JP5841978B2 - Image processing apparatus and image processing method - Google Patents

Description

  Embodiments described herein relate generally to an image processing apparatus and an image processing method for correcting image output characteristics in accordance with characteristics of a recording medium.

  In a general office environment, character images are mainly used, and there are not many variations of printing paper used in devices such as a copier, a printer, and an MFP (Multifunction Peripheral). Therefore, for normal use, the default image correction for the device is sufficient. The image correction table is selected for a specific printing job that occurs rarely, but the user selects the paper type on the printer driver screen displayed on the device control panel or PC (Personal Computer) monitor. Can be obtained as a result of image correction using an image correction table corresponding to the above.

  In light printing places such as catalog printing, a dedicated operator executes image correction according to printing paper in order to perform print output by strictly managing the quality difference of each printing paper. That is, the operator prints the reference chart once on the printing paper, and directly calculates the image correction amount by measuring the reference chart, or estimates and determines the optimum image correction amount through trial and error. Is done. Then, image correction is performed using the calculated image correction table, and hundreds to thousands of copies are printed at a time. As described above, in a general office environment or a light printing environment by a full-time operator, it is relatively easy to select an optimum image output characteristic for printing paper.

  However, when printing flyers, postcards, etc. at retail stores, etc., there are a wide variety of papers to be printed. Furthermore, since the number of copies to be printed is a small number of 1 to several hundred copies, there may be no dedicated operator. As described above, the correction for various types of printing paper is performed by printing the reference chart once on the printing paper and calculating the image correction amount by measuring the color of the reference chart pattern or estimating the image correction amount. The decision is made after mistakes. If there is no dedicated operator, it would be very complicated for a general user to create an image correction table for each paper type. Furthermore, since a high-performance printer having a colorimetric function is relatively expensive, there is a problem that many printers do not have this function.

JP 2009-71617 A

  The problem to be solved by the present invention is to provide an image processing apparatus and an image processing method capable of solving the above-described problems and capable of performing high-quality printing on a wide variety of recording media without the user being aware of it. .

To achieve the above object, an image processing apparatus according to the embodiment extracts a second medium, wherein the amount of the image data of a specific area in the first medium features and the fiber properties according to the color information of the recording medium, respectively A gamma correction value for image correction of the original image data to be printed is calculated for each input value indicating the color gradation of the pixel from the image data of the density feature printed on the recording medium and the medium feature amount extraction unit. A correction table creating unit that creates a correction table in which a gamma correction value related to the recording medium is associated with the first medium feature quantity or the second medium feature quantity in accordance with a range of the input value; and the correction table the use and correction table storage unit for storing a logical expression or the second medium feature based on the first media feature quantity relating to said recording medium to be printed in the database, the data A correction table search unit to search for a candidate of the correction table for the recording medium from the base, from the candidates of the correction table, the correction table to be applied to the image correction at the time of printing of the original image data on the recording medium A correction table selection unit that selects the image data, and an image correction unit that performs image correction of the document image data using the gamma correction value of the selected correction table.

In the image processing method of the embodiment includes the steps of extracting second medium feature quantity relating the image data of a specific area in the first medium features and the fiber properties according to the color information of the recording medium, respectively, said recording medium Calculating a gamma correction value for image correction of the original image data to be printed from the density patch image data printed on the image for each input value indicating the color gradation of the pixel, and gamma correction related to the recording medium Creating a correction table in which a value is associated with the first medium feature quantity or the second medium feature quantity in accordance with the range of the input value and storing the correction table in a database; and relating to the recording medium to be printed using formulas or the second medium feature based on the first media feature value, scan to find candidate of the correction table for the recording medium from the database And-up, from the candidates of the correction table, and selecting the correction table to be applied to the image correction at the time of printing of the original image data on the recording medium, wherein using the selected correction table Performing image correction of the document image data .

