JP4616199B2 - Image processing apparatus and program - Google Patents

Description

The present invention relates to an image processing apparatus and program used for an image forming apparatus such as a color digital copying machine or a scanner distribution apparatus. More specifically, the present invention enables appropriate image processing without reducing the resolution of characters. Related to technology .

  In recent years, color printing, such as color printers that digitally process color image data and output color, and color copiers that color-separate and electrically read color originals and copy the acquired color image data onto paper. -Image processing devices capable of output are widely used and popularized. In such an image processing apparatus, an enormous amount of image information related to a document image is handled, and an efficient compression method is required to reduce the data amount.

  Among them, for example, compression that performs irreversible compression like a JPG file has a very high compression rate, and can create a small file with a reduced data amount. Compressing an image is effective for multi-valued areas (gradation areas) such as images such as images, but character edges are not applied to binary images such as character images. It is out of focus and the text is not legible.

As conventional techniques for solving such problems, the inventions disclosed in Patent Documents 1 to 3 are known. Patent Document 1 describes an invention relating to an image processing apparatus capable of transmitting or storing image data with an optimum data amount and high image quality. Patent Document 2 discloses an invention relating to an adaptive encoding apparatus and decoding apparatus for a color document in which a color document image is divided into a black character / white background area and a picture area only by local processing and encoded for each area. Are listed. Further, Patent Document 3 describes an invention that prevents the appearance of light black or other colors adjacent to the outside of the character edge, and improves the reproduction image quality of the character.
JP 2002-368986 A Japanese Patent No. 3193086 JP 2001-268383 A

  As in Patent Document 1 and Patent Document 2 described above, two high-resolution binary data is obtained by combining two high-compression image data and high-resolution binary data in a single file. By selectively switching the image in (character area), it is possible to create a highly compressed image file while the character resolution remains high even if the character edge is output with binary resolution. . When extracting character data here, when separating the character area from the non-character area, for example, when using rough dots like characters in a newspaper photo section, when discontinuous points occur, lossless compression is performed. It is known that the compression rate is deteriorated. Also, it is known that even in a natural image such as a normal person, when the binarization is performed with darkness, many discontinuous points are generated and the compression rate is deteriorated.

  Moreover, in a printed matter or the like, characters are generally thin in background and dark. However, when emphasizing characters or synthesizing characters with photographs, there are so-called white characters that darken the background and white the characters, as shown in FIG.

  When such white characters are used, in the conventional technology, determination is performed using halftone dot determination or gray (medium density) determination. For example, when the halftone dot area is 100% or in a high density region It is difficult to make a gray judgment. In addition, for example, when the background is black and the characters are white, that is, when white characters are formed on the black background, if the white area is small, the pattern becomes a pattern, and the readability of the white characters is deteriorated. .

In view of such problems, the present invention aims to provide an image processing apparatus and a program for image processing readability of the so-called white text is not deteriorated.

In order to achieve the above object, the present invention is an image processing apparatus for detecting a character region from input image data, and for each of the N types of colors, a pixel having a dark color is selected as an active pixel. A second binarization process is performed, an output result is held for each of the N types of colors, and each pixel of the image data is binarized at a white level to determine whether the pixel is a white pixel A binarization process, and a gray area detection for sequentially determining each pixel of the image data for each line and determining whether each pixel is a gray pixel or a non-gray pixel And the gray area detecting means determines that the pixel of interest is a gray pixel until pixels determined to be white pixels by the second binarization process continue beyond the first number. In addition, the N binarization process performs the N binarization process. Pixels determined to be the active pixels of the black of the color classes is, when continuously exceeds the second number, a result of determining a pixel of interest as a non-gray pixels, the pixels that are gray pixel is detected as a gray area, further characterized by having a character area not equal determines the character region detecting unit gray area detected by the gray area detecting means, there is provided an image processing apparatus.

In addition, the present invention is a program for causing a computer to execute image processing for detecting a character area from input image data, wherein the computer has a dark color for each pixel of the image data for each of N types of colors. A first binarization process using an active pixel as a pixel, a process of holding an output result for each of the N colors, and a second binarization of binarizing each pixel of the image data at a white level and processing, by the sequential processing of each line of each pixel of the image data, wherein each pixel and gray area detecting process determines whether the non-gray pixels or a gray pixel, detected by the gray area detecting process and the gray region character area determined not character region detection processing, is executed, the gray area detection process, the second pixel determined as a white pixel by binarization process, the first few ultra Until successive Te, it determines the pixel of interest as a gray pixel, and the first said N type by binarization of the pixels determined to be the active pixels of the black of the color, the second If continuous beyond number, a result of determining a pixel of interest as a non-gray pixels, the pixels that are gray pixel, characterized in that it is a process of detecting a gray area, is provided a program is there.

