JPH0776978B2 - Image processing method - Google Patents

Description

The present invention relates to an image processing method for automatically reading and processing document image information.

[Prior Art] FIG. 10 shows a character recognition process of a conventional character recognition device of this type.

The characters on the manuscript paper P are read character by character as shown in step S81 and photoelectrically converted, and this is further converted to "1" in step S82.
Converted to binary data pattern of "0". In a succeeding step S83, pre-processing for making the later-described processing effective, that is, noise processing such as black dots on the paper P on which the characters are recorded based on the binarized pattern in step S82 and a character graphic boundary. A series of processing including surface smoothing is performed. Next, in step S84, a feature extraction process is performed to extract some features (intersection points, branch points, the number of loops, stroke length information, etc.) necessary for character recognition.
Depending on the extraction result, some characters having common characteristics are selected from many characters. Next, in step S85 and subsequent steps, a dictionary matching process and a recognition process are performed as an identification process for selecting a unique character from among them.

First, it is checked whether or not the dictionary can be guided (searched) according to the features extracted in step S85. If the feature extracted here is not enough to guide the dictionary, the process proceeds to step S88, and unrecognizable is output. On the other hand, if the dictionary can be guided by the extracted feature points, the built-in dictionary is searched in step S86, and the extracted features are sequentially compared with the extracted features. If the result of collation in step S87 is a match, step S88
Outputs the matching result as a recognition output. If no match is found, it is output as unrecognizable.

[Problems to be Solved by the Invention] However, according to the conventional recognition method, the complicated processing described above is performed even for simple characters (characters that are easily recognized), alphabet letters, and numbers only. However, there was a drawback that the processing time was too long.

Further, the configuration for realizing the above processing is complicated, and there are various problems in terms of cost up and reliability.

[Means for Solving Problems] The present invention has been made in view of the problems of the above-described conventional technology, and includes the following configuration as one means for solving the above problems.

That is, a reading unit that optically reads a document, a dividing unit that divides the document image information read by the reading unit into predetermined regions, and each region divided by the dividing unit appear on a predetermined number of lines. A detection unit that detects the number of groups of consecutive black pixel groups and a determination unit that determines the maximum value of the number of groups detected by the detection unit as a representative value of the area are provided.

[Operation] In the above configuration, image information obtained by optically reading a document is input, the input image information is divided into predetermined regions, and each divided region appears on a predetermined number of lines. By detecting the number of groups of consecutive black pixel groups and determining the maximum value of the number of detected groups as the representative value of the region, accurate pattern recognition processing can be performed in a very short time.

Embodiment An embodiment according to the present invention will be described in detail below with reference to the drawings.

FIG. 1 is a block diagram of an embodiment of the present invention.
Is a reader for reading document image information including keywords by OMR and converting it into an electric signal, 2 is an optical disk for storing the image information read by the reader 1, 3 is a host computer for controlling the entire embodiment, 4 is a keyboard, 5 Is a CRT that displays image information and operation information, and 6 is a printer that prints out image information and the like. Reference numeral 7 is an auto feeder for automatically feeding the originals to the original reading surface of the reader 1 one by one.

In the host computer 3, 50 is a CPU that controls the entire apparatus according to the control program shown in FIG. 4 stored in the ROM 51, and the CPU 50 is preferably composed of, for example, a Microcomputer MC68000 manufactured by Motorola. Reference numeral 51 is a ROM, and the ROM 51 includes a standard feature pattern storage area 51a. Reference numeral 52 is a CRT interface that controls the interface with the CRT 5, 53 is a keyboard interface that controls the interface with the keyboard 4, and 54 is an optical disk interface that controls the interface with the optical disk. Further, 55 is a reader interface that controls the interface with the reader 1, 56 is a printer interface that controls the interface with the printer 6, and 57 is a process progress, a read mark recognition process progress, etc. are stored.
The RAM and 60 are buses that connect the respective components.