1 is an overall block diagram of an image processing apparatus according to a first embodiment. The block block diagram of the medium feature-value calculation part in the embodiment. An example of a specific area for extracting an image correction pattern and a medium feature amount in the embodiment. The block block diagram of the medium feature-value extraction part in the embodiment. 2 is a configuration example of a color information extraction unit in the embodiment. An example of gamma correction of the embodiment. 4 is an example of a correction table in the embodiment. The flowchart figure of the database creation in the same embodiment. FIG. 6 is a flowchart showing a copy operation in the embodiment. FIG. 6 is a flowchart showing a printing operation in the embodiment. FIG. 9 is a flowchart showing a copy operation in the second embodiment. FIG. 6 is a flowchart showing a printing operation in the embodiment. The example of the fiber information extraction part in 3rd Embodiment. Explanatory drawing of fiber information calculation in the embodiment. 4 is an example of a correction table in the embodiment.

  The image processing apparatus of the present invention can perform various processes such as a color printer, a color copying machine, a function of copying a base paper, a function of communicating with an external device, a function of transmitting / receiving and printing as a facsimile apparatus, and the like. It includes composite devices (MFPs) that can be used.

  Hereinafter, embodiments will be described in detail with reference to FIGS. 1 to 15.

<First Embodiment>
FIG. 1 shows an overall block diagram of the image processing apparatus according to the present embodiment. In this embodiment, it is assumed that the image processing apparatus 1 is an MFP, and a copy operation, a scan operation, and a print operation can be executed. Further, although description will be made assuming that paper is used as the recording medium, the recording medium includes printing media other than paper. In the image processing apparatus 1, a PC (Personal Computer) 2 that controls the image processing apparatus 1 and a wireless portable terminal 3 such as a smartphone are connected via a network 4.

  The image processing apparatus 1 includes a scanner unit 11 that reads a document, an image processing unit 12 that performs image processing on a line sensor output of the document read by the scanner unit 11, and a specific area read by the scanner unit 11. A medium feature amount calculating unit 13 that calculates a medium feature amount, an image drawing unit 15 that converts data received via the network I / F unit 14 into image data, an image processing unit 12, or a medium as an output of the image drawing unit 15 An image correction unit 16 that applies image correction data based on a feature amount and corrects the signal for a printer, a printer unit 17 that outputs a correction result, and an image correction pattern for creating image correction data used in the image correction unit 16 Pattern forming unit 18 for generating image, control panel unit 19 for giving a control command to image processing apparatus 1 by a user, and image processing apparatus Composed of CPU unit 20 that controls integrally the. The CPU unit 20 is a configuration used for a general computer, and includes a processor, a memory, a hard disk, various interfaces, and the like, and is configured such that the above blocks function.

  FIG. 2 is a block configuration diagram of the medium feature amount calculation unit 13. The medium feature amount calculation unit 13 includes functional blocks of an extraction area determination unit 131, a medium feature amount extraction unit 132, a correction table search unit 133, a correction table creation unit 134, a correction table storage unit 135, and a correction table selection unit 136. Have. The above functional blocks excluding the storage table storage unit 135 operate by executing application software stored in the CPU unit 20 of the image processing apparatus 1.

  The extraction area determination unit 131 determines a specific area for extracting the medium feature amount of the recording medium and an area where the image correction pattern is printed based on the coordinate signal output from the CPU unit 20 at the time of scanning. . FIG. 3 shows an example of a specific area for extracting the image correction pattern and the medium feature amount. An image correction pattern 31 (31C, 31M, 31Y, and 31K) to be printed on a part of the recording medium 30 (printing paper) and specific areas 32A and 32B for extracting medium feature amounts are shown (C is cyan, M represents magenta, Y represents yellow, and K represents black). The image correction pattern 31 is formed by the pattern forming unit 18 for four colors of CMYK, and is printed on the recording medium to be printed by the printer unit 17. Although only the K color is illustrated in FIG. 3, the same applies to each color, and the image correction pattern 31 is formed of a plurality of density patch patterns.

