage means such as a ROM, the transfer parameter setting unit 224a updates the storage contents (parameters) of the transfer parameter storage unit 224b based on the flag value set in the transfer parameter change instruction flag 1624 and the flag parameter correspondence information 2100 read from the storage means.

  In the flag parameter correspondence information 2100 in FIG. 21, the voltage change amount (displacement amount) ΔV corresponding to the flag value “0” is “± 0”, which means that the transfer parameter is not changed. To do.

  Further, since the voltage change amount (displacement amount) ΔV corresponding to the flag value “1” is “−150”, the transfer parameter is a voltage change amount (displacement amount) ΔV = a predetermined transfer voltage. This means that the transfer voltage is lowered by 150V.

  Further, since the voltage change amount (displacement amount) ΔV corresponding to the flag value “2” is “−300”, the transfer parameter is a voltage change amount (displacement amount) ΔV = a predetermined transfer voltage. It means that the transfer voltage is changed by 300V.

  In the second embodiment, as shown in FIG. 22, the image output device control unit 210 performs second defect occurrence prediction flag information 1620 from the image processing device 100, environment information, paper quality information, and temporal characteristics information. Based on the defect occurrence prediction flag information, and, for example, the charging parameter setting unit 221a, the development parameter setting unit 223a, and the transfer parameter setting unit based on the defect occurrence prediction flag after the flag replacement. A request for changing the parameters is made to 224a so that the parameters correspond to the flag values.

  FIG. 22 shows an outline of the flow of the defect occurrence prediction flag information 1620 in the printer 10 shown in FIG. 1 and an outline of how the parameters are changed.

  The image data analysis process described above will be described with reference to FIG.

  FIG. 23 shows a state of image data analysis processing by the image data analysis unit 160.

  Note that the image data to be analyzed in page units is the same as the image data in the case of the first embodiment shown in FIG. 16, and a detailed description thereof will be omitted here.

  As shown in FIG. 23, the image data analysis unit 160 scans the image data 1600 (see FIG. 16) sequentially from the top line, for example, in units of 16 pixels, and analyzes the image data (P201, step S21 in FIG. 18). When the pixel data Gdata is detected to be within the color range G1 of the image on the ghost occurrence side (see P202, “YES” in step S201 in FIG. 18), the drum is more drummed than the position (XY coordinate value) of the pixel data Gdata. Pixel data located downstream in the sub-scanning direction by the pitch (Ydrum) is scanned (see P203, step S203 in FIG. 18).

  In this example, pixel data Rdata located at a position downstream (Xa, “Yb + Ydrum”) in the sub-scanning direction by the drum pitch (Tdrum) from the pixel data Gdata located at the (Xa, Yb) coordinate value is scanned. Is done.

  Next, the image data analysis unit 160 includes pixel data Gdata ((Xa, Yb) coordinate value) related to the image on the ghost generation side and pixel data Rdata ((Xa, “Yb + Ydrum”) coordinate value related to the image on the ghost receiving side. ), And when the calculated contrast difference ΔC meets the relational expression “C1 ≦ contrast difference ΔC <C2” (see P204, step S204 “C1 ≦ ΔC ≦ C2” in FIG. 18). ) Corresponding to the pixel data Rdata, the defect occurrence prediction flag “2” is primarily set (see P205, step S207 in FIG. 18).

  When the defect occurrence prediction flag “2” is primarily set in this way, the image data analysis unit 160 sets the number of defect occurrence prediction flags “2” each time the flag value “2” is set corresponding to the pixel data. Count.

  When the image data analysis unit 160 determines that the pixel data Rdata located at the (Xa, “Yb + Ydrum”) coordinate value is not the analysis end position, the image data analysis unit 160 uses the pixel data Gdata located at the (Xa, Yb) coordinate value as a reference. Image data analysis is performed on the pixel data Gdata located at the pixel that is thinned out by 16 pixels, that is, the (Xa + 16, Yb) coordinate value (see P206, step S209 “NO” in FIG. 18).

  Here, image data analysis processing is performed for a plurality of lines including the pixel data Gdata positioned at the (Xa + 16, Yb) coordinate value, and the pixel data Gdata currently positioned at the (Xc, Yd) coordinate value is, for example, Assume that the pixel data to be analyzed is reached.

  The image data analysis unit 160 performs processing similar to the processing of P202 and P203 corresponding to the pixel data Gdata located at the (Xc, Yd) coordinate value, and the pixel data Gdata located at the (Xc, Yd) coordinate value. The pixel data Rdata located at the downstream of the sub-scanning direction by the drum pitch (Ydrum), that is, the pixel data Rdata located at the coordinate value (Xc, “Yd + Ydrum”) is scanned.

  The image data analysis unit 160 compares the difference between the pixel data Gdata ((Xc, Yd)) relating to the ghost generation side image and the pixel data Rdata ((Xc, “Yd + Ydrum”)) relating to the ghost receiving side image. ΔC is obtained, and when the obtained contrast difference ΔC conforms to the relational expression “contrast difference ΔC ≧ C2” (see P207, step S204 “ΔC <C1” in FIG. 18), it corresponds to the pixel data Rdata. Thus, the defect occurrence prediction flag “0” is primarily set (see P208, step S205 in FIG. 18).

  When the defect occurrence prediction flag “0” is primarily set in this way, the image data analysis unit 160 counts the number of defect occurrence prediction flags “0” every time the flag value “0” is set corresponding to the pixel data. Count.

  When the image data analysis unit 160 determines that the pixel data Rdata located at the (Xc, “Yd + Ydrum”) coordinate value is not the analysis end position, the image data analysis unit 160 is located at the (Xc, Yd) coordinate value as in the process of P206. Image data analysis is performed on the pixel data Gdata that is located at the (Xc + 16, Yd) coordinate value obtained by thinning out 16 pixels with reference to the pixel data Gdata (see P209, step S209 “NO” in FIG. 18).

  Further, image data analysis processing is performed for a plurality of lines, and pixel data Rdata currently located at, for example, (Xmax, “Ymax−Ydrum”) coordinate values becomes pixel data to be analyzed, and an image corresponding to the pixel data Rdata is displayed. Assume that the data analysis process is completed.

  In this case, when the image data analysis unit 160 determines that the XY coordinate value of the pixel data Rdata has reached the analysis end position (see P210, step S209 “YES” in FIG. 18), the defect occurrence prediction flag “ It is determined whether or not the cumulative count number of “2” is equal to or greater than the predetermined count number N (see P211, step S210 in FIG. 18). As a result of this determination, the cumulative count number of the defect occurrence prediction flag “2” Is equal to or greater than the predetermined count number N (when the relational expression “cumulative count number ≧ N” is satisfied), the defect occurrence prediction flag “2” is confirmed (finally set) (P212, FIG. 18). Step S213).

  Then, the image data analysis unit 160 outputs the defect occurrence prediction flag having the flag value “2” to the image output device control unit 210 of the image output device 200 (see P213, step S214 in FIG. 18).

  The image output device controller 210 uses the defect occurrence prediction flag information (flag value “2”) from the image processing device 100 based on the environment information, the paper quality information, and the temporal characteristic information. “2”) is read, and the flag value is set to, for example, the charging parameter setting unit 221a, the development parameter setting unit 223a, and the transfer parameter setting unit 224a based on the defect occurrence prediction flag after the flag is read. Request a parameter change process so that the corresponding parameter is obtained.

  Then, the charging parameter, the development parameter, and the transfer parameter are changed to parameter values corresponding to the flag value (P214).

  (Embodiment 3)

  Next, a functional configuration of a printer to which the image forming apparatus having the image processing apparatus according to the third embodiment is applied will be described.

  The printer of the third embodiment has the same configuration and function as the printer 10 of the first embodiment shown in FIGS. Further, the printer 10 according to the third embodiment performs a printing process similar to the printing process performed by the printer 10 according to the first embodiment shown in FIG.

  Next, image data analysis processing by the image data analysis unit 160 of the image processing apparatus 100 of the printer 10 according to the third embodiment will be described with reference to FIG.

  FIG. 24 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 160 is performed under the following preconditions (1) to (6).

  (1) For example, scanning while calculating an average value (hereinafter referred to as “average value of 16 pixel × 16 pixel block”) or moving average value of pixel values (gradation value or density value) related to a block of 16 pixels × 16 pixels .

  Note that, for example, scanning and image data analysis are performed while calculating an average value of a 16 pixel × 16 pixel block, and the area relating to the image on the ghost generation side and the area relating to the image on the ghost receiving side are not large to some extent. For example, even if scanning is performed while calculating the average value of 16 pixels × 16 pixel blocks and the determination of the defect occurrence prediction flag is performed, there is no problem in the ghost occurrence prediction process. .

  (2) The drawn image (image data) is sequentially analyzed from the first line.

  (3) Analyze in units of jobs (JOB).

  (4) Analyze with CMYK data.

(5) The flag is set primarily based on the color range G1 on the ghost generation side and the contrast difference between the color information on the ghost generation side and the color information on the ghost reception side, and the flags are cumulatively counted in a predetermined band width. The flag is finally set for each band.
The band is a plurality of lines per length corresponding to the drum pitch in the Y direction (sub-scanning direction).

  (6) The flag value of the defect occurrence prediction flag information is “0”, “1”, and “3”, and the defect occurrence prediction flag is at three levels.

  (7) Flag setting information 1900 according to the second embodiment shown in FIG. 19 that is referred to by the image data analysis unit 160 is stored in a storage unit such as a ROM. Image data analysis processing is performed based on the flag setting information 1900 and the pixel value (gradation value) of the pixel to be analyzed.

  As shown in FIG. 18, the image data analysis unit 160 acquires drawing data (image data) of a processing unit (page) stored in the storage unit 150, and draws data corresponding to the acquired one page. For (CMYK data), a block of 16 pixels × 16 pixels, for example, is scanned according to the data format of the CMYK data (step S301), and image data analysis is performed.

  The image data analysis unit 160 obtains a result of analyzing a plurality of pixel data relating to a 16 pixel × 16 pixel block to be analyzed, that is, an average value of 16 pixel × 16 pixel blocks (step S302).

  The image data analysis unit 160 defines the average value of the obtained 16 pixel × 16 pixel block as “Gave”, and then reads the color allowable range information 1200 from the storage unit and also analyzes the 16 pixels × 16 pixels to be analyzed. Whether or not the relational expression “Gave ≧ G1” is satisfied based on the color range G1 in the block average value Gave and flag setting information 1900 (tone values “0” to “50” for each color of CMYK colors). Is determined (step S303).

  In step S303, the color information of the pixel data related to the image related to the first image (pixel data related to the image on the ghost occurrence side) is analyzed.

  If the image data analysis unit 160 determines in step S303 that the above relational expression is satisfied, the pixel value of the pixel located downstream in the sub-scanning direction by the drum pitch from the position of the pixel that was the object of the previous analysis process. (Tone value) is analyzed (step S304).

  In this case, the pixel value (gradation value) of the 16 pixel × 16 pixel block positioned downstream in the sub-scanning direction by the drum pitch (Ydrum) from the position of the 16 pixel × 16 pixel block related to the image on the ghost occurrence side. Analyzed.

  The image data analysis unit 160 obtains an average value of pixel values (gradation values) related to the downstream 16 pixel × 16 pixel block (step S305), and calculates the obtained average value of the 16 pixel × 16 pixel block. It is defined as “Rave”.

  The image data analysis unit 160 obtains a contrast difference ΔC between the average value Gave of the 16 pixel × 16 pixel block related to the ghost image and the average value Rave of the 16 pixel × 16 pixel block related to the ghost image. It is determined whether the obtained contrast difference ΔC matches any of the relational expressions “contrast difference ΔC <C1”, “C1 ≦ contrast difference ΔC ≦ C2”, or “contrast difference ΔC> 2” (step S306). .

  When the image data analysis unit 160 determines that the relational expression “contrast difference ΔC <C1” is established, the defect occurrence prediction flag is flagged corresponding to the average value Rave of the 16 pixel × 16 pixel block to be analyzed. The value is set to “0” (primary setting) (step S307), and if it is determined that the relational expression “contrast difference ΔC ≧ 2” is satisfied, the average value of the 16 pixel × 16 pixel block to be analyzed In response to Rave, the defect occurrence prediction flag is set to the flag value “1” (primary setting) (step S308), and if it is determined that the relational expression “C1 ≦ contrast difference ΔC ≦ C2” is satisfied, The defect occurrence prediction flag is set to the flag value “2” (primary setting) corresponding to the average value Rave of the 16 pixel × 16 pixel block to be analyzed. Step S309).

  When step S307 is finished, step S308 is finished, or step S309 is finished, the image data analysis unit 160 counts the number of the flag values for each set flag value (step S310).

  After completing step S310, the image data analysis unit 160 determines whether or not the position of the last pixel (pixel data) related to the average value Rave of the 16 pixel × 16 pixel block to be analyzed is the band analysis end position. Is determined (step S311).

  The band analysis end position corresponds to the position of the last pixel related to the last line among a plurality of lines per length corresponding to the drum pitch (Ydrum) related to the analysis target band. .

  When the image data analysis unit 160 determines in step S311 that the position of the last pixel (pixel data) related to the average value Rave of the 16 pixel × 16 pixel block to be analyzed is not the band analysis end position In step S301, the process returns to step S301 in order to perform image data analysis processing of the next 16 pixel × 16 pixel block, that is, the next pixel (next line).

  On the other hand, the image data analysis unit 160 that determines that the position of the last pixel (pixel data) related to the average value Rave of the 16 pixel × 16 pixel block to be analyzed is the band analysis end position, Whether the cumulative count number (cumulative count value) of the value “2” is greater than or equal to a preset predetermined count number M and less than the predetermined count number N, that is, the first of “M ≦ cumulative count number <N” Whether the cumulative count number is equal to or greater than a predetermined count number N set in advance, that is, whether the second relational expression of “cumulative count number ≧ N” is satisfied. (Step S312).

  If the image data analysis unit 160 determines that both the first relational expression and the second relational expression are not established in step S312, the image data analysis unit 160 sets the flag value “0” in the second defect occurrence prediction flag information 1620. If the first relational expression is determined to be satisfied (step S313), the flag value “1” is set to the second defect occurrence prediction flag information 1620 (step S314). If it is determined that the second relational expression is established, the flag value “2” is set in the second defect occurrence prediction flag information (step S315).

  Here, the final defect occurrence prediction flag determined based on the average value Gave of the 16 pixel × 16 pixel block on the ghost occurrence side and the contrast difference ΔC is, for example, the final setting flag information 2000 shown in FIG. (See Form 2).

Then, the image data analysis unit 160 sets the defect occurrence prediction flag having the flag value “0” set in step S313, the defect occurrence prediction flag having the flag value “1” set in step S314, or the flag value “set” in step S315. The defect occurrence prediction flag “2” is output to the image output device control unit 210 of the image output device 200 as the defect occurrence prediction flag of “Band _- No.” To be analyzed (step S316).

Here, “Band _- No.” Is “Band _- 1” indicating the first band, “Band _- 2” indicating the second band,..., “Band _- last” indicating the last band. It means a band to be analyzed among a plurality of bands.

  The image data analysis unit 160 that has finished step S316 determines whether or not the position is the analysis end position (step S317). If it is determined that the position is not the analysis end position, the image data analysis unit 160 moves to the next band. The process returns to step 301 to perform the image data analysis process concerned, and if it is determined that the analysis end position is reached, the image data analysis process ends.