The detailed storage area of the RAM 57 is shown in FIG.

In FIG. 2, 21 is a pattern buffer, 22 is a line histogram buffer, 23 is an area histogram buffer,
24 is a reading pattern.

FIG. 3 shows an external view of this embodiment having the above configuration.

In the figure, the same numbers are assigned to the same configurations as in FIG. 8
Is an interface cable between the reader 1 and the host computer 3, and 9 is an interface cable between the printer 6 and the host computer 3.

The operation of this embodiment having the above configuration will be described below with reference to the flow chart of FIG.

In FIG. 4 as well, similar to FIG. 10, the process of reading and recognizing the pattern indicated by P on the document set by the reader 1 will be described as an example.

First, in step S1, the CPU 50 activates the reader 1 via the reader interface 55, scans the read document surface, and reads the image data of the document surface.

On the original surface, for example, a mark is placed at the bottom of the OMR sheet shown in FIG. 9, and a type pattern is applied on the mark as shown in FIG. The OMR sheet is used for registering keywords of the electronic file system, inputting telephone numbers of facsimiles, setting the number of copies of image forming devices such as copying machines, and setting modes such as reduction ratio.

When the format as shown in FIG. 8 is fixed and the characters of the fixed pattern are written on it, the subsequent process becomes simpler. In addition, "A" to "Z" and "1" are shown in FIG.
A fixed pattern of "0" is shown. The basic pattern of the format shown in FIG. 8 is a part of a combination of a "Ta" character composed of three strokes in the x direction and three strokes in the y direction and two diagonal strokes "X". .

The case where one character at the mark position on the document surface thus written, for example, "A" is read will be described below as an example.

The signal photoelectrically converted by the reader 1 and read in step S1 is read by the reader interface as shown in step S2.
It is sent to 55, is converted into the digital signal of the binary pattern of "1", "0" by the analog-digital converter built in the reader interface 55, and the converted digital signal is
Input to CPU50.

The CPU 50 sequentially stores the digital data thus input in the pattern buffer 21 of the RAM 57. In this embodiment, the character pattern is divided into areas of 1 character 48 bits × 48 bits, and an example of storing read data in the pattern buffer 21 when "A" is read is shown in FIG.
Here, when the black density is detected, the data is "1".

In step S3, the CPU 50 obtains a histogram of the number of strokes for each line in the horizontal and vertical directions. Specifically, as shown in FIG. 5, the histogram of the stroke distribution of the uppermost line in the horizontal direction (X direction) is "1", the histogram of the fourth line is "2", and the histogram of the vertical direction (Y direction) is shown.
The histograms of the stroke distributions of the leftmost line and the next line are "1" and the fifth line is "2". Then, the stroke distribution histogram obtained in step S4 is stored in the line histogram buffer 22 of the RAM 57. In the next step S5, the reading pattern shown in FIG. 5 is changed to 1 to 6 in FIG.
It is divided into predetermined areas shown in A to D. In each of the divided areas, for example, the histogram of the stroke distribution for each line of the area 1 in FIG. 6 (A) is “1, 1, in order from the first line as shown in FIG. 6 (B) 51. "2,2,2",
As shown in 52, the area A is "2,2,3,2," in order from the first line.
2 ".

Then, in step S6, the minimum value of the histogram for each line in the predetermined area previously obtained is found, and this value is stored in the area histogram buffer 23 of the RAM 57 as a representative value of the area. In area 1, the minimum value of the histogram distribution is "1", and the area histogram buffer 23 has this "1".
Is stored. Similarly, in step S7, the maximum number of generated strokes of the histogram distribution for each line in the predetermined area previously obtained is obtained and stored in the area histogram buffer 23 of the RAM 57. In area A, the maximum number of strokes in the histogram distribution is "2", and the area histogram buffer
This “2” is stored in 23.