  The specific area 32A for extracting the medium feature amount is an area other than the image correction pattern 31 and is not printed. The specific area 32B is in the image correction pattern 31, but both are set to areas where the patch density is zero. Which specific region 32 is used is appropriately selected according to the embodiment. For example, the specific area 32B is used when reading the image correction pattern 31, and the specific area 32A is used otherwise.

  FIG. 4 shows a block configuration diagram of the medium feature amount extraction unit 132. The medium feature amount extraction unit 132 extracts at least one medium feature amount from the specific region 32. As illustrated in FIG. 4, the medium feature amount extraction unit 132 of the present embodiment includes a color information extraction unit 41 and a fiber information extraction unit 42. In addition, if necessary, a functional block that extracts various media characteristics such as thickness and hygroscopicity and performs parameterization may be added.

  FIG. 5 shows a configuration example of the color information extraction unit 41. The color information extraction unit 41 extracts pixel values that have been color-separated from the specific area 32 for extracting the medium feature amount. Specifically, the color information extraction unit 41 calculates the average of the pixel values for the pixels included in the specific area 32. Ask for each color. For the sake of explanation, FIG. 5 shows a circuit in which the specific region 32 has three pixels and the average value is obtained. The pixel value data in the specific area 32 is read based on the coordinate signal and the clock signal forming the specific area 32, and the data flip-flops 51, 52, 53 for latching the pixel value, and the pixel values in the specific area 32 And an average processing unit 54 for obtaining an average of the data, and a data flip-flop 55 for holding the averaged pixel value (R indicates red, G indicates green, and B indicates blue). With this circuit, an average pixel value in the specific area 32 is obtained for each RGB color. Various other circuits that perform the same operation are conceivable. For example, a circuit that adds pixel values by an adder each time each pixel in the specific area 32 is scanned and divides the number by the number of additions may be used.

  The correction table search unit 133 uses a medium feature amount extracted from the specific area 32 in the medium feature amount extraction unit 132 as a search key, and uses a predetermined logic based on the medium feature amount from a database stored in the correction table storage unit 135. A correction table that matches the expression condition is found and set as a correction table candidate to be applied to the recording medium to be printed. A specific example of the search logical expression will be described later.

  The correction table creation unit 134 calculates a gamma correction value from the density patch data in the area of the image correction pattern 31 read by the scanner unit 11, and the same gamma correction value as the medium feature amount acquired by the medium feature amount extraction unit 132. Create a correction table included in the table.

  Here, a method for calculating the gamma correction value will be described. First, an image correction pattern 31 in which a plurality of density patches shown in FIG. 3 is arranged is formed in the pattern forming unit 18, and this is printed by the printer unit 17 on a recording medium to be printed. The printing result is captured by the scanner unit 11.

  FIG. 6 shows an example of gamma correction. The horizontal axis indicates the read pixel value for the patch number, and the vertical axis indicates the output pixel value. Originally, it is preferable that the gradation characteristic is linear with a one-to-one input / output relationship as indicated by a line segment 60. However, the read value varies like curves 61A and 62A depending on the characteristics of the device, the environment, the recording medium to be printed, and the like. Correction values for correcting the input / output relationship to be linear are curves 61B and 62B. In general, this correction is referred to as gamma correction, but in the present embodiment, a gamma correction value for each CMYK color is included in the correction table.

  FIG. 7 is an example of the correction table of the embodiment. The correction table is databased in association with an identifier (medium ID) for identifying the recording medium, and the medium feature amount and the gamma correction value are included in the same table. The medium feature amount 1 (paper color) is written in the order of R, G, B, and the gamma correction values are written in the order of C, M, Y, K. The correction value in the highlight area is affected by the paper color. For yellow and red paper, the output of the color related to highlight (Y for yellow and M and Y for red) is higher than that for white paper. It can be seen that the correction is made.