  Also in the image data analysis processing described above, as in the case of the second embodiment, the charging parameter change instruction flag 1621 and the exposure parameter change instruction flag of the second defect occurrence prediction flag information 1620 shown in FIG. A flag value “0”, a flag value “1”, or “2” is set in 1622, the development parameter change instruction flag 1623, and the transfer parameter change instruction flag 1624.

  The outline of the defect occurrence prediction flag information 1620 and the outline of how the parameters are changed are the same as those in the example of the second embodiment shown in FIG.

  That is, based on the defect occurrence prediction flag information, the environment information, the paper quality information, and the temporal characteristics information, the defect occurrence prediction flag information is replaced with a flag, and based on the defect occurrence prediction flag after the flag replacement, for example, Then, the charging parameter setting unit 221a, the development parameter setting unit 223a, and the transfer parameter setting unit 224a are requested to perform a parameter changing process so that the parameter corresponds to the flag value.

  Next, the image data analysis process described above will be described with reference to FIGS. 25 and 26. FIG.

  FIG. 25 shows drawing data (image data to be printed) 2600 to be analyzed in page units.

  As shown in FIG. 25, the drawing area related to the drawing data 2500 corresponds to a plurality of pages, and the XY coordinate values (0, 0), (Xmax, 0), an area formed by the XY coordinate values (0, Ymax) and (Xmax, Ymax) of the lower left corner and the lower right corner corresponding to the last page.

  The image data analysis unit 160 converts the drawing data 2500 to be analyzed into an image data analysis area, that is, a range from (0, 0) coordinate values to (Xmax, “Ymax−Ydum”), for example, a block of 16 pixels × 16 pixels. Scan and analyze image data in units.

  In FIG. 25, the values of Xa, Yb, Xc, Yd, Xe, and Yf are arbitrary coordinate values in the drawing area, and Ydum indicates the drum pitch. Band length = Ydum = drum pitch is set.

  Note that, in the drawing data 2500, the regions 2501, 2502, and 2503 are target regions for image data scanning and image data analysis in the sub-scanning direction. Regarding the region 2504 in the sub-scanning direction, the region 1602 in the sub-scanning direction is not affected by ghosts, so that image data analysis (scanning) is unnecessary.

In the third embodiment, the band length = Ydum = drum pitch is set as described above. Therefore, for a plurality of bands, the odd-numbered band corresponds to the image on the ghost generation side, and the even-numbered band is the ghost. Corresponds to the receiving image. An example is given below.
“Band _- 1” indicating the first band corresponds to the drawing data on the ghost generation side.
“Band _- 2” indicating the second band corresponds to the drawing data on the ghost receiving side.
“Band _- 3” indicating the third band corresponds to the drawing data on the ghost generation side.
“Band _- 4” indicating the fourth band corresponds to the drawing data on the ghost receiving side.

  FIG. 26 shows the state of image data analysis processing by the image data analysis unit 160.

  As shown in FIG. 26, the image data analysis unit 160 acquires drawing data (image data) of a processing unit (page) stored in the storage unit 150, and the drawing data 2500 corresponding to the acquired one page. For example, a block of 16 pixels × 16 pixels is scanned and image data analysis is performed (see P301, step S301 in FIG. 24).

  The image data analysis unit 160 obtains an average value (average value of pixel values) Gave of 16 pixels × 16 pixel blocks to be analyzed (P302, see step S302 in FIG. 24), and the average value of the 16 pixels × 16 pixel blocks. Based on the Gave and the flag setting information 1900 (see FIG. 19), it is recognized that the relational expression “Gave ≧ G1” is satisfied (see P303, “YES” in step S303 in FIG. 24).

  The image data analysis unit 160 is positioned downstream in the sub-scanning direction by the drum pitch (Ydrum) from the position of the pixel that was the object of the previous analysis process, that is, the position of the 16 pixel × 16 pixel block related to the ghost generation image. The average value (average value of pixel values) of the 16 pixel × 16 pixel block is analyzed (P304, see step S304 in FIG. 24), and based on the result of this analysis, the 16 pixel × 16 pixel block located downstream is analyzed. An average value Rave is obtained (see P305, step S305 in FIG. 24).

In this example, the 16 pixel × 16 pixel block located downstream in P304 is a block in the image corresponding to “Band _- 2” indicating the second band.

The image data analysis unit 160 obtains a contrast difference ΔC between the average value Gave of the 16 pixel × 16 pixel block related to the image on the ghost occurrence side and the average value Rave of the 16 pixel × 16 pixel block related to the image on the ghost reception side, It is recognized that the calculated contrast difference ΔC matches the relational expression “C1 ≦ contrast difference ΔC ≦ C2” (see P306, step S306 “C1 ≦ ΔC ≦ C2” in FIG. 24). The defect occurrence prediction flag is set to the flag value “2” (primary setting) corresponding to the average value Rave of the pixel × 16 pixel block (block in the second band “Band _- 2” in this example) (P307, (See step S309 in FIG. 24).

  When the image data analysis unit 160 sets the flag value “2” in the defect occurrence prediction flag corresponding to the average value Rave of the 16 pixel × 16 pixel block to be analyzed as described above (primary setting), The number of flag values “2” is counted.

  The image data analysis unit 160 determines that the position of the last pixel (pixel data) in the 16 pixel × 16 pixel block to be analyzed relating to the band corresponding to the image on the ghost receiving side is the band analysis end position, for example, When it is recognized that the coordinate value is not (Xmax, Ydrum2), the next 16 pixel × 16 pixel block, that is, the next pixel (next line) related to the image on the ghost occurrence side is scanned and image data analysis is performed (P308, Step S311 “NO” in FIG. 24).

Note that (Xmax, Ydrum2) means the coordinate value of the lower right corner of the drawing area corresponding to the second band “Band _- 2” (the coordinate value of the pixel located at the lower right corner).

The image data analysis unit 160 performs the same processing as the processing of P302 to P307, and then the analysis target related to the band corresponding to the image on the ghost receiving side (the second band “Band _- 2” in this example). It is recognized that the position of the last pixel (pixel data) in the 16 pixel × 16 pixel block is the band analysis end position, for example, (Xmax, Ydrum2) coordinate value (P309, step S311 in FIG. 24). See "YES").

When the image data analysis unit 160 recognizes that it is the band analysis end position as described above, a cumulative count number (cumulative count value) of the flag value “2” is set in advance. It is determined whether or not the count number is N or more (whether the relational expression “cumulative count number ≧ N” is satisfied), and when the relational expression “cumulative count number ≧ N” is satisfied as a result of this determination, P310, step S312 “≧ N” in FIG. 24), and the flag value “2” is set in the defect occurrence prediction flag corresponding to the second band “Band _- 2” (P311, step S315 in FIG. 24). reference).

The image data analysis unit 160 outputs the defect occurrence prediction flag (flag value “2”) related to the second band “Band _- 2” to the image output device control unit 210 of the image output device 200 (P312). FIG. 24, step S316).

The image data analysis unit 160 performs image data analysis processing on the drawing data corresponding to the third band “Band _- 3” (P313), and thereafter, the drawing data corresponding to the fourth band “Band _- 4”. Perform image data analysis processing.

That is, the image data analysis unit 160 scans a block of 16 pixels × 16 pixels for drawing data corresponding to the fourth band “Band _- 4”, and performs image data analysis (P314, step S301 in FIG. 24). reference).

  The image data analysis unit 160 obtains an average value (average value of pixel values) Gave of 16 pixels × 16 pixel blocks to be analyzed (P315, see step S302 in FIG. 24), and the average value of the 16 pixels × 16 pixel blocks. Based on the Gave and the flag setting information 1900 (see FIG. 19), it is recognized that the relational expression “Gave ≧ G1” is established (see P316, step S303 “YES” in FIG. 24).

The image data analysis unit 160 is positioned downstream in the sub-scanning direction by the drum pitch (Ydrum) from the position of the pixel that was the object of the previous analysis process, that is, the position of the 16 pixel × 16 pixel block related to the ghost generation image. The average value (average value of the pixel values) of the 16 pixel × 16 pixel block (in this example, the block in the fourth band “Band _- 4”) is analyzed (see P317, step S304 in FIG. 24), and this analysis is performed. Based on the result, the average value Rave of the 16 pixel × 16 pixel block located downstream is obtained (see P318, step S305 in FIG. 24).

The image data analysis unit 160 relates to the average value Gave of a 16 pixel × 16 pixel block (block in the third band “Band _- 3” in this example) related to the image on the ghost generation side and 16 related to the image on the ghost reception side. The contrast difference ΔC with respect to the average value Rave of the pixel × 16 pixel block (in this example, the block in the fourth band “Band _- 4”) is obtained, and the obtained contrast difference ΔC is “contrast difference ΔC> C2”. Recognizing that the relational expression is satisfied (see step S306 “ΔC> C2” in P319 in FIG. 24), the 16 pixel × 16 pixel block to be analyzed (in this example, the block in the fourth band “Band _- 4”) ) Is set to the flag value “1” (primary setting) corresponding to the average value Rave (P320, FIG. 24). See step S308).

  When the image data analysis unit 160 sets (primary setting) the flag value “1” in the defect occurrence prediction flag corresponding to the average value Rave of the 16 pixel × 16 pixel block to be analyzed as described above, The number of flag values “1” is counted.

  The image data analysis unit 160 determines that the position of the last pixel (pixel data) in the 16 pixel × 16 pixel block to be analyzed relating to the band corresponding to the image on the ghost receiving side is the band analysis end position, for example, When it is recognized that the coordinate value is not (Xmax, Ydrum4), the next 16 pixel × 16 pixel block, that is, the next pixel (next line) related to the image on the ghost generation side is scanned and image data analysis is performed (P321, Step S311 “NO” in FIG. 26).

Note that (Xmax, Ydrum4) means the coordinate value of the lower right corner of the drawing area corresponding to the fourth band “Band _- 4” (the coordinate value of the pixel located at the lower right corner).

The image data analysis unit 160 performs processing similar to the processing of P302 to P307, and then the analysis target related to the band corresponding to the image on the ghost receiving side (the fourth band “Band _- 4” in this example). It is recognized that the position of the last pixel (pixel data) in the 16 pixel × 16 pixel block is the band analysis end position, for example, (Xmax, Ydrum4) coordinate value (P322, step S311 in FIG. 24). See "YES").

When the image data analysis unit 160 recognizes that it is the band analysis end position as described above, a cumulative count number (cumulative count value) of the flag value “1” is set in advance. It is determined whether the count number is N or more (whether the relational expression “cumulative count number ≧ N” is satisfied). As a result of the determination, the relational expression “cumulative count number ≧ N” is not satisfied and is set in advance. When the relational expression of “M ≦ cumulative count number <N” is satisfied when it is equal to or greater than the predetermined count number M and is less than the predetermined count number N (see P323, step S312 “M ≦ ˜ <N” in FIG. 24). In response to the fourth band “Band _- 4”, a flag value “1” is set in the defect occurrence prediction flag (see P324, step S314 in FIG. 24).

The image data analysis unit 160 outputs the defect occurrence prediction flag (flag value “1”) related to the fourth band “Band _- 4” to the image output device control unit 210 of the image output device 200 (P325). FIG. 24, step S316).

Then, the image data analysis unit 160 performs an image data analysis process on the drawing data corresponding to the fifth band “Band _- 5” (P326), and further draws data corresponding to the other bands for the image data. After performing the analysis process, when it is recognized that it is the analysis end position in the image data analysis process for the drawing data corresponding to the final band “Band _- last” (P327, Step S317 “YES” in FIG. 24). The image data analysis processing for the drawing data 2500 is terminated.

  (Embodiment 4)

  Next, a functional configuration of a printer to which the image forming apparatus having the image processing apparatus according to the fourth embodiment is applied will be described.

  The printer of the fourth embodiment has the same configuration and function as the printer 10 of the first embodiment shown in FIGS. Further, the printer 10 according to the third embodiment performs a printing process similar to the printing process performed by the printer 10 according to the first embodiment shown in FIG.

  In the fourth embodiment, the rendering unit 140, the storage unit 150, and the image data analysis unit 160 are slightly different in function from those in the first embodiment, and the differences will be described next. .

  The drawing unit 140 is based on the PDL interpretation result read from the storage unit 130 and is an area formed by the length corresponding to the drum pitch in the main scanning direction and the sub-scanning direction (hereinafter referred to as “drum pitch drawing”). The image data (drawing data) is drawn in units of “area”), the image data (drawing data) drawn data drawn in units of the drum pitch drawing area is stored in the storage unit 150, and the drawing process is terminated. The image data analysis unit 160 is notified of the fact.

  When the drawing unit 140 receives a drawing request for the next image data from the image data analysis unit 160, the drawing unit 140 draws image data (drawing data) in units of the next drum pitch drawing area and stores it in the storage unit 150.

  The storage unit 150 stores image data in the latest drum pitch drawing area unit.

  In response to the notification from the drawing unit 140 that the drawing process has been completed, the image data analysis unit 160 acquires the image data (drawing target) of the processing target (drum pitch drawing area unit) from the storage unit 150 and acquires the image data. Perform analysis processing.

  When the image data analysis process for the image data in the drum pitch drawing area unit) is completed, the image data analysis unit 160 requests the drawing unit 140 to perform a drawing process related to the image data in the next drum pitch drawing area unit.

  As described above, in the fourth embodiment, the drawing unit 140 and the image data analysis unit 160 cooperate to perform the image data analysis process.

  Next, image data analysis processing by the cooperation of the drawing unit 140 and the image data analysis unit 160 in the image processing apparatus 100 of the printer 10 according to the fourth embodiment will be described with reference to FIG.

  FIG. 27 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 160 is performed under the following preconditions (1) to (7).

  (1) For example, in the main scanning direction, thinning scanning is performed with 16 pixels and image data analysis is performed.

  It should be noted that the image data analysis process is performed by performing a thinning scan with 16 pixels in the main scanning direction if the area related to the image on the ghost generation side and the area related to the image on the ghost receiving side are not large to some extent. This is because, for example, even if scanning is performed while calculating the average value of the pixel values of 16 pixels and the determination of the defect occurrence prediction flag is performed, there is no problem in the ghost occurrence prediction process.

  (2) Analyzing the drawn drum pitch drawing area unit image, that is, image data.

  (3) Analyze in units of jobs (JOB).

  (4) Analyze with CMYK data.

  (5) The flag is temporarily set based on the setting table, the flag within one page is cumulatively counted, and the flag is finally set for each page.

  (6) The flag value of the defect occurrence prediction flag information is “0”, “1”, and “3”, and the defect occurrence prediction flag is at three levels.

  (7) Flag setting information 2800 shown in FIG. 28 that is referred to by the image data analysis unit 160 is stored in a storage unit such as a ROM. The flag setting information 2800 is stored in the storage unit for each of the CMYK colors. Image data analysis processing is performed based on the flag setting information 2800 and the pixel values (gradation values) of 16 pixels to be analyzed.

  Now, as shown in FIG. 27, the drawing unit 140 draws an image (image data) in units of drum pitch drawing areas based on the PDL interpretation result read from the storage unit 120 (step S401), and this drum pitch drawing. The image data (CMYK data) in units of areas is stored in the storage unit 150, and the image data drawing unit 160 is notified that the drawing process has been completed.