ADVANTAGE OF THE INVENTION According to this invention, the image processing apparatus and program which perform the image process which does not deteriorate the legibility of what is called a white character can be provided .

  In the present embodiment, the gray portion and the halftone dot region are detected in the photographic part, and the period of the isolated dot and the specific color are handled in the same manner as the white pixel, so that the high density portion of the specific color (black) or the halftone dot is obtained. Is not used as a picture. As a result, white characters on the background of the specific color (black) as shown in FIG. 20 become characters. Furthermore, it is possible to deal with white characters on gradation. The gradation is a halftone dot shape or expresses light and shade according to numerical values of image data.

Hereinafter, an image processing apparatus, an image transmission apparatus, an image forming apparatus, a program, and a recording medium according to the present embodiment will be described with reference to the drawings. In addition, this embodiment is not limited to what is described below, A various change is possible in the range which does not deviate from the meaning. In the present embodiment, a digital color image processing measure will be used.
FIG. 1 is a block diagram showing a schematic configuration of a color image processing apparatus 1 of the present embodiment.

  As shown in FIG. 1, a color image processing apparatus 1 according to this embodiment includes a scanner 2, a scanner correction unit 3, a compression processing unit 4, a controller 5, an HDD 6, a NIC 7, an expansion processing unit 8, and a printer. A correction unit 9 and a plotter 10 are provided.

  When the color image processing apparatus 1 operates as a copying machine, first, the scanner 2 reads image data from a document, converts the image data (analog signal) into digital data (for example, 600 dpi), and outputs the digital data to the scanner correction unit 3. . As will be described later, the scanner correction unit 3 classifies the image area of the image data (digital data) read and output by the scanner 2 into characters, line drawings, photographs, etc., or removes the background image of the original image. In addition, image processing such as filter processing of RGB data that is image data in the R (red), G (green), and B (blue) format, which are the three primary colors of light, is performed.

  After the image correction processing in the scanner correction unit 3, the compression processing unit 4 compresses, for example, each RGB 8-bit image data, edge character region signal (1 bit), and color region signal (1 bit) into a general-purpose bus. Send the compressed data. The compressed image data is sent to the controller 5 through the general-purpose bus. The controller 5 has a semiconductor memory (not shown) and accumulates transmitted data. In the accumulated data, the image size and the type of the read original are recorded as bibliographic information.

  Although the image data is compressed here, the data may be handled in an uncompressed state if the bandwidth of the general-purpose bus is sufficiently wide and the capacity of the HDD to be stored is large.

  Next, the controller 5 sends the image data of the HDD 6 to the decompression processing unit 8 via the general-purpose bus. The decompression processing unit 8 decompresses the compressed image data into original RGB 8-bit data, an edge character region signal (1 bit), and a color region signal (1 bit), and sends them to the printer correction unit 9. The printer correction unit 9 converts the RGB image data into Y (yellow), M (magenta), C (cyan), and Bk (black) toners for color printing by a color correction processing unit 91 described later. Convert to corresponding YMCBk data.

  A portion that is an edge character area signal but not a color area signal is replaced with black color data as Bk monochromatic data. Further, γ correction processing, halftone processing, and the like are performed, and the light / dark characteristic correction processing and tone number conversion processing of the plotter 10 are performed. In the gradation number conversion process here, image data is converted from 8 bits to 2 bits for each color using error diffusion, dither processing, or the like. The plotter 10 is a transfer paper printing unit using, for example, a laser beam writing process, draws 2-bit image data as a latent image on a photoconductor, and forms a copy image on the transfer paper after image formation / transfer processing with toner.

  When the color image processing apparatus 1 operates as a distribution scanner that distributes image data to a PC or the like via a network, the image data is sent to the controller 5 through a general-purpose bus. As will be described in detail later, the controller 5 performs color conversion processing, formatting processing, and the like. In the gradation processing, gradation conversion processing is performed in accordance with the mode during the distribution scanner operation. In the format processing, general-purpose image format conversion to JPEG format or TIFF format is performed. Thereafter, the image data is distributed to an external PC terminal or the like via a NIC (network interface controller) 7.

  Further, when the color image processing apparatus 1 operates as a printer that prints out from a PC or the like via a network, it can analyze an image and a command instructing printing from data sent from the NIC 7 and print it as image data. Bitmap is expanded into a state, and the expanded data is compressed and accumulated. The accumulated data is written to a hard disk drive (HDD) 6 which is a large capacity storage device as needed. When the image data is stored, bibliographic information, which will be described later, is also written in the HDD 6.