  The correction table storage unit 135 stores a plurality of correction tables as a database. The meaning that the medium feature amount and the gamma correction value are included in the same table does not necessarily have to be stored in the same physical location (for example, in the same hard disk), but is associated with a link address. It may be stored in another physical location. The creation of the database will be described later.

  The correction table selection unit 136 selects one of correction tables to be applied to the recording medium during printing from the correction table candidates obtained by the correction table search unit 133. Also, processing such as default setting of an image correction table to be selected is performed when a correction table candidate is not found. Then, using this correction table, image correction is performed on the recording medium to be printed.

  FIG. 8 is a flowchart of database creation.

  In step ST801, the recording medium for performing gamma correction is set on the document table of the image processing apparatus 1. Then, the pattern forming unit 18 generates an image correction pattern (step ST802).

  In step ST803, the printer unit 17 performs image correction pattern printing on the recording medium. In step ST804, the density patch of the printed image correction pattern is read, and the gamma correction amount is calculated from the density of the read patch (step ST805).

  On the other hand, in step ST806, the medium feature of the recording medium is read from the specific area 32, and in step ST807, the read medium feature is parameterized to calculate a medium feature amount.

  In step ST808, the gamma correction amount and the medium feature amount are stored in the same correction table, and in step ST809, the correction table is stored in the correction table storage unit 135 as a database. A database composed of a plurality of correction tables is constructed by repeating the operations in steps ST801 to ST808 described above.

  Next, the copy operation of the image processing apparatus 1 will be described with reference to the flowchart of FIG. First, in step ST901, the user selects whether to perform image correction processing based on the medium feature amount of the present embodiment. Here, this step is defined as a sheet determination step.

  When the user selects paper determination using the control panel unit 19 (ST901: Yes), the user places printing paper on a document table (not shown) according to the instruction displayed on the control panel unit 19 (step ST902). ).

  In step ST903, the scanner unit 11 scans the specific area 32 of the printing paper and calculates a medium feature amount. In step ST <b> 904, the correction table search unit 133 searches the correction table storage unit 135 for correction table candidates that match the logical expression conditions using a logical expression based on the medium feature amount.

  Here, an example of a logical expression when color information is used as the medium feature amount will be described. Now, it is assumed that a database including N correction tables (N is a natural number) is stored in the correction table storage unit 135. Each is set in a correction table (k) (subscript k is a natural number 1 ≦ k ≦ N). Then, the color-separated medium feature amounts in the correction table (k) are R (k), G (k), and B (k).

On the other hand, the color-separated medium feature amounts of the recording medium read from the specific area 32 are R ₀ , G ₀ and B ₀ . As shown in the equation (1), an error between the medium feature amount of the recording medium and the medium feature amount of the correction table is obtained for each color, and a correction table in which these are within predetermined threshold values, R _th , G _th , B _th Search for.

(| R ₀ −R (k) | <R _th ) & (| G ₀ −G (k) | <G _th ) & (| B ₀ −B (k) | <B _th ) (1)
Then, the searched correction table (i) (subscript i is k selected by the expression (1)) is a correction table candidate for applying image correction to the recording medium.

  In step ST905, it is determined whether there is a correction table candidate. When there is a correction table candidate (ST905: Yes), the process proceeds to step ST906.

  In step ST906, the correction table selection unit 136 selects a correction table to be actually applied to the recording medium from the correction table candidates.

  As shown in Expression (2), for example, for each color of the correction table candidate, an error between the medium characteristic amount of the recording medium and the medium characteristic amount of the correction table is obtained, and the largest value among them is calculated.

Max (i) = max (| R ₀ −R (i) |, | G ₀ −G (i) |, | B ₀ −B (i) |)
(∀i) ... Formula (2)
Then, as shown in Expression (3), the correction table having the smallest Max (i) is selected.

min (Max (i): ∀i) (3)
As described above, the correction table to be applied to the recording medium may be automatically determined, or in some cases, the correction table may be manually selected from the correction table candidates.

  In step ST907, the user sets a copy document on the document table, and presses the copy button on the control panel unit 19. Then, the gamma correction value of the selected correction table is applied and printed (step ST908).