  The image data analysis unit 160 receives the notification that the drawing process is finished from the drawing unit 140, and the CMYK data data for the drum pitch drawing area unit image data (drawing data) stored in the storage unit 150. According to the format, for example, image data of 16 pixels is scanned in the main scanning direction (step S402).

  Note that the image (image data) in units of the drum pitch drawing area scanned in step S402 corresponds to the image on the ghost occurrence side.

  The image data analysis unit 160 obtains an average value of pixel values (tone values) related to the scanned image data of 16 pixels, and defines the obtained average value of the image data as image data “Gdata”.

  When the image data analysis unit 160 that has obtained the image data “Gdata” requests the drawing unit 140 to perform drawing processing related to the image data of the next drum pitch drawing area unit, the drawing unit 140 is the target of the previous analysis processing. A drum pitch drawing area unit image (image data) is drawn downstream in the sub-scanning direction by a drum pitch (Ydrum) from the position of the drum drum drawing area unit image (image data). Then, the image (image data) in units of the drum pitch drawing area is overwritten in the storage unit 150, and the image data analysis unit 160 is notified that the drawing process is finished.

  Note that the image (image data) of the drum pitch drawing area unit drawn in step S403 corresponds to the image on the ghost receiving side.

  The image data analysis unit 160 that has received the notification that the drawing processing has been completed converts the image (image data) of the drum pitch drawing area unit corresponding to the image on the ghost receiving side into image data of 16 pixels in the main scanning direction. An average value of the pixel values (gradation values) concerned is obtained (step S404), and the obtained average value of the image data is defined as image data “Rdata”.

  The image data analysis unit 160 reads flag setting information 2800 for each color of CMYK colors from the storage unit 150 (see FIG. 28), and reads the flag setting information 2800 for each color, the image data “Gdata”, and the image data “Rdata”. The flag value is obtained on the basis of “” (step S405). When the flag value is “0”, the flag value “0” is set (primary setting) to the defect occurrence prediction flag (step S406), and the flag value “1”. In this case, the flag value “1” is set (primary setting) in the defect occurrence prediction flag (step S407). In the case of the flag value “2”, the flag value “2” is set in the defect occurrence prediction flag (primary setting). (Step S408).

  For example, when the image data “Gdata” means color data with a gradation value “70%”, for example, the image data “Rdata” means color data with a gradation value “5%” In this case, the flag value is “0”, and when the color data indicates the gradation value “20%”, the flag value is “1”, and the color data indicates the gradation value “30%”. If it is, the flag value is “2”.

  When step S406 is finished, step S407 is finished, or step S408 is finished, the image data analysis unit 160 counts the number of the flag values for each set flag value (step S409).

  The image data analysis unit 160 determines whether or not the image data analysis processing for the image data corresponding to one page has ended (step S410), and as a result of the determination, the image data analysis processing has not ended. In this case, the process returns to step 402 so that the next pixel (next line), that is, the image (image data) of the next drum pitch drawing area unit is drawn by the control unit 140.

  If the image data analysis unit 160 determines in step S410 that the image data analysis processing for the image data corresponding to one page has been completed, the cumulative count number (cumulative count value) of the flag value “2” is set. Whether the first relational expression “M ≦ cumulative count number <N” is satisfied, or whether the cumulative count number is previously set is greater than or equal to a predetermined count number M and smaller than the predetermined count number N. It is determined whether it is equal to or greater than a predetermined count number N, that is, whether the second relational expression “cumulative count number ≧ N” is satisfied (step S411).

  If the image data analysis unit 160 determines in step S411 that both the first relational expression and the second relational expression are not established, the flag value “0” is adopted for the defect occurrence prediction flag. (Step S412) When it is determined that the first relational expression is satisfied, the flag value “1” is adopted for the defect occurrence prediction flag (Step S413), and further, the second relation When it is determined that the equation is established, the flag value “2” is adopted for the defect occurrence prediction flag (step S414).

  If the flag value “0” is adopted for the defect occurrence prediction flag in step S412, the image data analysis unit 160 sets the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “0” is set (step S415). The flag value “0” is also set for the other parameter change instruction flags.

  If the image data analysis unit 160 adopts the flag value “1” for the defect occurrence prediction flag in step S 413, the image data analysis unit 160 sets the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “1” is set (step S416). The flag value “0” is set for the other parameter change instruction flags.

  If the image data analysis unit 160 adopts the flag value “2” for the defect occurrence prediction flag in step S 414, the image data analysis unit 160 sets the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “2” is set (step S417). The flag value “0” is set for the other parameter change instruction flags.

  When the flag value “1” or the flag value “2” is set in the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610 as described above, the gradation correction unit 172 The parameter value of the gradation parameter (gradation correction parameter) is changed according to the flag value “1” or the flag value “2”.

  The image data analysis unit 160 outputs the final first defect occurrence prediction flag information 1610 to the image processing unit 170 when step S415 is completed, step S416 is completed, or step S417 is completed. At the same time, it is determined whether or not the image data analysis processing for all pages has been completed (step S418).

  If the image data analysis unit 160 determines in step S418 that the image data analysis processing for all pages has been completed, the image data analysis unit 160 determines whether drawing of images for all pages has been completed (step S419). Here, when it is determined that drawing of images for all pages has been completed, the image data analysis processing is ended.

  If it is determined in step S418 that the image data analysis processing for all pages has not been completed, the process returns to step S401.

  If it is determined in step S419 that drawing of images for all pages has not been completed, the process returns to step S401.

  By the way, in the image processing unit 170 that has received the first defect occurrence prediction flag information 1610, the color conversion unit 171 performs the color conversion process based on the flag value “0” set in the color parameter change instruction flag 1611. . In this case, the color parameter is not changed, and the color conversion process is performed based on the stored content (color parameter) of the color parameter storage unit 171b.

  In addition, the halftone dot generation unit 173 performs a halftone dot generation process (screen process) based on the flag value “0” set in the halftone dot parameter change instruction flag 1613. In this case, the halftone dot parameters are not changed, and the halftone dot generation process is performed based on the storage contents (halftone dot parameters) of the halftone dot parameter storage unit 173b.

  Further, the gradation correction unit 172 performs gradation correction processing based on the flag value “0”, flag value “1”, or flag value “2” set in the gradation parameter change instruction flag 1612.

  Here, when the flag value “1” or the flag value “2” is set in the gradation parameter change instruction flag 1612, the gradation parameter setting unit 172a of the gradation correction unit 172, based on the flag value, The stored contents (gradation parameters) of the gradation parameter storage unit 172b are updated. Note that when the flag value “0” is set in the gradation parameter change instruction flag 1612, the gradation parameter is not changed.

  Then, the gradation correction unit 172 performs gradation correction on the image data from the drawing unit 140 based on the storage contents of the gradation parameter storage unit 172b and the gradation correction information 2900 shown in FIG. FIG. 30 shows gradation correction information 3000 in which the gradation correction information 2900 in the graph format is rewritten into the contents of the table format.

  Incidentally, in FIG. 29 and FIG. 30, the parameter [1] has the content of increasing the density in the Cin 20 to 50% region where ghost is likely to occur on the receiving side. This means that ghosts are less likely to occur.

  Parameter [2] has the content of increasing the density in the Cin 20 to 50% region where ghosts are likely to occur on the receiving side and decreasing the concentration in the Cin 80 to 100% region where ghosts are likely to occur on the receiving side. . This means that ghosts are less likely to occur.

  In FIG. 30, the input gradation information corresponds to Cin [unit:%] on the horizontal axis in FIG. 29, and the output gradation information corresponds to Cout [unit:%] on the vertical axis in FIG. In the output gradation information, the correction parameter [0] means the gradation parameter (gradation correction parameter) [0] corresponding to the flag value “0”, and the correction parameter [1] corresponds to the flag value “1”. The gradation parameter (gradation correction parameter) [1] means the correction parameter [2] means the gradation parameter (gradation correction parameter) [2] corresponding to the flag value “2”.

  For example, when the gradation value of the image data is “50%” and the flag value “0” is set in the gradation parameter change instruction flag 1612, the gradation value is “42%”. When the flag value “1” is set, the gradation value is “56%”, and when the flag value “2” is set, the gradation value is “54%”.

  As described above, in the fourth embodiment, when a ghost is predicted to be generated by the image data analysis process, the gradation parameter (gradation correction parameter) is changed as shown in FIG. Yes.

  FIG. 31 shows an overview of the flow of the first defect occurrence prediction flag information 1610 in the printer 10 shown in FIG. 1 and an overview of how the parameters are changed. In this example, when it is predicted that a ghost will occur, a gradation parameter (gradation correction parameter) changing process is performed by the gradation correction unit 172, and the corresponding parameter is calculated by the color conversion unit 171 and the halftone generation unit 173. This shows how the change process is not performed.

  Incidentally, the first defect occurrence prediction flag information 1610 is input to the image processing unit 170 and is input to the color conversion unit 171, the gradation correction unit 172, and the halftone generation unit 173, respectively.

  The image data analysis process described above will be described with reference to FIGS. 32 and 33. FIG.

  FIG. 32 shows image data to be analyzed (image data to be printed) 3200 in page units.

  As shown in FIG. 32, the image data 3200 includes a plurality (N) of image data 3200-1, 3200-2,..., 3200-N corresponding to a plurality (N) pages.

  The drawing area related to the image data 3200-1 corresponding to the first page has XY coordinate values (0, 0), (Xmax, 0), (0, 0) of the upper left corner, upper right corner, lower left corner, and lower right corner. Ymax) and (Xmax1, Ymax1).

  The XY coordinate values of the upper left corner and upper right corner of the drawing area related to the image data 3200-2 corresponding to the second page are (0, 0) and (Xmax 2, 0). Incidentally, the XY coordinate values of the lower left corner and the lower right corner of this drawing area are (0, Ymax2) and (Xmax2, Ymax2) (not shown).

  The XY coordinate values of the lower left corner and the lower right corner of the drawing area related to the image data 3200-N corresponding to the last page (N page) are (0, Ymax) and (Xmax, Ymax). The drawing area includes XY coordinate values (0, “Ymax−Ydrum”) and XY coordinate values (Xmax, “Ymax−Ydrum”).

  This XY coordinate value (Xmax, “Ymax−Ydrum”) means the end position of the image data analysis processing for a plurality of pages.

  The XY coordinate values (Xmax, Ymax) mean the drawing end positions for a plurality of pages.

  In FIG. 32, each value of (Xa, Yb), (Xc, Yd) is an arbitrary coordinate value in the drawing area, Ydum indicates the drum pitch, and (Xmax1, Ymax1) is the first page. The end position is indicated, and (Xmax2, 0) indicates the end position of the first line related to the second page.

  Each value of Xa, Yb, Xc, Yd, Xe, and Yf is an arbitrary coordinate value in the drawing area, and Ydum indicates a drum pitch.

  In the example shown in FIG. 32, a drawing area 3201 formed by XY coordinate values of (0, “Ymax−Ydrum”), (Xmax, “Ymax−Ydrum”), (0, Ymax), and (Xmax, Ymax). Is an area where image data analysis (scanning) is not required because there is no ghost effect.

  FIG. 33 shows a state of the image data analysis processing by the cooperation of the drawing unit 140 and the image data analysis unit 160.

  As shown in FIG. 33, when the drawing unit 140 draws an image (image data) in units of drum pitch drawing areas (see P401, step S401 in FIG. 27), the image data analysis unit 160 displays the drum pitch drawing area units. The image (the image data on the ghost generation side) is thinned and scanned with 16 pixels in the main scanning direction (see P402, step S402 in FIG. 27), and the scanned image data “Gdata” (pixel value (gradation value) of 16 pixels). Average).

  The image data analysis unit 160 scanned in this way requests the drawing unit 140 to perform a drawing process on an image (image data) in the next drum pitch drawing area unit.

  Upon receiving this drawing processing request, the drawing unit 140 is downstream in the sub-scanning direction by the drum pitch (Ydrum) from the position of the image (image data) in the drum pitch drawing area unit that was the object of the previous analysis processing. An image (image data on the ghost receiving side) of the drum drum drawing area unit positioned is drawn (see P403, step S403 in FIG. 27).

  The image data analysis unit 160 calculates the average of 16-pixel image data “Rdata” (pixel value (gradation value)) in the main scanning direction for an image (image data) in a drum pitch drawing area unit corresponding to the ghost receiving image. Value) is obtained (see P404, step S404 in FIG. 27).

  The image data analysis unit 160 reads flag setting information 2800 for each color of CMYK colors from the storage unit 150 (see FIG. 28), and reads the flag setting information 2800 for each color, the image data “Gdata”, and the image data “Rdata”. ”(P405, see step S405 in FIG. 27). For example, when the flag value is“ 2 ”, for example, the flag value“ 2 ”is set (primary setting) for the defect occurrence prediction flag (P406). FIG. 27, step S408).

  Here, the image data analysis unit 160 counts (cumulatively counts) the number of the set flag value “2”.

  When the image data analysis unit 160 recognizes that the image data corresponding to one page is not the image data analysis processing position, the process returns to P401 (P408).

  When the image data analysis unit 160 recognizes the image data analysis processing position for the image data corresponding to one page, the cumulative count number (cumulative count value) of the flag value “2” is the cumulative count number. Is greater than or equal to a predetermined count number N set in advance (whether the relational expression of “cumulative count number ≧ N” is satisfied), and as a result of this determination, the relation of “cumulative count number ≧ N” When the expression is satisfied (see P409, step S411 “≧ N” in FIG. 27), a flag value “2” is set for the defect occurrence prediction flag (see P410, step S414 in FIG. 27).

  When the flag value “2” is set for the defect occurrence prediction flag in P410, the image data analysis unit 160 sets the flag value “2” in the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. Is set (see step P411, step S417 in FIG. 27). The flag value “0” is set for the other parameter change instruction flags.

  The image data analysis unit 160 recognizes, for example, (Xmax, “Ymax−Ydrum”) coordinate values indicating the end of all page analysis for the drawn image data (drawing data) (step P412, step S418 in FIG. 27 [YES]. In addition, when (Xmax, Ymax) coordinate values indicating that all page rendering is completed are recognized (see step P413 and step S419 “YES” in FIG. 27), this image data analysis is terminated.

  (Embodiment 5)

  Next, a functional configuration of a printer to which the image forming apparatus having the image processing apparatus according to the fifth embodiment is applied will be described.

  The printer of the third embodiment has the same configuration and function as the printer 10 of the first embodiment shown in FIGS. Further, the printer 10 according to the third embodiment performs a printing process similar to the printing process performed by the printer 10 according to the first embodiment shown in FIG.

  In the fifth embodiment, the function of the image data analysis unit 160 is slightly different from that in the first embodiment, and the difference will be described next.

  The image data analysis unit 160 uses the environment information from the image output device control unit 210 for the defect occurrence prediction flag information determined by the image data analysis process, particularly the flag value set in the first defect occurrence prediction flag information 1610, A flag value replacement process is performed based on the paper quality information and the temporal characteristic information.

  First defect occurrence prediction flag information 1610 in which the flag value after the replacement process is set is output to the image processing unit 170.

  Next, image data analysis processing by the image data analysis unit 160 of the image processing apparatus 100 of the printer 10 according to the fifth embodiment will be described with reference to FIG.

  FIG. 34 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 160 is performed under the following preconditions (1) to (6).