  Next, the controller 5 sends the image data of the HDD 6 to the decompression processing unit 8 via the general-purpose bus. The decompression processing unit 8 decompresses the compressed image data to the original 8-bit data and sends it to the printer correction unit 9. In the printer correction unit 9, if the input is RGB, the color correction processing unit 91 converts it into YMCBk data. Next, γ correction processing, halftone processing, and the like are performed independently for each YMCBk, and lightness / darkness characteristic correction processing and gradation number conversion processing of the plotter 10 are performed.

  In the gradation number conversion process here, image data is converted from 8 bits to 2 bits for each color using error diffusion, dither processing, or the like. The plotter 10 is a transfer paper printing unit using, for example, a laser beam writing process, draws 2-bit image data as a latent image on a photoconductor, and forms a copy image on the transfer paper after image formation / transfer processing with toner.

  In the color image processing apparatus of this embodiment, generally, an original is read by a scanner, image data is converted into digital data, and an image area (image area) of the original is classified into areas having different characteristics (image area separation). ) Various image processing is performed on the image data according to the determination result as to which region the pixel of interest belongs to. As a result, the image quality of the output image can be greatly improved.

Next, FIG. 2 is a block diagram showing a configuration of the scanner correction unit 3 of the present embodiment.
The scanner correction unit 3 of the present embodiment includes an image area separation unit 31, a scanner γ unit 32, a filter processing unit 33, and a document type determination unit 34.

  The scanner correction unit 3 performs image area separation by the image area separation unit 31 based on the image data img (reflectance linear) input from the scanner 2. The image area is separated into three areas: a black edge character area, a color (color) edge character area, and the other (photo area). By separating the image areas, an image area separation signal (edge character area, color area) is given to the image data for each pixel. The image area separation signal is classified into black edge character areas (areas that are edge character areas and not color areas), color edge character areas (areas that are color areas instead of edge character areas), and photo areas (black edge areas and color edges). Non-region). Note that the image area separation in the present embodiment may be performed by separating the image areas by an image area separation method described in Japanese Patent Application Laid-Open No. 2003-259115, which is a prior invention of the present application.

  The scanner γ unit 32 converts image data from reflectance linear to density linear. The filter processing unit 33 switches the filter processing based on the image area separation signal. In this case, sharpening processing is performed with emphasis on legibility in the edge character area of the black edge character and the color edge character. On the other hand, in the photo area, a sharp density change in the image data is used as an edge amount, and smoothing processing or sharpening processing is performed according to the edge amount. The sharp edges are sharpened to make the characters in the picture easier to read.

  The document type determination unit 34 determines whether the image data img is a character-only document or a color document. As the document determination block, a determination method described in Japanese Patent Application Laid-Open No. 2000-324338, which is a prior invention of the present applicant, may be used. Specifically, the determination method described in paragraphs [0023]-[0025] in the above-mentioned Japanese Patent Application Laid-Open No. 2000-324338 is used for determining the document with characters, and the same method is used for determining the chromatic document. The determination method described in paragraph numbers [0026] and [0027] is used, the determination method described in paragraph number [0028] is used for photographic paper photo determination, and the same is applied to print photo determination. The determination method described in paragraph numbers [0029]-[0031] is used.

  Using the feature values obtained by these determination methods, it is determined whether the document is a character-only document or a color document. The result is recorded as bibliographic information of the image data when the image data is stored. Note that a character-only document is a character document determination (present), photographic paper photograph determination (none), and print photograph determination (none), as shown in Table 1 below, under the above-described determination conditions. In addition, the color document indicates a condition for determining whether a chromatic document is present (present).

  In other words, a text-only document is a document in which only characters are present in the document. Here, gradation processing is applied to a pattern such as a copy original or an ink jet original, and the image is classified as either a photographic paper photographic original or a printed photographic original.

Next, FIG. 3 is a block diagram showing the configuration of the printer correction unit 9 of the present embodiment.
The printer correction unit 9 of the present embodiment includes a printer γ unit 92 that performs γ correction on the image data that has undergone the color correction processing unit 91 and the compression processing unit 4 and the expansion processing unit 8 according to the γ characteristics of the plotter 10. A halftone processing unit 93 that performs gradation correction by performing quantization such as dither processing and error diffusion processing, and an edge amount detection unit 94 that detects a steep density change in the image data as an edge amount. Yes.

  The color correction processing unit 91 converts R, G, B data into C, M, Y data by a primary density masking method or the like except for the black edge character region. In order to improve the color reproduction of the image data, the common portion of the C, M, Y data is subjected to UCR (additional color removal) processing to generate Bk data, and the C, M, Y, Bk data is output. Here, the black edge character area corresponds to the luminance only of the black character area because the black character of the original is colored due to the RGB reading position deviation of the scanner or the overlapping position deviation is present in the printer with the YMCBk of the plotter. The signal is output as Bk single color data (C, M, and Y are data not printed out).