  If there is no correction table candidate in step ST905 (ST905: No), it is determined whether a new correction table is created and stored in the database.

  When a new correction table is created (step ST909: Yes), the process proceeds to step ST910, and a gamma correction value based on the printed image correction pattern 31 is calculated. An image correction table is created by combining the gamma correction value and the medium feature amount acquired in step ST 903, and the database is updated to the correction table storage unit 135.

  Then, the correction table is set in the correction table selection unit 136 (step ST906), and the process proceeds to step ST907 and step ST908 to complete the copy operation.

  When a new image correction table is not created (step ST909: No), or when paper determination is not selected (ST901: No), a predetermined correction table is selected, and steps ST907 and ST908 are performed. Go ahead and finish the copy operation.

Here, taking the correction table of FIG. 7 as an example, the processing of steps ST904 to ST906 will be described with specific numerical values. Threshold value R _th = 35, threshold value G _th = 35, threshold value B _th = 35, medium feature amount (240, 240, 240) of paper 0 (white), medium feature amount (237, 210, 180) of paper 1 (yellow) ), The medium feature amount (235, 176, 176) of paper 2 (red) and the medium feature amount of the recording medium to be printed having a pink paper color are (232, 178, 202). From equation (1), paper 0: (8 <threshold R _th ), (62> threshold G _th ), (38> threshold B _th )
Paper 1: (5 <threshold R _th ), (32 <threshold G _th ), (22 <threshold B _th )
Paper 2: (3 <threshold R _th ), (2 <threshold G _th ), (26 <threshold B _th )
Therefore, the image correction table for paper 1 (yellow) or paper 2 (red) is a candidate. Which of these is to be selected is determined by selecting the correction table for paper 2 from min (Max (paper 1) = 32, Max (paper 2) = 26) from equations (2) and (3). The correction value is finally applied.

Similarly, when the medium characteristic amount of the green paper color is (168, 210, 189), paper 0: (72> threshold Rth), (30 <threshold Gth), (51> threshold Bth)
Sheet 1: (69> threshold Rth), (0 <threshold Gth), (9 <threshold Bth)
Sheet 2: (67> threshold Rth), (34 <threshold Gth), (13 <threshold Bth)
In this case, there is no correction table that satisfies the conditions. For this reason, it is selected whether to newly calculate the gamma correction value or to use the existing image correction table even if the accuracy is somewhat reduced.

  Next, the printing operation of the image processing apparatus 1 will be described with reference to the flowchart of FIG. Since the flow on the image processing apparatus 1 (MFP) side is almost the same as that in FIG. 9, the flow ST101, ST102, and ST103 between the PC 2 and the image processing apparatus 1 will be mainly described.

  In step ST101, the user uses the user interface screen of the printer driver installed on the PC 2 to select whether to determine paper. This selection command is transmitted to the MFP side via the network 4 and received by the network I / F unit 14. Then, the process proceeds to step ST901. Thereafter, the image correction table shown in the flowchart of FIG. 9 is searched and selected.

  When the image correction table is set in step ST906, the MFP notifies the PC 2 that the setting of the image correction table has been completed. In step ST102, the PC 2 performs PDL (Page Description Language) of the document / image file to be printed. Send data to the MFP.

  In step ST103, the image drawing unit 15 of the MFP generates image data from the PDL file sent from the PC 2. In step ST908, image correction is performed on the image data based on the gamma correction value of the selected image correction table, and printing is performed.

  According to the first embodiment described above, the image correction table in which the medium feature amount and the gamma correction table are stored in advance is stored as a database, and the medium feature amount of the recording medium is read at the time of printing. It is possible to apply an optimal gamma correction value based on the above.

  Therefore, it is possible to provide an image processing apparatus and an image processing method that can perform high-quality printing on a wide variety of recording media without the user being aware of it. In addition, since an image correction table can be newly registered in the database even for a recording medium that is not in the database, the optimum gamma correction table is searched and selected the next time printing is performed on the recording medium.