  (1) Analysis is performed in units of one pixel.

  (2) The drawn image (image data) is sequentially analyzed from the first line.

  (3) Analyze in units of jobs (JOB).

  (4) In order to detect a white ghost, an edge is detected, a contrast and a white distance (area) are determined, and a flag is primarily set. Further, the flag is finally set in consideration of the image output apparatus information.

  (5) The flag value of the defect occurrence prediction flag information is “0”, “1”, and “3”, and the defect occurrence prediction flag is at three levels.

  (6) The storage means such as the ROM stores flag setting information 3500 shown in FIG. 35 and flag replacement information 3600 shown in FIG. 36 which are referred to by the image data analysis unit 160. The flag setting information 3500 is stored in the storage means for each color of RGB.

  The flag setting information 3500 is stored in the storage means for each color of RGB. Image data analysis processing is performed based on the flag setting information 3500 and the pixel value (gradation value) of the pixel to be analyzed.

  The image data analysis unit 160 acquires image data (drawing data) of processing units (pages) stored in the storage unit 150, and for the image data (RGB data) corresponding to the acquired one page, According to the data format, scanning is performed in units of pixels sequentially from the first line (step S501).

  The image data analysis unit 160 determines whether or not an edge in the main scanning direction or the sub-scanning direction has been detected for the image data related to the scanned line (step S502). If the edge is not detected, the process proceeds to step S501. Returning, if an edge in the main scanning direction or the sub-scanning direction is detected, whether the data value (color gradation value) is equal to or higher than preset first color information (color gradation value) G1. (Whether or not the relational expression “data value ≧ G1” is satisfied), or whether or not it is equal to or less than preset second color information (color gradation value) G2 (≠ G1) (“ Whether or not the relational expression of “data value ≦ G2” is satisfied ”is determined (step S503).

  The image data analysis unit 160 that has determined that the relational expression “data value ≦ G2” is satisfied in step S503 calculates the contrast of the edge portion (step S504), and the calculated contrast is equal to or higher than the preset contrast C1. (Whether or not the relational expression of calculated contrast ≧ C1 is satisfied) (step S505). If the relational expression of “calculated contrast ≧ C1” is satisfied as a result of the determination, an edge is determined. An inter-distance (area) is calculated (step S506).

  The image data analysis unit 160 determines whether or not the edge distance (area) calculated in step S506 is equal to or smaller than the preset distance S1 (whether the relational expression “edge distance (area) ≦ S1” is satisfied). (Step S507), and if the above relational expression is satisfied as a result of the determination, the pixel of the pixel located downstream in the sub-scanning direction by the drum pitch from the position of the pixel to be analyzed The value (tone value) is scanned (step S508).

  If it is determined in step S503 that the relational expression “data value ≧ G1” is established, the process proceeds to step S508.

  After completing step S508, the image data analysis unit 160 sets a flag based on the flag setting information 3500 shown in FIG. 35 (step S509).

  After completing step S509, the image data analysis unit 160 sets the flag value “1” to the defect occurrence prediction flag (primary setting) or sets the flag value “2” to the defect occurrence prediction flag (primary setting) (step S510). Step S511).

  If the image data analysis unit 160 determines in step S503 that the relational expressions “data value ≧ G1” and “data value ≦ G2” are not satisfied, “calculated contrast ≧ C1” is satisfied in step S505. When it is determined that the relational expression is not established, the flag value “0” is set in the defect occurrence prediction flag when the relational expression “distance between edges (area) ≦ S1” is not established in step S507 (primary (Step S512).

  When step S510 is finished, step S511 is finished, or step S512 is finished, the image data analysis unit 160 determines whether or not the analysis processing of the image data corresponding to one page is finished (step S513). If it is determined that the analysis process has not been completed, the process returns to step S501. On the other hand, if the analysis process for image data corresponding to one page is completed, the process returns to step S510, step S511, or step S512. With respect to the flag value of the set defect occurrence prediction flag, a flag value replacement process is performed based on the environmental information, the paper quality information, the temporal characteristic information, and the flag replacement information 3600 (see FIG. 36) from the image output device control unit 210. (Step S514).

  Here, the replacement process will be described with reference to FIG. When the set sheet is thick and the environment is low humidity, a value increased by “+2” is reset as the flag value with respect to the flag value that is set initially. In this fifth embodiment, since the flag value “2” is the maximum value, “2” is reset when the result obtained by adding the predetermined value of the flag replacement information 3600 to the flag value initially set exceeds “2”. To do.

  The image data analysis unit 160 employs the flag value “0”, the flag value “1”, or the flag value “2” for the defect occurrence prediction flag based on the result of the flag replacement process (step S515). , Step S516, Step S517).

  If the image data analysis unit 160 adopts the flag value “0” for the defect occurrence prediction flag in step S515, the image data analysis unit 160 sets the halftone dot parameter change instruction flag 1613 in the first defect occurrence prediction flag information 1610. A flag value “0” is set (step S516). The flag value “0” is also set for the other parameter change instruction flags.

  If the image data analysis unit 160 adopts the flag value “1” for the defect occurrence prediction flag in step S516, the image data analysis unit 160 sets the halftone dot parameter change instruction flag 1613 in the first defect occurrence prediction flag information 1610. A flag value “1” is set (step S519). The flag value “0” is set for the other parameter change instruction flags.

  If the image data analysis unit 160 adopts the flag value “2” for the defect occurrence prediction flag in step S517, the image data analysis unit 160 sets the halftone dot parameter change instruction flag 1613 in the first defect occurrence prediction flag information 1610. A flag value “2” is set (step S520). The flag value “0” is set for the other parameter change instruction flags.

  As described above, when the flag value “1” or the flag value “2” is set in the halftone parameter change instruction flag 1613 in the first defect occurrence prediction flag information 1610, the halftone generation unit 173 causes The parameter value of the halftone dot parameter (halftone dot generation parameter) is changed according to the flag value “1” or the flag value “2”.

  The image data analysis unit 160 outputs the final first defect occurrence prediction flag information 1610 to the image processing unit 170 when step S518 ends, when step S519 ends, or when step S520 ends. At the same time, it is determined whether or not the image data analysis processing for all pages has been completed (step S521).

  If the image data analysis unit 160 determines in step S521 that the image data analysis process for all pages has not been completed, the process returns to step S501, while the image data analysis process for all pages is completed. If it is determined that the image data has been analyzed, the image data analysis process is terminated.

  In the fifth embodiment, when it is predicted that a ghost will occur, the halftone dot parameter is changed. Therefore, in the first defect occurrence prediction flag information 1610, the color parameter change instruction flag 1611 and the floor parameter are changed. The adjustment parameter flag 1622 is set with a flag value “0”, and the halftone dot parameter change instruction flag 1613 is set with a flag value “0”, a flag value “1”, or a flag value “2”.

  In the image processing unit 170 that has received the first defect occurrence prediction flag information 1610 in which such a flag value is set, the color conversion unit 171 sets the flag value “0” set in the color parameter change instruction flag 1611. The color conversion process is performed based on the above. In this case, the color parameter is not changed, and the color conversion process is performed based on the stored content (color parameter) of the color parameter storage unit 171b.

  In addition, the gradation correction unit 172 performs gradation correction processing based on the flag value “0” set in the gradation parameter change instruction flag 1612. In this case, the gradation parameter is not changed, and the color conversion process is performed based on the stored content (gradation parameter) of the gradation parameter storage unit 172b.

  Further, the halftone dot generation unit 173 performs halftone dot generation processing (screen processing) based on the flag value “0”, flag value “1”, or flag value “2” set in the halftone dot parameter change instruction flag 1613. To do.

  When the flag value “1” or the flag value “2” is set in the halftone parameter change instruction flag 1613, the halftone dot parameter setting unit 173a of the halftone dot generation unit 173 determines the halftone dot parameter based on the flag value. The storage content (halftone dot parameter) of the storage unit 173b is updated. Note that when the flag value “0” is set in the halftone dot parameter change instruction flag 1613, the halftone dot parameter is not changed.

  Here, when the halftone dot parameter (halftone dot generation parameter) is a parameter meaning the number of screen lines, a flag value “0”, a flag value “1” set in the halftone dot parameter change instruction flag 1613 and Assume that the parameter values of the halftone dot parameters (halftone dot generation parameters) respectively corresponding to the flag value “2” are “0”, “−α1”, and “−α2”.

  Note that “| α1 |” and “| α2 |” mean the amount of change in the number of screen lines. In this case, the parameter value is determined in advance so that the relational expression “| α1 | <| α2 |” is satisfied.

  Incidentally, when the flag value “2” is set in the halftone parameter change instruction flag 1613, the parameter value of the halftone parameter corresponding to this flag value “2” is the parameter value of the halftone parameter “0”. In this case, “−α2” means a screen line number smaller than the screen line number.

  In the fifth embodiment, as shown in FIG. 37, the image data analysis unit 160, the defect occurrence prediction flag information obtained by the image data analysis process, the environment information, the paper quality information, and the time-lapse information from the image output device control unit 210. A flag replacement process is performed based on the characteristic information, and the flag value of the defect occurrence prediction flag information is reset based on the result of the flag replacement process.

  FIG. 37 shows an overview of the flow of the first defect occurrence prediction flag information 1610 in the printer 10 shown in FIG. 1 and an overview of how the parameters are changed. In this example, when a ghost is predicted to occur, the halftone dot parameter changing process is performed by the halftone dot generating unit 173, and the corresponding parameter changing process is not performed by the color converting unit 171 and the gradation correcting unit 172. It shows a state.

  Incidentally, the first defect occurrence prediction flag information 1610 is input to the image processing unit 170 and is input to the color conversion unit 171, the gradation correction unit 172, and the halftone generation unit 173, respectively.

  The image data analysis process described above will be described with reference to FIG.

  FIG. 38 shows the state of image data analysis processing by the image data analysis unit 160.

  The image data to be analyzed in page units is the same as the image data in the case of the fourth embodiment shown in FIG. 32, and therefore detailed description thereof is omitted here.

  The image data analysis unit 160 scans image data (RGB data) corresponding to one page sequentially in units of pixels from the first line according to the RGB data format (P501, step S501 in FIG. 34). reference).

  The image data analysis unit 160 detects an edge of the image data in the main scanning direction or the sub scanning direction (see P502, step S502 in FIG. 34).

  In this example, for example, (“Xa + 2”, Yb) coordinate values and (“Xa + 14”, Yb) coordinate values are detected as edges.

  The image data analysis unit 160 recognizes that the data value (color gradation value) relating to the image on the ghost occurrence side is equal to or less than the preset second color information (color range) G2 (P503, FIG. 34). Step S503 “≦ G2”), and thereafter, the contrast of the edge (edge portion) detected in P502 is calculated (P504).

  In this case, the contrast of each edge portion corresponding to each coordinate value of (“Xa + 2”, Yb) and (“Xa + 14”, Yb) coordinate values is calculated as “255-0”, that is, “255”. "

  The image data analysis unit 160 calculates the distance (area) between the two edge portions detected in P502 (see P505, step S506 in FIG. 34).

  In this example, the distance (edge distance) between the edge corresponding to the (“Xa + 2”, Yb) coordinate value and the edge corresponding to the (“Xa + 14”, Yb) coordinate value is calculated.

  If the image data analysis unit 160 determines that the distance (area) between the edges calculated in P505 is equal to or less than the preset distance S1, the image data analysis unit 160 predicts that a white ghost will occur (P506), and then performs analysis processing. The pixel value (gradation value) of the pixel located downstream of the target pixel position in the sub-scanning direction by the drum pitch is scanned (see P507, step S508 in FIG. 34).

  The image data analysis unit 160 sets a flag based on the flag setting information 3500 (FIG. 35) (see P508, step S509 in FIG. 34), and sets a flag value “1” (primary setting) in the defect occurrence prediction flag. (See P509, step S510 in FIG. 34).

  If the image data analysis unit 160 determines that the image data analysis process corresponding to one page has not been completed, the image data analysis unit 160 performs P502 and subsequent steps to perform image analysis processing on the next pixel (next line) ( P510, see step S513 “NO” in FIG. 34).

  For example, if the image data analysis unit 160 detects (Xmax1, Ymax1) coordinate values and determines that the analysis processing of the image data corresponding to one page has ended (see P511, “YES” in step S513), the image Environmental information, paper quality information, and time-dependent characteristic information are acquired from the output device controller 210 (P512), and flag value replacement processing is performed based on these information and flag replacement information 3500 (P513, step of FIG. 34). (See S514).

  When the result of the flag replacement process in P513 is the flag value “2”, the image data analysis unit 160 adopts the flag value “2” for the defect occurrence prediction flag, and the first defect occurrence prediction flag information A flag value “2” is set in the halftone dot parameter change instruction flag of 1610 (see P514, step S517 of FIG. 34).

  In this example, the defect occurrence prediction flag for which the flag value “1” is set in P509 is changed to the flag value “2” by the flag replacement process in P513.

  When the image data analysis unit 160 detects the (Xmax, Ymax) coordinate value and determines that the image data analysis processing corresponding to all pages has been completed (see P515, step S521 “YES” in FIG. 34). ), The image data analysis process is terminated.

  (Embodiment 6)

  Next, a functional configuration of a printer to which the image forming apparatus having the image processing apparatus according to the sixth embodiment is applied will be described.

  The printer of the third embodiment has the same configuration and function as the printer 10 of the first embodiment shown in FIGS. Further, the printer 10 according to the third embodiment performs a printing process similar to the printing process performed by the printer 10 according to the first embodiment shown in FIG.

  Next, image data analysis processing by the image data analysis unit 160 of the image processing apparatus 100 of the printer 10 according to the fifth embodiment will be described with reference to FIG.

  FIG. 39 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 160 is performed under the following preconditions (1) to (6).

  (1) Analysis is performed in units of one pixel.

  (2) The drawn image (image data) is sequentially analyzed from the first line.

  (3) Analyze in units of jobs (JOB).

  (4) In order to detect a white ghost, an edge is detected, a contrast and a white distance (area) are determined, and a flag is primarily set. Further, the flag is finally set in consideration of the image output apparatus information.

  (5) The flag value of the defect occurrence prediction flag information is “0”, “1”, and “3”, and the defect occurrence prediction flag is at three levels.

  (6) In the storage means such as the ROM, the gradation correction information 2900 or gradation correction information 300 (see Embodiment 4) shown in FIG. 29 or FIG. The indicated flag setting information 3500 (see the fifth embodiment) is stored.

  Now, the image data analysis unit 160 acquires image data (drawing data) of a processing unit (page) stored in the storage unit 150, and performs RGB processing on the acquired image data (RGB data) corresponding to one page. According to the data format of the data, scanning is performed in pixel units sequentially from the first line (step S601).

  The image data analysis unit 160 determines whether or not an edge in the main scanning direction or the sub-scanning direction has been detected for the image data related to the scanned line (step S602). If the edge is not detected, the process proceeds to step S601. Returning, if an edge in the main scanning direction or the sub-scanning direction is detected, whether the data value (color gradation value) is equal to or higher than preset first color information (color gradation value) G1. (Whether or not the relational expression “data value ≧ G1” is satisfied), or whether or not it is equal to or less than preset second color information (color gradation value) G2 (≠ G1) (“ Whether or not a relational expression of “data value ≦ G2” is satisfied ”is determined (step S603).