Then, in step S8, a representative value for each area is obtained and stored in the read pattern 24 of the RAM 57. Here, FIG. 6 (A)
In areas 1 to 6 shown in (1), the minimum value of the histogram distribution is used as a representative value, and in areas A to D, the maximum number of generated strokes is used as a representative value. FIG. 6C shows the storage state of representative values in all areas in the read pattern 24.

In a succeeding step S10, the standard pattern stored in the standard characteristic pattern 51a of the ROM 51 and the read pattern stored in the read pattern 24 are matched. As a result, if a pattern match is obtained in step S11, step S12
It is recognized as an input of the pattern obtained by matching, and the result is output. On the other hand, if no match is found, step S13
Then, the recognition is not output and the process is terminated. Then, the reading process of the next pattern is executed again.

The standard pattern of "A" of the input standard feature pattern 51a is the seventh
The pattern shown in the figure matches the read pattern shown in FIG. 6 (C), and the input pattern in FIG. 6 (A) is recognized as the input of "A".

As described above, according to this embodiment, the following effects can be considered in recognizing the character pattern shown in FIG. 5, for example.

By setting the maximum number of occurrences of stroke distribution in a predetermined area as a representative value, it is possible to remove reading of dust or the like which is erroneous reading in the area. For this reason,
As shown in FIG. 6 (B), even if the histogram of the line changes to some extent, such as when there is dust in the area and the histogram of the line becomes “3”, the maximum number of occurrences of stroke distribution is set as the representative value. The influence can be prevented and accurate character recognition becomes possible.

Furthermore, since the amount of data to be collated is small, the processing time is greatly reduced, and recognition is possible only by collating a small amount of data, the pattern of FIG. 6C and the standard feature pattern shown in FIG.

In this way, the drawbacks of simple character recognition of the character recognition device can be eliminated, the processing time required for simple character recognition can be shortened, and high-speed and highly accurate character recognition can be performed.

Further, it is possible to recognize a fixed pattern (print type) numeral or an alphanumeric character at high speed and with high accuracy.

As described above, according to the present invention, in a very short time,
And accurate pattern recognition processing can be performed.

[Brief description of drawings]

FIG. 1 is a block diagram of an embodiment according to the present invention, FIG. 2 is a detailed configuration diagram of the RAM shown in FIG. 1, FIG. 3 is an external view of this embodiment, and FIG. 4 is a pattern of this embodiment. Recognition control flow chart, FIG. 5 is a diagram showing an example of reading pattern storage in the pattern buffer of the present embodiment, and FIGS. 6 (A) to 6 (C) explain the recognition processing of the pattern “A” according to the present embodiment. FIG. 7 is a diagram showing a storage pattern of “A” in a standard feature pattern, FIG. 8 is a diagram showing a standard input pattern used in this embodiment, and FIG. 9 is an OMR used in this embodiment. FIG. 10 shows a sheet, and FIG. 10 is a flow chart showing conventional pattern recognition processing. In the figure, 1 ... reader, 2 ... optical disk, 3 ... host computer, 4 ... keyboard, 5 ... CRT, 6 ...
Printer, 7 ... Auto feeder, 50 ... CPU, 51 ... R
OM, 51a …… Standard feature pattern storage area, 52 …… CRT interface, 53 …… Keyboard interface, 54 ……
Optical disk interface, 55 …… Reader interface, 56 …… Printer interface, 57 …… RAM, 60…
… It ’s a bus.

Front Page Continuation (72) Inventor Akihiko Uekusa 3-30-2 Shimomaruko, Ota-ku, Tokyo Canon Inc. (56) Reference JP-A-57-45682 (JP, A)

Claims (1)

[Claims] 1. Image information obtained by optically reading a document is input, the input image information is divided into predetermined regions, and continuous blacks appearing on a predetermined number of lines for each of the divided regions. An image processing method, comprising: detecting a group number of a pixel group, and determining a maximum value of the detected group number as a representative value of the area.