<Second Embodiment>
In the first embodiment, the scanner function of the image processing apparatus 1 (MFP) having the scanning unit 11 is used. In this case, the user needs to set a recording medium to be printed on the scanner platen. In the present embodiment, a device and method for adding a medium feature amount in addition to the scanner function of the MFP and selecting an optimal gamma correction value without the user setting a recording medium on the scanner platen will be described. .

  For example, an image sensor for each of the R, G, and B channels is arranged in the paper conveyance unit of the printer unit 17, and the medium feature amount is acquired using the paper conveyance at the time of printing. Alternatively, a method of installing an application using a camera function in a mobile terminal 3 such as a smartphone connected to the network 4 and acquiring a medium feature amount based on an image taken by the camera can be considered.

  FIG. 11 is a flowchart showing a copy operation in this embodiment. The same flow as in FIG. 9 is denoted by the same reference numeral, and the description is simplified.

  In step ST111, a copy document is placed on the document table of the scanner unit 11. When paper determination is made (step ST902: Yes), the R, G, B image sensors arranged in the paper conveyance unit (not shown) of the printer unit 17 read the medium feature amount according to the conveyance of the recording medium (step ST112). .

  Alternatively, the user captures a recording medium using the camera function of the mobile terminal 3 and transfers the image or paper color to the image processing apparatus 1. These functions are installed as an application in the mobile terminal 3 such as a smartphone, and are processed in synchronization with the operation of the image processing apparatus 1.

  In step ST113, the medium feature amount is calculated from the output signals of the R, G, and B image sensors arranged in the paper transport unit of the printer unit 17 or the image or paper color information transmitted from the portable terminal 3, and the image is obtained from the database. It progresses to the step which searches a correction table (step ST904). If the correction table exists and is set (step ST905: Yes, step ST906), image correction processing is performed using the gamma correction value of the image correction table and printing is performed (step ST908).

  FIG. 12 is a flowchart showing the printing operation in the same embodiment, but each flow is the same as FIGS. When correction table candidates are found from the database, the user can perform high-quality printing operations on various recording media without leaving the PC.

  As described above, according to the second embodiment, since the medium feature amount is not acquired using the scanner function of the image processing apparatus 1 (MFP), the convenience is further improved.

<Third Embodiment>
In the present embodiment, an embodiment in which fiber information is used as a medium feature amount will be described. FIG. 13 is a block configuration diagram of the fiber information extraction unit 42. FIG. 14 is an explanatory diagram of fiber information calculation.

  The fiber information extraction unit 42 includes an edge enhancement unit 421, a histogram calculation unit 422, and a fiber information calculation unit 423. When the recording medium is paper, the characteristics of the fibers differ from one sheet to another. Therefore, a difference appears in the medium characteristics by acquiring the fiber pattern with the same amount of light.

  The edge emphasizing unit 421 performs edge emphasis processing for emphasizing fibers on the image data obtained from the specific region 32. The image data 141 acquired from the specific area 32 is subjected to edge enhancement processing on the paper A and the paper B in 142A and 142B. For the sake of explanation, it is assumed that the fiber patterns of the two types of papers A and B are the same. In the case of the paper A, the paper fibers can be clearly acquired, but in the case of the paper B, the fibers are discontinuous.

  The histogram calculation unit 422 calculates histograms 143A and 143B for the fiber pattern subjected to the edge enhancement processing. By digitizing with a histogram, the difference in fiber pattern can be clarified.

  The histogram itself may be used as the medium feature amount, but the fiber feature calculation unit 423 may further process the histogram to calculate the medium feature amount. For example, in the case of a recording medium with thick fibers and absorbability such as Japanese paper, it may be necessary to increase the amount of toner or the amount of ink in a region having a high density. In order to correct such a case, only the frequency included in the predetermined pixel value range on the high density side may be extracted and used as the medium feature amount. Further, the medium feature amount may be changed by changing the level of the light amount and including the change in the fiber information accompanying the change in the light amount.