  The image data analysis unit 160 that has determined that the relational expression “data value ≦ G2” is satisfied in step S603 calculates the contrast of the edge portion (step S604), and the calculated contrast is equal to or higher than the preset contrast C1. (Whether or not the relational expression of calculated contrast ≧ C1 is satisfied) (step S605). As a result of the determination, if the relational expression of “calculated contrast ≧ C1” is satisfied, an edge is determined. An inter-distance (area) is calculated (step S606).

  The image data analysis unit 160 determines whether or not the edge distance (area) calculated in step S606 is equal to or less than a preset distance S1 (whether the relational expression “edge distance (area) ≦ S1” is satisfied). (Step S607), and if the result of this determination is that the relational expression is satisfied, the pixel of the pixel located downstream in the sub-scanning direction by the drum pitch from the position of the pixel to be analyzed The value (tone value) is scanned (step S608).

  If it is determined in step S603 that the relational expression “data value ≧ G1” is established, the process proceeds to step S608.

  After completing step S608, the image data analysis unit 160 sets a flag based on the flag setting information 3500 shown in FIG. 35 (step S609).

  After completing step S609, the image data analysis unit 160 sets the flag value “1” to the defect occurrence prediction flag (primary setting) or sets the flag value “2” to the defect occurrence prediction flag (primary setting) (step S610). Step S611).

  If the image data analysis unit 160 determines in step S603 that the relational expressions “data value ≧ G1” and “data value ≦ G2” are not satisfied, “calculated contrast ≧ C1” is satisfied in step S605. When it is determined that the relational expression is not established, the flag value “0” is set in the defect occurrence prediction flag when the relational expression “distance between edges (area) ≦ S1” is not established in step S607 (primary (Step S612).

  When step S610 is finished, step S611 is finished, or step S612 is finished, the image data analysis unit 160 determines whether or not the image data analysis processing corresponding to one page is finished (step S613). ) If the result of this determination is that the analysis process has not ended, the process returns to step S601.

  When the image data analysis unit 160 finishes analyzing the image data corresponding to one page in step S613, the image data analysis unit 160 uses the flag value of the defect occurrence prediction flag set in step S610, step S611, or step S612 as the predetermined page. For example, the flag values of the first defect occurrence prediction flag and the second defect occurrence prediction flag for the first page are set (step S614).

  That is, the image data analysis unit 160 includes at least one of the charging parameter change instruction flag 1621, the exposure parameter change instruction flag 1622, the development parameter change instruction flag 1623, and the transfer parameter change instruction flag 1624 in the second defect occurrence prediction flag information 1620. A flag value “0”, a flag value “1”, or a flag value “2” is set for one parameter change instruction flag, and a flag value “0” is set for another parameter change instruction.

  The image data analysis unit 160 notifies the image output device control unit 210 of the image output device 200 of the second defect occurrence prediction flag information 1620 in which the flag value is set in this way (step S615).

  Further, the image data analysis unit 160 adopts the flag value “0”, the flag value “1”, or the flag value “2” for the first defect occurrence prediction flag (step S616, step S617, step S618).

  If the image data analysis unit 160 adopts the flag value “0” for the defect occurrence prediction flag in step S616, the image data analysis unit 160 sets the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “0” is set (step S619). The flag value “0” is also set for the other parameter change instruction flags.

  If the image data analysis unit 160 adopts the flag value “1” for the defect occurrence prediction flag in step S617, the image data analysis unit 160 sets the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “1” is set (step S620). The flag value “0” is set for the other parameter change instruction flags.

  If the image data analysis unit 160 adopts the flag value “2” for the defect occurrence prediction flag in step S618, the image data analysis unit 160 sets the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “2” is set (step S621). The flag value “0” is set for the other parameter change instruction flags.

  When the flag value “1” or the flag value “2” is set in the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610 as described above, the gradation correction unit 172 The parameter value of the gradation parameter (gradation correction parameter) is changed according to the flag value “1” or the flag value “2”.

  The image data analysis unit 160 outputs the final first defect occurrence prediction flag information 1610 to the image processing unit 170 when step S619 is completed, step S620 is completed, or step S621 is completed. At the same time, it is determined whether or not the image data analysis processing for all pages has been completed (step S622).

  If the image data analysis unit 160 determines in step S622 that the image data analysis process for all pages has not been completed, the process returns to step S601, while the image data analysis process for all pages is completed. If it is determined that the image data has been analyzed, the image data analysis process is terminated.

  By the way, in the image processing unit 170 that has received the first defect occurrence prediction flag information 1610, the color conversion unit 171 performs the color conversion process based on the flag value “0” set in the color parameter change instruction flag 1611. . In this case, the color parameter is not changed, and the color conversion process is performed based on the stored content (color parameter) of the color parameter storage unit 171b.

  In addition, the halftone dot generation unit 173 performs a halftone dot generation process (screen process) based on the flag value “0” set in the halftone dot parameter change instruction flag 1613. In this case, the halftone dot parameters are not changed, and the halftone dot generation process is performed based on the storage contents (halftone dot parameters) of the halftone dot parameter storage unit 173b.

  Further, the gradation correction unit 172 performs gradation correction processing based on the flag value “0”, flag value “1”, or flag value “2” set in the gradation parameter change instruction flag 1612.

  Here, when the flag value “1” or the flag value “2” is set in the gradation parameter change instruction flag 1612, the gradation parameter setting unit 172a of the gradation correction unit 172, based on the flag value, The stored contents (gradation parameters) of the gradation parameter storage unit 172b are updated. Note that when the flag value “0” is set in the gradation parameter change instruction flag 1612, the gradation parameter is not changed.

  Then, the gradation correction unit 172 stores the contents stored in the gradation parameter storage unit 172b and the gradation correction information 2900 of the fourth embodiment shown in FIG. 29 or the gradation correction information 3000 of the fourth embodiment shown in FIG. Based on the above, tone correction is performed on the image data from the drawing unit 140.

  Incidentally, the gradation parameters (gradation correction parameters) when the gradation parameter change instruction flag 1612 is the flag value “0”, the flag value “1”, and the flag value “2” are the same as those in the fourth embodiment. Similarly, parameter value “0” = correction parameter [0], parameter value “1” = correction parameter [1], and parameter value “1” = correction parameter [2].

  On the other hand, in the image output device control unit 210 that has received the second defect occurrence prediction flag information 1620, the flag value, environment information, and paper quality set in each parameter change instruction flag of the second defect occurrence prediction flag information 1620. Based on the information and the temporal characteristic information, the second defect occurrence prediction flag information 1620, that is, the flag value of each parameter change instruction flag is reset.

  The image output device control unit 210 then controls the parameter setting unit subordinate to the parameter storage unit that stores the parameter corresponding to the parameter change instruction flag in which the flag value “1” or the flag value “2” is reset. Request the parameter change process.

  For example, it is assumed that the flag value “1” is set in the transfer parameter change instruction flag 1624 in the second defect occurrence prediction flag information 1620 and the flag value “1” is set in the other parameter change instruction flags.

  In this case, the image output device controller 210 uses the flag value “1” of the transfer parameter change instruction flag 1624 in the second defect occurrence prediction flag information 1620 and the transfer parameter reset information 4000 shown in FIG. 40, for example. Then, reset the transfer parameters.

  In FIG. 40, the notification flag values “0”, “1”, and “2” correspond to the flag values “0”, “1”, and “2” set in the transfer parameter change instruction flag 1624.

  In the column of the transfer voltage Δ (volt), “−150” indicates a parameter value that means a transfer voltage that is “150 volts” lower than the predetermined transfer voltage. Similarly, “−300” indicates the predetermined transfer voltage. A parameter value indicating a transfer voltage that is "300 volts" lower than the voltage is shown.

  For example, when the flag value “1” is set in the transfer parameter change instruction flag 1624, the transfer parameter means a transfer voltage that is “150 volts” lower than a predetermined transfer voltage by the image output device controller 210. Reset to the parameter value.

  In the sixth embodiment, as shown in FIG. 41, the image processing apparatus 100 uses the gradation parameter change instruction flag 1622 of the first defect occurrence prediction flag information 1610 to change the gradation parameter. In the image output apparatus 200, the transfer parameter change instruction flag 1624 of the transfer parameter change instruction flag 1624 of the first defect occurrence prediction flag information 1620 from the image processing apparatus 100 and the environment information, paper quality information, and temporal characteristics information are set. The flag value is replaced, and the transfer parameter is changed based on the flag value after the flag replacement.

  FIG. 41 shows an outline of the flow of the first defect occurrence prediction flag information 1610 and the second defect occurrence prediction flag information 1620 in the printer 10 shown in FIG. 1 and an outline of how the parameters are changed. Yes. In this example, when it is predicted that a ghost will occur, the gradation parameter changing process is performed by the gradation correcting unit 172, and the transfer parameter changing process is performed by the transfer parameter setting unit 224a. ing. In addition, the other parameters are not changed.

  Incidentally, the first defect occurrence prediction flag information 1610 is input to the image processing unit 170 and is input to the color conversion unit 171, the gradation correction unit 172, and the halftone generation unit 173, respectively.

  The image data analysis process described above will be described with reference to FIG.

  FIG. 42 shows a state of image data analysis processing by the image data analysis unit 160.

  The image data to be analyzed in page units is the same as the image data in the case of the fourth embodiment shown in FIG. 32, and therefore detailed description thereof is omitted here.

  The image data analysis unit 160 scans image data (RGB data) corresponding to one page sequentially in units of pixels from the first line according to the data format of RGB data (P601, step S601 in FIG. 39). reference).

  The image data analysis unit 160 detects an edge in the main scanning direction or the sub-scanning direction for the image data (see P602, step S602 in FIG. 39).

  In this example, for example, (“Xa + 2”, Yb) coordinate values and (“Xa + 14”, Yb) coordinate values are detected as edges.

  The image data analysis unit 160 recognizes that the data value (color gradation value) related to the image on the ghost occurrence side is equal to or less than the preset second color information (color range) G2 (P603, FIG. 39). Step S603 “≦ G2”), and then the contrast of the edge (edge portion) detected in P602 is calculated (P604).

  In this case, the contrast of each edge portion corresponding to each coordinate value of (“Xa + 2”, Yb) and (“Xa + 14”, Yb) coordinate values is calculated as “255-0”, that is, “255”. "

  The image data analysis unit 160 calculates the distance (area) between the two edge portions detected in P602 (see P605, step S606 in FIG. 39).

  In this example, the distance (edge distance) between the edge corresponding to the (“Xa + 2”, Yb) coordinate value and the edge corresponding to the (“Xa + 14”, Yb) coordinate value is calculated.

  If the image data analysis unit 160 determines that the distance (area) between the edges calculated in P605 is equal to or less than the preset distance S1, the image data analysis unit 160 predicts that a white ghost will occur (P606), and then performs analysis processing. The pixel value (gradation value) of the pixel located downstream of the target pixel position in the sub-scanning direction by the drum pitch is scanned (see P607, step S608 in FIG. 39).

  The image data analysis unit 160 sets a flag based on the flag setting information 3500 (FIG. 35) (see P608, step S609 in FIG. 39), and sets a flag value “1” (primary setting) to the defect occurrence prediction flag. (See P609, step S610 in FIG. 39).

  If the image data analysis unit 160 determines that the image data analysis process corresponding to one page has not been completed, the image data analysis unit 160 performs P602 and subsequent steps to perform image analysis processing on the next pixel (next line) ( P610, see step S613 “NO” in FIG. 39).

  For example, when the image data analysis unit 160 detects (Xmax1, Ymax1) coordinate values and determines that the analysis processing of the image data corresponding to one page has ended (see P611, step S613 “YES” in FIG. 39). ), The second defect occurrence prediction flag information 1620 is notified to the image output device controller 210 of the image output device 200 (see P612, step S615 in FIG. 39).

  The image data analysis unit 160 sets, for example, a flag value “1” in the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610 (see P613, step S620 in FIG. 39).

  In the image output device control unit 210, based on, for example, the tone parameter change instruction flag 1622 of the second defect occurrence prediction flag information 1620 from the image processing device 100, the environment information, the paper quality information, and the temporal characteristic information, The flag value of the parameter change instruction flag 1622 is reset (P614). Here, the transfer parameter is reset to a parameter value that means a transfer voltage that is 150 volts lower than the predetermined parameter.

  When the result of the flag replacement process in P613 is the flag value “2”, the image data analysis unit 160 adopts the flag value “2” for the defect occurrence prediction flag, and the first defect occurrence prediction flag information A flag value “2” is set in the halftone dot parameter change instruction flag of 1610 (see P614, step S517 of FIG. 39).

  When the image data analysis unit 160 detects the (Xmax, Ymax) coordinate value and determines that the image data analysis processing corresponding to all pages has been completed (see P615, step S622 “YES” in FIG. 39). ), The image data analysis process is terminated.

  (Embodiment 7)

  Next, a functional configuration of a printer to which the image forming apparatus having the image processing apparatus according to the seventh embodiment is applied will be described.

  FIG. 43 shows the configuration of the printer 10 to which the image forming apparatus having the image processing apparatus according to the seventh embodiment is applied.

  The printer 10 has a configuration in which the drawing unit 140 and the image data analysis unit 160 are changed to a drawing unit 4310 and an image data analysis unit 4320 in the configuration of the printer 10 of the first embodiment shown in FIG. In FIG. 43, parts having the same functions as those shown in FIG.

  In the seventh embodiment, the PDL interpretation unit 130 notifies the image data interpretation unit 4320 of job (JOB) information such as the number of jobs and double-sided setting obtained by PDL interpretation.

  In addition to the function of the drawing unit 140, the drawing unit 4310 receives an instruction to change the drawing direction from the image data analysis unit 4320 and rotates the image data in a predetermined direction according to the indicated drawing direction. In this state, the image data is drawn and the rotated image data is output to the image processing unit 170.

  In addition to the function of the image data analysis unit 160, the image data analysis unit 4320 acquires JOB information from the PDL interpretation unit 13 and paper size information from the image output control unit 210 of the image output apparatus 200, and acquires these. When recognizing that the output direction of the image (image data) is changed based on the information, the drawing unit 4310 is notified (instructed) that the image data should be drawn by rotating the image data by a predetermined angle in a predetermined direction. ) Function.

  The printer 10 of the seventh embodiment has the same configuration and function as the printer 10 of the first embodiment shown in FIGS.

  Furthermore, the printer 10 according to the seventh embodiment performs a printing process similar to the printing process performed by the printer 10 according to the first embodiment illustrated in FIG.

  Next, image data analysis processing by the image data analysis unit 4300 of the image processing apparatus 100 of the printer 10 according to the seventh embodiment will be described with reference to FIG.

  FIG. 44 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 4320 is performed under the following preconditions (1) to (8).

  (1) The drawn image (image data) is scanned in units of one pixel.

  (2) The drawn image (image data) is scanned from the first line. This means that the determination is made after drawing once.

  (3) Analyze in units of jobs (JOB).

  (4) Detect with RGB data.

  (5) In order to detect a white ghost, an edge is detected and the contrast and white distance (area) are counted. In addition, the flag is reset in consideration of the image output device information.

  (6) Change the drawing direction of image data to be output (printed).

  (7) The flag value of the defect occurrence prediction flag information is “0”, “1”, and “3”, and the defect occurrence prediction flag is at three levels.

  (8) Flag setting information 3500 (see Embodiment 5) shown in FIG. 35 that is referenced by the image data analysis unit 160 is stored in a storage unit such as a ROM.

  Now, the PDL interpretation unit 130 interprets the PDL data and outputs job (JOB) information (job number, duplex setting, etc.) obtained by the PDL interpretation to the image data analysis unit 4320.

  As shown in FIG. 44, the image data analysis unit 160 scans image data (RGB data) corresponding to one page sequentially in units of pixels from the first line in accordance with the data format of RGB data ( P701).

  The image data analysis unit 4320 determines whether or not an edge in the main scanning direction or the sub-scanning direction has been detected for the image data related to the scanned line (step S702). If the edge is not detected, the process proceeds to step S701. Returning, if an edge in the main scanning direction or the sub-scanning direction is detected, whether the data value (color gradation value) is equal to or higher than preset first color information (color gradation value) G1. (Whether or not the relational expression “data value ≧ G1” is satisfied), or whether or not it is equal to or less than preset second color information (color gradation value) G2 (≠ G1) (“ Whether or not the relational expression of “data value ≦ G2” is satisfied ”is determined (step S703).

  The image data analysis unit 4320 that has determined that the relational expression “data value ≦ G2” is satisfied in step S703 calculates the contrast of the edge (step S704), and the calculated contrast is equal to or higher than the preset contrast C1. Whether or not the relational expression “calculated contrast ≧ C1” is satisfied (step S705). If the relational expression “calculated contrast ≧ C1” is satisfied as a result of the determination, an edge An inter-distance (area) is calculated (step S706).

  The image data analysis unit 4320 determines whether or not the inter-edge distance (area) calculated in step S706 is equal to or less than a preset distance S1 (whether the relational expression “inter-edge distance (area) ≦ S1” is satisfied). (Step S707), and if the result of this determination is that the relational expression is satisfied, the pixel of the pixel located downstream in the sub-scanning direction by the drum pitch from the position of the pixel that was the object of the analysis processing The value (tone value) is scanned (step S708).

  If it is determined in step S703 that the relational expression “data value ≧ G1” is established, the process proceeds to step S708.

  After completing step S708, the image data analysis unit 4320 sets a flag based on the flag setting information 3500 shown in FIG. 35 (step S709).

  After completing step S709, the image data analysis unit 4320 sets a flag value “1” for the defect occurrence prediction flag (primary setting) or sets a flag value “2” for the defect occurrence prediction flag (primary setting) (step S710). Step S711).

  If the image data analysis unit 4320 determines in step S703 that the relational expressions “data value ≧ G1” and “data value ≦ G2” are not satisfied, “calculated contrast ≧ C1” is satisfied in step S705. If it is determined that the relational expression is not established, the flag value “0” is set in the defect occurrence prediction flag when the relational expression “distance between edges (area) ≦ S1” is not established in step S707 (primary (Step S712).

  When step S710 is finished, step S711 is finished, or step S712 is finished, the image data analysis unit 4320 determines whether the analysis processing of image data corresponding to one page is finished (step S713). ) If the result of this determination is that the analysis process has not ended, the process returns to step S701.

  When the image data analysis unit 4320 finishes the analysis processing of the image data corresponding to one page in step S713, the image data analysis unit 4320 uses the flag value of the defect occurrence prediction flag set in step S710, step S711, or step S712 as the predetermined page. For example, it is set as the flag value of the second first defect occurrence prediction flag for the first page (step S714).

  That is, the image data analysis unit 4320 includes at least one of the charging parameter change instruction flag 1621, the exposure parameter change instruction flag 1622, the development parameter change instruction flag 1623, and the transfer parameter change instruction flag 1624 in the second defect occurrence prediction flag information 1620. A flag value “0”, a flag value “1”, or a flag value “2” is set for one parameter change instruction flag, and a flag value “0” is set for another parameter change instruction.

  The image data analysis unit 4320 obtains paper size information indicating the size of the paper set in the paper feeding device from the image output device control unit 210 of the image output device 200 (step S715), and the second defect occurs. The prediction flag information 1620 is notified to the image output apparatus 200 (step S716).

  When the job data is acquired from the PDL interpretation unit 130 (step S717), the image data analysis unit 4320 outputs the job data based on the job (JOB) information and the paper size information acquired in step S715. It is determined whether or not the output direction related to the power image (image data) can be changed (step S718).

  If the image data analysis unit 4320 determines in step S718 that the output direction related to the image data cannot be changed, the process returns to step S701, while the output direction related to the image data can be changed. If it is determined, in order to change the drawing direction (step S719), the drawing unit 4310 is informed that the image data should be drawn by rotating the image data by a predetermined angle (for example, rotating 180 degrees). At the same time (step S720), the image output device controller 210 of the image output device 200 is notified of the output direction (output direction change flag) related to the image data (step S721).

  When the image data analysis unit 4320 has finished the notification of the drawing direction related to the image data to the drawing unit 4310 and the notification of the output direction related to the image data to the image output device control unit 210, the image data for all pages is displayed. It is determined whether or not the analysis process has been completed (step S722). If the result of this determination is that the image data analysis process for all pages has not been completed, the process returns to step S701. When the image data analysis process is finished, the image data analysis process is finished.

  By the way, in the image output device control unit 210 that has received the second defect occurrence prediction flag information 1620, the flag value, environment information, and paper quality set in each parameter change instruction flag of the second defect occurrence prediction flag information 1620. Based on the information and the temporal characteristic information, the second defect occurrence prediction flag information 1620, that is, the flag value of each parameter change instruction flag is reset.

  The image output device control unit 210 then controls the parameter setting unit subordinate to the parameter storage unit that stores the parameter corresponding to the parameter change instruction flag in which the flag value “1” or the flag value “2” is reset. Request the parameter change process.

  Here, the charging parameter and development parameter changing processing will be described with reference to FIG.

  The parameter reset information 4500 shown in FIG. 45 includes parameter information 4510 that is applied when the second defect occurrence prediction flag information 1620 is notified, and parameter information 4520 that is applied when the output direction change flag is notified. , Including.

  45, the notification flag values “0”, “1”, and “2” are flag values “0”, “1”, and “0” set in the charging parameter change instruction flag 1621 or the development parameter change instruction flag 1623, respectively. 2 ”.

  In the column of charging voltage or developing voltage (charging / developing voltage) Δ (volt), “+100” is a parameter value that means a charging voltage or developing voltage increased by “100 volts” from a predetermined charging voltage or developing voltage. Similarly, “+200” indicates a parameter value indicating a charging voltage or a developing voltage which is increased by “200 volts” from the predetermined transfer voltage.

  Further, the output direction change flag values “0”, “1”, and “2” correspond to parameters related to the output direction related to the image data to be output, and are “no change”, “A4LEF to A4SEF”, respectively. “Change” and “180 ° rotation output”.

  Incidentally, when the flag value “1” is set in the charging parameter change instruction flag 1621 or the development parameter change instruction flag 1623 in the notified second defect occurrence prediction flag information 1620, based on the parameter information 4510, A parameter value indicating a charging voltage or a developing voltage that is increased by Δ100 volts with respect to the charging voltage or the developing voltage set based on the image output device information such as environmental information, paper quality information, and time-dependent characteristic information is reset.

  Further, when the flag value “2” is set in the charging parameter change instruction flag 1621 or the development parameter change instruction flag 1623 in the notified second defect occurrence prediction flag information 1620, based on the parameter information 4520, A parameter value representing a charging voltage or developing voltage that is increased by Δ200 volts from the charging voltage or developing voltage set based on image output device information such as environmental information, paper quality information, and time-dependent characteristic information is reset. In addition, the drawing direction (output direction) is changed (for example, changed to a parameter value indicating 180 degree rotation output).

  When the drawing direction (output direction) is changed, the image output device control unit 210 uses the output direction related to the image data notified from the image data analysis unit 4320 to set parameters related to the paper supply device that stores the paper. Is changed to a parameter value indicating a plurality of paper feeding devices that contain paper in a parameter value corresponding to the paper feeding device that contains paper in a state where an image can be output in the notified output direction.

  In the seventh embodiment, as shown in FIG. 46, when the image processing apparatus 100 recognizes that the output direction of the image (image data) is changed based on the JOB information and the paper size information, the drawing unit 4310 Then, the image data is drawn by being rotated by a predetermined angle in a predetermined direction. Further, the image output apparatus 200 changes the charging parameter and the development parameter based on the second defect occurrence prediction flag information 1620 and the image output apparatus information such as the environment information, the paper quality information, and the time-dependent characteristic information, and further outputs it. The drawing direction (output direction) related to the power image (image data) is changed.

  46 shows the outline of the flow of the first defect occurrence prediction flag information 1610 and the second defect occurrence prediction flag information 1620 and the outline of how the parameters are changed in the printer 10 shown in FIG. Yes. In this example, when it is predicted that a ghost (outlined ghost) will occur, charging parameters and development parameters are changed, and the drawing direction (output direction) related to the image (image data) to be output is further changed. It shows how the change process is performed.

  The image data analysis process described above will be described with reference to FIG.

  FIG. 47 shows the state of image data analysis processing by the image data analysis unit 4320.

  The image data to be analyzed in page units is the same as the image data in the case of the fourth embodiment shown in FIG. 32, and therefore detailed description thereof is omitted here.

  The image data analysis unit 4320 scans image data (RGB data) corresponding to one page in units of pixels sequentially from the first line according to the RGB data format (P701, step S701 in FIG. 44). reference).

  The image data analysis unit 4320 detects an edge in the main scanning direction or the sub-scanning direction for the image data (see P702, step S702 in FIG. 44).

  In this example, for example, (“Xa + 2”, Yb) coordinate values and (“Xa + 14”, Yb) coordinate values are detected as edges.

  The image data analysis unit 4320 recognizes that the data value (color gradation value) related to the image on the ghost occurrence side is equal to or less than the preset second color information (color range) G2 (P703, FIG. 44). Step S703 “≦ G2”), and thereafter, the contrast of the edge (edge portion) detected in P602 is calculated (P704).

  In this case, the contrast of each edge portion corresponding to each coordinate value of (“Xa + 2”, Yb) and (“Xa + 14”, Yb) coordinate values is calculated as “255-0”, that is, “255”. "

  The image data analysis unit 4320 calculates the distance (area) between the two edges detected in P702 (see P705, step S706 in FIG. 44).

  In this example, the distance (edge distance) between the edge corresponding to the (“Xa + 2”, Yb) coordinate value and the edge corresponding to the (“Xa + 14”, Yb) coordinate value is calculated.

  If the image data analysis unit 4320 determines that the inter-edge distance (area) calculated in P705 is equal to or less than the preset distance S1, the image data analysis unit 4320 predicts that an outline ghost will occur (P706), and then performs analysis processing. The pixel value (gradation value) of the pixel located downstream of the target pixel position in the sub-scanning direction by the drum pitch is scanned (see P707, step S608 in FIG. 44).

  The image data analysis unit 4320 sets a flag based on the flag setting information 3500 (FIG. 35) (see P708, step S709 in FIG. 44), and sets (first setting) the flag value “2” to the defect occurrence prediction flag. (See P709, step S711 in FIG. 44).

  If the image data analysis unit 4320 determines that the analysis processing of the image data corresponding to one page has not been completed, the image data analysis unit 4320 performs P702 and subsequent steps to perform image analysis processing on the next pixel (next line) ( P710, see step S713 “NO” in FIG. 44).

  For example, if the image data analysis unit 4320 detects (Xmax1, Ymax1) coordinate values and determines that the analysis processing of the image data corresponding to one page has ended (see P711, “YES” in step S713 in FIG. 44). ), “2” is set as the flag value of the second defect occurrence prediction flag for a predetermined page, for example, the first page.

  The image data analysis unit 4320 obtains paper size information indicating the size of the paper set in the paper feeding device from the image output device control unit 210 of the image output device 200 (P712, step S715 in FIG. 44). The second defect occurrence prediction flag information 1620 in which the flag value “2” is set is notified to the image output apparatus 200 (P713, step S716 in FIG. 44).

  Here, in the second defect occurrence prediction flag information 1620, it is assumed that a flag value “2” is set in the charging parameter change instruction flag 1621 and the development parameter change instruction flag 1623.

  Can the image data analysis unit 4320 change the output direction of an image (image data) to be output based on job (JOB) information from the PDL interpretation unit 130 or paper size information from the image output device control unit 210? If it is determined that it is possible to change the output direction related to the image data (see P714, “YES” in step S718 of FIG. 44), the drawing direction should be changed. (See P715, step S719 in FIG. 44), the drawing unit 4310 is notified that the image data should be drawn by being rotated in a predetermined direction by a predetermined angle (for example, rotated 180 degrees), and the image output apparatus The image output device control unit 210 of 200 is notified of the output direction (output direction change flag) related to the image data (P716, FIG. 44). Step S721).

  In the image output apparatus 200, the charging parameter change instruction flag 1621 and the development parameter change instruction flag 1623 in which the flag value “2” in the notified second defect occurrence prediction flag information 1620 is set, and parameter resetting information are set. Based on 4500, parameter values representing charging voltage and developing voltage increased by 200 volts from the predetermined charging voltage and predetermined developing voltage are adopted.

  Finally, when the image data analysis unit 4320 detects the (Xmax, Ymax) coordinate value and determines that the analysis processing of the image data corresponding to all pages has been completed (P717, step S722 “of FIG. 44). This image data analysis process is terminated.

  (Embodiment 8)

  Next, a functional configuration of a printer to which the image forming apparatus having the image processing apparatus according to the eighth embodiment is applied will be described.

  The printer of the eighth embodiment has the same configuration and function as the printer 10 of the seventh embodiment shown in FIG. 43 and the printer 10 of the first embodiment shown in FIGS. Further, the printer 10 according to the eighth embodiment performs a printing process similar to the printing process performed by the printer 10 according to the first embodiment illustrated in FIG.

  Next, image data analysis processing by the image data analysis unit 4320 of the image processing apparatus 100 of the printer 10 according to the eighth embodiment will be described with reference to FIG.

  FIG. 48 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 4320 is performed under the following preconditions (1) to (10).

  (1) All drawn images (image data) are scanned in units of objects.

  (2) The drawn image (image data) is scanned from the first line. This means that the determination is made after drawing once.

  (3) Analyze in units of jobs (JOB).

  (4) Detect with RGB data.

  (5) In order to detect a white ghost, an edge is detected and the contrast and white distance (area) are counted. In addition, the flag is reset in consideration of the image output device information.

  (6) Detect upstream and downstream of drum pitch.

  (7) A flag is set in consideration of other defect information.

  (8) The drawing direction of the image data to be output (printed) is changed.

  (9) The flag value of the defect occurrence prediction flag information is “0”, “1”, and “3”, and the defect occurrence prediction flag is at three levels. In this case, the flag level is divided according to the average value (for example, average density) of the object.

  (10) Flag setting information 3500 (see Embodiment 5) shown in FIG. 35 that is referenced by the image data analysis unit 160 is stored in a storage unit such as a ROM.

  Now, the PDL interpretation unit 130 interprets the PDL data and outputs job (JOB) information (job number, duplex setting, etc.) obtained by the PDL interpretation to the image data analysis unit 4320.

  As shown in FIG. 48, the image data analysis unit 4320 scans image data (RGB data) corresponding to one page sequentially in units of pixels from the first line according to the data format of the RGB data ( Step S801).