  FIG. 15 shows an example of the image correction table. The sheet color information of the first embodiment is used as the medium feature amount 1, and the fiber information histogram of the present embodiment is stored as the medium feature amount 2. At this time, it can be seen that correction on the high density side has been made for paper 0, paper 1 and paper 2. In the correction on the low density side, the paper color is corrected.

  As described above, according to the third embodiment, since a number of different recording media can use the gamma correction values associated with a plurality of medium feature amounts, the user can perform simple operations without being aware of them. Thus, a high-quality printing result suitable for the recording medium can be obtained.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

11 ... scanner part,
12: Image processing unit,
13: Medium feature calculation unit,
14 ... Network I / F part,
15: Image drawing unit,
16: Image correction unit,
17 ... Printer section,
18 ... pattern formation part,
19 ... Control panel section,
20 ... CPU section,
131... Extraction area determination unit,
132... Medium feature amount calculation unit,
133 ... Correction table search unit,
134... Correction table creation unit,
135: Correction table storage unit,
136... Correction table selection unit.

Claims (6)

A media feature amount extraction unit which extracts second medium characteristic quantity of the first medium features and the fiber properties according to the color information from the image data of the specific area of the recording medium, respectively,
A gamma correction value for correcting the image of the original image data to be printed is calculated for each input value indicating the color gradation of the pixel from the density patch image data printed on the recording medium, and the gamma according to the recording medium is calculated. A correction table creating unit that creates a correction table in which a correction value is associated with the first medium feature quantity or the second medium feature quantity according to a range of the input value ;
A correction table storage unit for storing the correction table in a database;
Using formulas or the second medium feature based on the first media feature quantity relating to said recording medium to be printed, the correction table search to find candidate of the correction table for the recording medium from the database And
From the candidates of the correction table, the correction table selection unit for selecting the correction table to be applied to the image correction at the time of printing of the original image data on the recording medium,
An image correction unit that performs image correction of the document image data using a gamma correction value of the selected correction table;
An image processing apparatus. In the correction table search unit, if the candidate of the correction table for the recording medium is not found,
The correction table creation unit creates a new correction table associating the gamma correction value according to the recording medium to the first medium characteristic quantity or the second medium feature amount according to the range of the input value,
The correction table storage unit stores the new correction table in the database,
The image processing apparatus according to claim 1, wherein the image correction unit performs image correction using a gamma correction value of the new correction table. It said first media feature amount is pre Kitoku image processing apparatus according to claim 1, wherein the constant region image data of a pixel value extracted by the color separation. It said second media feature quantity, the image processing apparatus according to claim 1, wherein calculated based on a histogram indicating the frequency of pre Kitoku pixel value of the constant region image data. Extracting second medium characteristic quantity of the first medium features and the fiber properties according to the color information from the image data of the specific area of the recording medium, respectively,
Calculating a gamma correction value for image correction of the original image data to be printed from the density patch image data printed on the recording medium for each input value indicating the color gradation of the pixel ;
Creating a correction table in which a gamma correction value related to the recording medium is associated with the first medium feature quantity or the second medium feature quantity according to the range of the input value , and storing the correction table in a database;
A step of using a logical expression or the second medium feature based on the first media feature quantity relating to said recording medium to be printed, looking for candidates of the correction table for the recording medium from said database,
From the candidates of the correction table, and selecting the correction table to be applied to the image correction at the time of printing of the original image data on the recording medium,
Performing image correction of the document image data using the selected correction table;
An image processing method. If the candidate of the correction table for the recording medium is not found,
A new correction table is created in which a gamma correction value related to the recording medium is associated with the first medium feature quantity or the second medium feature quantity according to the range of the input value, and the new correction table is Storing in the database and performing image correction using the gamma correction value of the new correction table;
The image processing method according to claim 5, further comprising:

Images