  The image data analysis unit 4320 determines whether a graphic (graphic object) or an image (image object) is included in the image data (step S802). As a result of the determination, the graphic object or image object is determined. If included, the average value (for example, average density) of the object is calculated (step S803).

  The image data analysis unit 4320 determines whether or not the average value of the object calculated in step S803 is equal to or higher than the first color information (color gradation value) P1 set in advance (relationship “average value ≧ P1”). Whether or not the expression is satisfied), whether or not it is equal to or less than the preset second color information (color gradation value) P2 (≠ P1) (whether the relational expression of “average value ≦ P2” is satisfied) (No) is determined (step S804).

  The image data analysis unit 4320 that has determined that the relational expression “average value ≦ P2” is established in step S804 calculates the contrast of the edge (step S805), and the calculated contrast is equal to or higher than the preset contrast C1. (Whether or not the relational expression of calculated contrast ≧ C1 is satisfied) (step S806). As a result of this determination, if the relational expression of “calculated contrast ≧ C1” is satisfied, an edge is determined. An inter-distance (area) is calculated (step S807).

  The image data analysis unit 4320 determines whether or not the inter-edge distance (area) calculated in step S807 is equal to or less than the preset distance S1 (whether the relational expression “inter-edge distance (area) ≦ S1” is satisfied). (Step S808), and if the above relational expression is satisfied as a result of the determination, the pixel of the pixel located downstream in the sub-scanning direction by the drum pitch from the position of the pixel that was the object of the analysis processing The value (tone value) is scanned (step S809).

  If it is determined in step S804 that the relational expression “average value ≧ P1” is satisfied, the process proceeds to step S809.

  The image data analysis unit 4320 that has determined that the relational expression “P1 <average value <P2” is established in step S804 is a pixel located upstream in the sub-scanning direction by the drum pitch from the position of the pixel that was the object of analysis processing. The pixel value (gradation value) is scanned (step S810).

  The image data analysis unit 4320 acquires other defect information (step S811), the acquired other defect information, the result of scanning in step S809, or the result of scanning in step S810, and are shown in FIG. The defect occurrence prediction flag is set based on the flag setting information 3500 (step S812).

  After completing step S812, the image data analysis unit 4320 sets a flag value “1” to the defect occurrence prediction flag (primary setting) or sets a flag value “2” to the defect occurrence prediction flag (primary setting) (step S813). Step S814).

  If the image data analysis unit 4320 determines that only the text object is present in step S802, the image data analysis unit 4320 determines that any of the relational expressions “average value ≧ P1” and “average value ≦ P2” is not satisfied in step S804. In step S806, if it is determined that the relational expression “calculated contrast ≧ C1” is not established, it is determined in step S808 that the relational expression “distance (area) between edges ≦ S1” is not established. A flag value “0” is set (primary setting) in the occurrence prediction flag (step S815).

  When step S813 is finished, step S814 is finished, step S815 is finished, the image data analysis unit 4320 determines whether the analysis processing of image data corresponding to one page is finished (step S816). ) If the result of this determination is that the analysis process has not ended, the process returns to step S801.

  When the image data analysis unit 4320 finishes the analysis processing of the image data corresponding to one page in step S816, the image data analysis unit 4320 uses the flag value of the defect occurrence prediction flag set in step S813, step S814, or step S815 as the predetermined page. For example, it is set as the flag value of the second defect occurrence prediction flag for the first page (step S817).

  That is, the image data analysis unit 4320 includes at least one of the charging parameter change instruction flag 1621, the exposure parameter change instruction flag 1622, the development parameter change instruction flag 1623, and the transfer parameter change instruction flag 1624 in the second defect occurrence prediction flag information 1620. A flag value “0”, a flag value “1”, or a flag value “2” is set for one parameter change instruction flag, and a flag value “0” is set for another parameter change instruction.

  The image data analysis unit 4320 obtains paper size information indicating the size related to the paper set in the paper feeding device from the image output device control unit 210 of the image output device 200 (step S818), and the second defect occurs. The prediction flag information 1620 is notified to the image output apparatus 200 (step S819).

  When acquiring the job (JOB) information from the PDL interpretation unit 130 (step S820), the image data analysis unit 4320 outputs the job data based on the job (JOB) information and the paper size information acquired in step S818. It is determined whether or not the output direction related to the power image (image data) can be changed (step S821).

  If the image data analysis unit 4320 determines in step S821 that the output direction related to the image data cannot be changed, the process returns to step S801, while the output direction related to the image data can be changed. If it is determined, in order to change the drawing direction (step S822), the drawing unit 4310 indicates that the image data should be drawn by rotating the image data in a predetermined direction by a predetermined angle (for example, rotating 180 degrees). At the same time (step S823), the image output device controller 210 of the image output device 200 is notified of the output direction (output direction change flag) related to the image data (step S824).

  When the image data analysis unit 4320 has finished the notification of the drawing direction related to the image data to the drawing unit 4310 and the notification of the output direction related to the image data to the image output device control unit 210, the image data for all pages is displayed. It is determined whether or not the analysis process has been completed (step S825). As a result of the determination, if the image data analysis process for all pages has not been completed, the process returns to step S701. When the image data analysis process is finished, the image data analysis process is finished.

  By the way, in the image output device control unit 210 that has received the second defect occurrence prediction flag information 1620, the flag value, environment information, and paper quality set in each parameter change instruction flag of the second defect occurrence prediction flag information 1620. Based on the information and the temporal characteristic information, the second defect occurrence prediction flag information 1620, that is, the flag value of each parameter change instruction flag is reset.

  The image output device control unit 210 then controls the parameter setting unit subordinate to the parameter storage unit that stores the parameter corresponding to the parameter change instruction flag in which the flag value “1” or the flag value “2” is reset. Request the parameter change process.

  Also in the eighth embodiment, the charging parameter and development parameter changing processing can be performed in the same manner as in the seventh embodiment. That is, in the image output apparatus 200, the charging parameter and the development parameter are based on the flag value set in the charging parameter change instruction flag 1621 or the development parameter change instruction flag 1623 and the parameter reset information 4500 shown in FIG. Reset the parameter value of.

  Also in the eighth embodiment, as in the example of the seventh embodiment shown in FIG. 46, when it is predicted that a ghost (white ghost) will occur, the charging parameter and development parameter changing processing is performed. Further, a drawing direction (output direction) change process relating to an image (image data) to be output is performed.

  The image data analysis process described above will be described with reference to FIG.

  FIG. 49 shows the state of image data analysis processing by the image data analysis unit 4320.

  The image data to be analyzed in page units is the same as the image data in the case of the fourth embodiment shown in FIG. 32, and therefore detailed description thereof is omitted here.

  The image data analysis unit 4320 scans image data (RGB data) corresponding to one page sequentially in units of pixels from the first line in accordance with the data format of the RGB data (P801).

  The image data analysis unit 4320 detects a graphic (graphic object) or an image (image object) (P802), and calculates an average value (for example, average density) of the object (P803).

  The image data analysis unit 4320 determines whether the calculated average value is equal to or lower than a preset density P1 (whether the relational expression “average value ≦ P1” is satisfied) or a preset density P2 (≠ P1). Whether the relational expression of “average value ≧ P2” is satisfied, or whether it exceeds P1 and less than P2 (whether the relational expression of “P1 <average value <P2” is satisfied). As a result of the determination, it is recognized that the relational expression “P1 <average value <P2” is satisfied in this case (P804).

    The image data analysis unit 4320 scans the pixel value (gradation value) of the pixel located upstream in the sub-scanning direction by the drum pitch from the position of the pixel to be analyzed (P805).

  The image data analysis unit 4320 sets a flag based on the other defect information and the flag setting information 3500 shown in FIG. 35 (P806), and sets the flag value “2” in the second defect occurrence prediction flag information 1620. Set (primary setting) (P807).

  For example, when the image data analysis unit 4320 detects (Xmax1, Ymax1) coordinate values and determines that the analysis processing of the image data corresponding to one page has ended (P808), the image output device of the image output device 200 The paper size information is acquired from the control unit 210 (P809), and the second defect occurrence prediction flag information 1620 is notified to the image output apparatus 200 (P810).

  Based on the job (JOB) information and the paper size information, the image data analysis unit 4320 determines whether it is possible to change the output direction for the image (image data) to be output (P811).

  If it is determined that the output direction can be changed, the image data is rotated by a predetermined angle in a predetermined direction (for example, 180 degrees) with respect to the drawing unit 4310 in order to change the drawing direction. The image output device control unit 210 of the image output device 200 is notified of the output direction (output direction change flag) related to the image data.

  Finally, when the image data analysis unit 4320 detects the (Xmax, Ymax) coordinate value and determines that the analysis processing of the image data corresponding to all pages has been completed (P812), this image data analysis processing Exit.

  (Embodiment 9)

  Next, a functional configuration of a printer to which the image forming apparatus having the image processing apparatus according to the ninth embodiment is applied will be described.

  The printer of the ninth embodiment has the same configuration and function as the printer 10 of the seventh embodiment shown in FIG. 43 and the printer 10 of the first embodiment shown in FIGS. Further, the printer 10 according to the eighth embodiment performs a printing process similar to the printing process performed by the printer 10 according to the first embodiment illustrated in FIG.

  Next, image data analysis processing by the image data analysis unit 4320 of the image processing apparatus 100 of the printer 10 according to the ninth embodiment will be described with reference to FIG.

  FIG. 50 is a flowchart showing the processing procedure of the image data analysis processing.

  In this example, image data analysis processing by the image data analysis unit 160 is performed under the following preconditions (1) to (10).

  (1) All drawn images (image data) are scanned in units of objects.

  (2) Detection is performed for each object at the stage of intermediate data before rasterization (the determination process is simplified).

  (3) Detect the ghost receiving object.

  (4) When there is a possibility of ghosting, the upstream of the drum pitch (the upstream of the drum pitch in the sub-scanning direction) is detected.

  (5) If an object exists upstream and the image on the ghost generation side also meets a predetermined condition, a predetermined correction is performed.

  (6) Analyze in units of jobs (JOB).

  (7) Detect with RGB data.

  (8) A flag is set in consideration of other defect information.

  (9) The flag value of the defect occurrence prediction flag information is “0”, “1”, and “3”, and the defect occurrence prediction flag is at three levels. In this case, the flag level is divided according to the average value (for example, average density) of the object.

  (10) Flag setting information 3500 (see Embodiment 5) shown in FIG. 35 that is referenced by the image data analysis unit 160 is stored in a storage unit such as a ROM.

  As shown in FIG. 50, the image data analysis unit 4320 scans all image data (RGB data) in an intermediate data format corresponding to one page in units of objects according to the data format of RGB data (step S901).

  The image data analysis unit 4320 determines whether a graphic (graphic object) or an image (image object) is included in the image data (step S902). As a result of the determination, the graphic object or image object is determined. If it is included, the color information R of the object is detected (step S903).

  The image data analysis unit 4320 determines whether or not the detected color information R is not less than the preset color information P1 and not more than the preset color information P2 (≠ P1) (“P1 ≦ R ≦ P2”). It is determined whether or not a relational expression is established (step 904).

  If the image data analysis unit 4320 determines in step S904 that the relational expression “P1 ≦ R ≦ P2” is satisfied, the image data analysis unit 4320 scans an image positioned upstream in the sub-scanning direction by the drum pitch (step 905).

  The image data analysis unit 4320 determines whether a graphic (graphic object) or an image (image object) is included in the image (image data) scanned in step S905 (step 906). As a result, when a graphic object or an image object is included, the color information G of the object is detected (step 907).

  After completing step S907, the image data analysis unit 4320 determines whether the color information G is greater than or equal to the color information P1 (whether the relational expression “P1 ≦ G” is satisfied), or the color information G is the color information P2. It is determined whether or not (whether the relational expression “P2 ≧ G” is satisfied) (step S908).

  The image data analysis unit 4320 acquires other defect information (step S909), and sets a defect occurrence prediction flag based on the acquired other defect information and the flag setting information 3500 shown in FIG. Step S910).

  Here, the other defect information is, for example, transfer failure (motor). The image data analysis unit 4320 can predict the occurrence of the transfer failure (motor) as in the case of the ghost occurrence prediction based on another determination formula. Then, the image data analysis unit 4320 sets a defect occurrence prediction flag in consideration of defect information of defective transfer in addition to the flag setting information 3500.

  After completing step S910, the image data analysis unit 4320 sets a flag value “1” for the defect occurrence prediction flag (primary setting) or sets a flag value “2” for the defect occurrence prediction flag (primary setting) (step S911). Step S912).

  If the image data analysis unit 4320 determines that only the text object is found in step S902, or if it is determined that the relational expression “P1 ≦ R ≦ P2” is not established in step S904, the image data analysis unit 4320 If no image object exists, the flag value “0” is set in the defect occurrence prediction flag when it is determined in step S908 that neither the relational expression “P1 ≦ G” nor the relational expression “P2 ≧ G” is satisfied. (Primary setting) is performed (step S913).

  When step S911 is finished, step S912 is finished, or step S913 is finished, the image data analysis unit 4320 determines whether the analysis processing of image data corresponding to one page is finished (step S914). ) If the result of this determination is that the analysis process has not ended, the process returns to step S901.

  When the image data analysis unit 4320 finishes the analysis processing of image data corresponding to one page in step S914, the flag value of the defect occurrence prediction flag set in step S911, step S912, or step S913 is set to a predetermined page. For example, the first defect occurrence prediction flag and the second defect occurrence prediction flag for the first page are set as flag values (step S915).

  That is, the image data analysis unit 4320 includes at least one of the charging parameter change instruction flag 1621, the exposure parameter change instruction flag 1622, the development parameter change instruction flag 1623, and the transfer parameter change instruction flag 1624 in the second defect occurrence prediction flag information 1620. A flag value “0”, a flag value “1”, or a flag value “2” is set for one parameter change instruction flag, and a flag value “0” is set for another parameter change instruction.

  The image data analysis unit 4320 notifies the image output device control unit 210 of the image output device 200 of the second defect occurrence prediction flag information 1620 in which the flag value is set in this way.

  The image data analysis unit 4320 adopts the flag value “0”, the flag value “1”, or the flag value “2” for the first defect occurrence prediction flag (step S916, step S917, step S918). .

  If the image data analysis unit 160 adopts the flag value “0” for the defect occurrence prediction flag in step S916, the image data analysis unit 160 sets the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “0” is set (step S619). The flag value “0” is also set for the other parameter change instruction flags.

  If the image data analysis unit 4320 adopts the flag value “1” for the defect occurrence prediction flag in step S917, the image data analysis unit 4320 displays the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “1” is set (step S920). The flag value “0” is set for the other parameter change instruction flags.

  If the image data analysis unit 4320 adopts the flag value “2” for the defect occurrence prediction flag in step S918, the image data analysis unit 4320 displays the gradation parameter change instruction flag 1612 in the first defect occurrence prediction flag information 1610. A flag value “2” is set (step S921). The flag value “0” is set for the other parameter change instruction flags.

  The image data analysis unit 4320 outputs the final first defect occurrence prediction flag information 1610 to the image processing unit 170 when step S919 is completed, step S920 is completed, or step S921 is completed. At the same time, it is determined whether or not the image data analysis processing for all pages has been completed (step S922).

  If the image data analysis unit 4320 determines in step S922 that the image data analysis process for all pages has not been completed, the process returns to step S901, and the image data analysis process for all pages is terminated. If it is determined that the image data has been analyzed, the image data analysis process is terminated.

  Also in the ninth embodiment, the charging parameter and development parameter changing process can be performed in the same manner as in the seventh embodiment. That is, in the image output apparatus 200, the charging parameter and the development parameter are based on the flag value set in the charging parameter change instruction flag 1621 or the development parameter change instruction flag 1623 and the parameter reset information 4500 shown in FIG. Reset the parameter value of.

  Also in the ninth embodiment, when it is predicted that a ghost (white ghost) will occur as in the example of the seventh embodiment shown in FIG. 46, the charging parameter and development parameter changing processing is performed. Further, a drawing direction (output direction) change process relating to an image (image data) to be output is performed.

  The image data analysis process described above will be described with reference to FIG.

  FIG. 51 shows the state of image data analysis processing by the image data analysis unit 4320.

  In the ninth embodiment, an image data analysis process is assumed for image data in which a ghost as shown in FIG. 52 may occur.

  The image data to be analyzed in page units is the same as the image data in the case of the fourth embodiment shown in FIG. 32, and therefore detailed description thereof is omitted here.

  The image data analysis unit 4320 scans all image data (RGB data) corresponding to one page in units of objects (P901).

  The image data analysis unit 4320 recognizes that there is a graphic (graphic object) or an image (image object) in the image data (P902), and the recognized object may be a ghost receiver. (P903).

  The image data analysis unit 4320 scans an image located upstream in the sub-scanning direction by the drum pitch (P904).

  The image data analysis unit 4320 recognizes that there is a graphic (graphic object) or an image (image object) in the image (image data) at the upstream position (P905), and for the recognized object, the ghost generation side It is determined that the object is likely to become (P906).

  The image data analysis unit 4320 sets a defect occurrence prediction flag based on the flag setting information 3500 shown in FIG. 35 (P907).

  (Embodiment 10)

  FIG. 53 shows the configuration of an image forming system according to the tenth embodiment.

  As shown in FIG. 53, in the image forming system 1, a printer 10 as an image forming apparatus and a computer 20 as a processing apparatus (client apparatus) are connected via a communication line 30.

The computer 20 functions as a processing device and has a CPU (Central
Processing Unit: Central processing unit 21, storage device 22 such as hard disk, RAM (Random
And a communication interface (hereinafter referred to as “communication I / F”) 24, such as an Access Memory (anytime read / write memory).

  The storage device 22 stores various types of data such as application software for issuing documents and printing requests, printer drivers, and print data (PDL data).

  The memory 23 stores programs and data read from the storage device 22.

  The communication I / F 24 is an interface that transmits and receives data to and from the printer 10 via the communication line 30.

  The CPU 21 controls the entire computer 20. For example, the CPU 21 reads a printer driver from the storage device 22 into the memory 23 and executes it. As a result, print data (PDL data) is transmitted to the printer 10.

  A printer 10 that functions as an image forming apparatus includes a CPU 11, a storage device 12 such as a hard disk, a memory 13 such as a RAM, and an image output device 200 having a communication I / F 14. This printer 10 corresponds to the printer of any one of the first to ninth embodiments.

  The storage device 12 stores various programs and data necessary for performing the printing process, such as the above-described image processing program (predetermined program) 50 that is software.

  The communication I / F 14 is an interface that transmits and receives data to and from the computer 20 via the communication line 30. For example, the communication I / F 14 receives print data transmitted from the computer 20.

  Incidentally, the image processing program 50 includes a PDL interpretation unit 130, a drawing unit 140 (drawing unit 4310), an image data analysis unit 160 (image data analysis unit 4310), and an image processing unit 170 (color conversion unit 171 and tone correction unit). 172 and halftone dot generation unit 173) programs (software) for realizing the respective functions, and the processing procedure of the image data analysis processing described in any one of the first to ninth embodiments The program (software) corresponding to is included.

  The memory 13 stores the image processing program 50 read from the storage device 12, print data received via the communication I / F 14, and the like. In addition, at least the following storage areas (a) to (e) are allocated to the memory 13.

  (A) A storage area that functions as the storage unit 120 (an area for storing print data).

  (B) A storage area that functions as the storage unit 150 (an area for storing drawing data).

  (C) A storage area that functions as a color parameter storage unit 171b, a gradation parameter storage unit 172b, and a halftone parameter storage unit 173b (an area for storing each parameter).

  (D) A storage area required when the image data analysis unit 160 performs a prediction process of occurrence of a ghost (white ghost) (a work area required for a prediction process, information on a prediction process, and information on a result thereof) Storage area to store etc.).

  (E) A storage area required when the image processing unit 170 performs image processing (such as a storage area for storing color conversion processing, gradation correction processing, screen processing steps, processing results, and the like).

  The CPU 11 controls the entire printer 10. For example, the CPU 11 reads the image processing program 50 from the storage device 12 into the memory 13 and executes it, thereby generating high-quality image data and directing it to the image output device 200. Output.

As the communication line 30, a local area network (LAN: Local
(Area Network), a wired communication line such as a telephone line, a wireless communication line such as a wireless LAN, and a combination of these communication lines.

  For example, a ghost as shown in FIG. 54 occurs in the printer (image forming apparatus) 10 according to any one of the first to ninth embodiments described above or the image forming system 1 according to the tenth embodiment. When performing the printing process on such image data or image data on which a ghost as shown in FIG. 55 occurs, the image processing apparatus 100 performs image data analysis processing on the image data, and the image processing unit 170 A parameter changing process related to the image processing or a parameter changing process related to the image forming process by the image output apparatus 200 is performed to suppress the occurrence of the ghost described above (the image shown in FIG. 2 or the image shown in FIG. 3 is printed out) )

  In the present specification, the information processing apparatus includes a CPU, a memory, and a storage device like a printer, in other words, an image processing apparatus (see FIG. 20).

  In the specification of the present application, each function of the image processing device is realized, and a predetermined program including a program indicating the processing procedure of the image processing is recorded in a storage device such as a hard disk as a recording medium. It is also possible to provide the predetermined program as follows.

  That is, the predetermined program may be stored in the ROM, and the CPU may load the program from the ROM to the main storage device and execute it.

  The predetermined program may be stored and distributed in a computer-readable recording medium such as a DVD-ROM, CD-ROM, MO (magneto-optical disk), flexible disk, or the like. In this case, after the image processing apparatus installs the program recorded on the recording medium, the CPU executes the program. As an installation destination of this program, there is a memory such as a RAM or a storage device such as a hard disk. The image processing apparatus loads the program stored in the storage device into the main storage device and executes it as necessary.

  Further, the image processing apparatus is connected to a computer such as a server apparatus or a host computer via a communication line (for example, the Internet), and after the image processing apparatus downloads the predetermined program from the server apparatus or the computer, This program may be executed. In this case, the download destination of the program includes a memory such as a RAM and a storage device (recording medium) such as a hard disk. Then, the image processing apparatus loads the program stored in the storage device into the main storage device and executes it as necessary.

  The present invention relates to image data for printing with respect to an image forming apparatus such as a printing apparatus that prints at least one of a monochrome image and a color image, or an image forming apparatus having a plurality of image forming processing functions including at least a printing function. And an image forming apparatus having the image processing apparatus, and an image forming system having the image forming apparatus.

1 is a block diagram illustrating a functional configuration of a printer to which an image forming apparatus having an image processing apparatus according to a first embodiment is applied. 6 is a diagram illustrating an example of image data that is an object of image data analysis processing by the image processing apparatus according to Embodiment 1. FIG. 6 is a diagram illustrating an example of image data that is an object of image data analysis processing by the image processing apparatus according to Embodiment 1. FIG. 6 is a diagram illustrating an example of image data that is an object of image data analysis processing by the image processing apparatus according to Embodiment 1. FIG. 6 is a diagram illustrating an example of image data that is an object of image data analysis processing by the image processing apparatus according to Embodiment 1. FIG. It is a figure which shows an example of the format of the 1st defect generation | occurrence | production prediction flag information which concerns on Embodiment 1. FIG. It is a figure which shows an example of the format of the 1st defect generation | occurrence | production prediction flag information which concerns on Embodiment 1. FIG. 3 is a block diagram illustrating detailed functional configurations of an image processing unit and a parameter setting unit according to Embodiment 1. FIG. 2 is a configuration diagram illustrating a configuration of an image forming unit according to Embodiment 1. FIG. 4 is a flowchart illustrating a processing procedure of print processing of a printer to which the image forming apparatus according to the first embodiment is applied. 5 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to the first embodiment. 6 is a diagram illustrating an example of color allowable range information according to Embodiment 1. FIG. It is a figure which shows an example of the primary setting flag information which concerns on Embodiment 1. FIG. It is a figure which shows an example of the last setting flag information which concerns on Embodiment 1. FIG. It is a figure which shows the outline | summary of a flow of the defect generation | occurrence | production prediction flag information which concerns on Embodiment 1, and a mode that a parameter is changed. 6 is a diagram for explaining image data to be subjected to image data analysis processing according to the first embodiment. FIG. 6 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to Embodiment 1. FIG. 10 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to the second embodiment. It is a figure which shows an example of the flag setting information which concerns on Embodiment 2. It is a figure which shows an example of the last setting flag information which concerns on Embodiment 2. FIG. It is a figure which shows an example of the flag parameter corresponding | compatible information which concerns on Embodiment 2. FIG. It is a figure which shows the outline | summary of a flow of the defect generation | occurrence | production prediction flag information which concerns on Embodiment 2, and a mode that a parameter is changed. FIG. 10 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to the second embodiment. 10 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to Embodiment 3. FIG. 10 is a diagram for explaining image data to be subjected to image data analysis processing according to the third embodiment. FIG. 10 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to a third embodiment. 15 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to the fourth embodiment. It is a figure which shows an example of the flag setting information which concerns on Embodiment 4. It is a figure which shows an example of the gradation correction information which concerns on Embodiment 4. FIG. It is a figure which shows an example of the gradation correction information which concerns on Embodiment 4. FIG. It is a figure which shows the outline | summary of a flow of the defect generation | occurrence | production prediction flag information which concerns on Embodiment 4, and a mode that a parameter is changed. FIG. 10 is a diagram for explaining image data to be subjected to image data analysis processing according to a fourth embodiment. FIG. 10 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to a fourth embodiment. 10 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to a fifth embodiment. It is a figure which shows an example of the flag setting information which concerns on Embodiment 5. FIG. It is a figure which shows an example of the flag replacement information which concerns on Embodiment 5. It is a figure which shows the outline | summary of a flow change of a defect generation | occurrence | production prediction flag information which concerns on Embodiment 5, and a mode that a parameter is changed. FIG. 10 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to a fifth embodiment. 20 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to the sixth embodiment. It is a figure which shows an example of the flag parameter corresponding | compatible information which concerns on Embodiment 6. FIG. It is a figure which shows the outline | summary of a flow outline of a defect generation | occurrence | production prediction flag information which concerns on Embodiment 6, and a mode that a parameter is changed. FIG. 20 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to a sixth embodiment. FIG. 20 is a block diagram illustrating a functional configuration of a printer to which an image forming apparatus having an image processing apparatus according to a seventh embodiment is applied. 20 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to Embodiment 7. FIG. 20 is a diagram illustrating an example of parameter resetting information according to the seventh embodiment. It is a figure which shows the outline | summary of a flow of the defect generation | occurrence | production prediction flag information which concerns on Embodiment 7, and a mode that a parameter is changed. FIG. 20 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to a seventh embodiment. 20 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to Embodiment 8. FIG. 20 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to Embodiment 8. 30 is a flowchart illustrating a processing procedure of image data analysis processing of an image data analysis unit according to the ninth embodiment. FIG. 20 is a diagram illustrating a state of image data analysis processing by an image data analysis unit according to a ninth embodiment. FIG. 20 is a diagram illustrating an example of image data to be subjected to image data analysis processing by an image data analysis unit according to a ninth embodiment. FIG. 16 is a configuration diagram illustrating a configuration of an image forming system according to a tenth embodiment. It is a figure which shows an example of the image data which a ghost generate | occur | produces. It is a figure which shows the other example of the image data which a ghost generate | occur | produces.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image forming system 10 Image forming apparatus (printer)
20 Computer (Processor)
30 communication line 50 image processing program 100 image processing apparatus 110 data receiving unit 120, 150 storage unit 130 PDL interpretation unit 140, 4310 drawing unit 160, 4320 image data analysis unit 170 image processing unit 171 color conversion unit 172 gradation correction unit 173 Halftone generation unit 200 Image output device 210 Image output device control unit 220 Parameter setting unit 230 Image forming unit 1610 First defect occurrence prediction flag information 1620 Second defect occurrence prediction flag information

Claims (10)

For predetermined image data including the first image and the second image located downstream in the sub-scanning direction from the first image, the color density information of the first image and the second image Predicting means for predicting that an image defect event will occur due to the fact that at least a part of the image corresponding to the first image is included in the second image, based on color density information ,
When the predicting means predicts that the image defect event will occur, a determining means for determining element information to be updated from among a plurality of element information related to image quality;
Updating means for updating the element content of the element information determined by the determining means to a predetermined element content;
An image processing apparatus comprising: The prediction means includes
The first image and the first image located at a distance corresponding to a length that is a positive integer multiple of the circumference in the rotation direction of the image carrier on which the electrostatic latent image corresponding to the predetermined image data is formed. The position information indicating the position in the main scanning direction related to at least a part of the first image includes the position in the main scanning direction related to the second image. Predicting the occurrence of the image defect event based on the density information of the colors of the two images when included in the position information shown;
The image processing apparatus according to claim 1. The prediction means includes
The image defect event occurs when the color density information of the first image is included in a first allowable range and the color density information of the second image is included in a second allowable range. Predict,
The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus. The prediction means includes
Predicting that the image defect event occurs when the area of the first image region or the area of the second image region is equal to or greater than a predetermined threshold;
The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus. The prediction means includes
Predicting that the image defect event occurs when the difference between the contrast of the first image and the contrast of the second image is equal to or greater than a predetermined value ;
The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus. The prediction means includes
Information about the environment of at least one of the periphery and the inside of the image forming unit that performs the image forming process, information about the quality of the paper on which the result of the image forming process by the image forming unit is printed, and the temporal characteristics of the image forming unit Predicting that the image defect event will occur based on at least one piece of information, information about the first image, and information about the second image,
The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus. The update target element information is at least one of element information related to image processing and element information related to image formation processing.
The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus. An image forming apparatus comprising: the image processing apparatus according to claim 1, wherein an image forming process is performed on output data output from the image processing apparatus. 9. The image forming apparatus according to claim 8 and a processing apparatus that outputs predetermined image data to the image forming apparatus are connected via a communication line, and the image forming apparatus performs image forming processing on the acquired predetermined image data. An image forming system comprising: For predetermined image data including the first image and the second image located downstream in the sub-scanning direction from the first image, the color density information of the first image and the second image A prediction process for predicting that an image defect event will occur due to the fact that at least a part of the image corresponding to the first image is included in the second image based on color density information When,
When it is predicted that the image defect event will occur by the prediction process, a determination process for determining element information to be updated from a plurality of element information related to image quality;
An update process for updating the element content of the element information determined by the determination process to a predetermined element content;
An image processing program for causing a computer to execute.