  The printer γ unit 94 performs γ correction processing according to the frequency characteristic of γ in the plotter 10 for image data. The halftone processing unit 93 performs quantization such as dither processing according to the gradation characteristics and edge amount of the plotter 10. At this time, it is also possible to enhance the contrast of the black character by performing a black character signal (a black character extraction process described later) during the quantization process. This improves the legibility of characters.

Next, FIG. 4 is a block diagram showing a configuration of the controller 5 of the present embodiment.
The controller 5 of the present embodiment includes a page memory 51, a compression / decompression processing unit 52, an output format conversion unit 53, an input format conversion unit 54, and a data interface (i / f) unit 55.

A data flow when image data is output to an external device via the controller 5 will be described.
First, the image data in the page memory 51 is compressed / decompressed by the compression / decompression processing unit 52. Since the data is output to the external device, the compressed image data is expanded to the original 8-bit data for each color and output to the output format conversion unit 53. The output fort conversion unit 53 performs color conversion of RGB data to sRGB data, which is a standard color space, and simultaneously performs general-purpose image format conversion to JPEG format or TIFF format. The data i / f unit 55 outputs the data sent from the output format conversion unit 53 to the NIC.

On the other hand, the flow of data when image data from an external device is output to the plotter 10 via the controller 5 will be described.
A command (not shown) is analyzed by a CPU (not shown) and written in the page memory 51. The data i / f unit 55 expands the image data into bitmap data by the input format conversion unit 54, performs compression processing by the compression / decompression processing unit 52, and writes it to the page memory 51. The input format data is a natural image such as JPG or TIFF.

Next, the output format conversion unit will be described with reference to the drawings.
FIG. 5 is a block diagram illustrating a configuration of the output format conversion unit 53.

  The output format conversion unit 53 includes a color conversion unit 531, a resolution conversion unit 532, a TIFF format generation unit 533, a JPG format generation unit 534, and a compression format generation unit 535.

  As described above, the color conversion unit 531 performs data conversion from RGB data to sRGB data. Then, the data converted into sRGB is subjected to pixel density conversion such as 300 dpi and 200 dpi by the resolution conversion unit 532. In this embodiment, the pixel density degree when converted at 300 dpi will be described.

  The image whose resolution is converted by the resolution conversion unit 532 is converted into each format by the TIFF format generation unit 533, the JPG format generation unit 534, and the compression format generation unit 535. The data thus converted outputs a format to be output to the NIC 7 via the data i / f unit 55.

  Here, the compression format generation unit 535, which is a main part of the present embodiment, will be described.

  The compression format generation unit 535 of the present embodiment includes a binarization unit 5351, a binary image generation unit 5352, a black image generation unit 5353, a resolution conversion unit A5354, a resolution conversion unit B5355, and a background image generation unit 5356. And a character image generation unit 5357 and an image file composition unit 5358.

  A binarization unit 5351 outputs binary data and black character data of a character region and a non-character region on the basis of light and dark image density. The binary image generation unit 5352 performs MMR compression, which is reversible conversion, on binary data. The black image generation unit 5353 performs MMR compression that is reversible conversion on black character data.

  The resolution conversion unit A5354 and the resolution conversion unit B5355 perform resolution conversion on the image data and reduce the resolution to, for example, about 150 dpi. Further, the background image generation unit 5356 rewrites the image data of the region that has become the character region by the binarization unit 5351 to the image data of the region corresponding to white to image data of a certain value, and is irreversibly compressed jpg Perform compression. Furthermore, the character image generation unit 5357 rewrites the image data of the region that has become the character background region to image data of a certain value, and performs irreversible compression jpg compression.

  The reason why the character portion is set to a constant value for the background image is that the compression is improved by setting the constant value. Setting the background image to a constant value for the character image is also for improving the compression. The resolution conversion unit A5354 and the resolution conversion unit B5355 may be about 75 dpi because the character image and the background image need not have the same resolution as the background image. When the bibliographic information includes a document containing only characters, a jpg file may be created with a resolution of 75 dpi for both the background image and the character image.

  The reason for reducing the resolution of characters is that the resolution of the characters is guaranteed by the MMR resolution, and even if the dpi (resolution) of the jpg image is reduced, the gradation is deteriorated but there is no problem. By reducing the resolution, the file size can be reduced. In this embodiment, the file size is reduced by reducing the image resolution. However, the file size may be reduced by reducing the image quality such as the number of gradations other than the image resolution. Since the bibliographic information in the stored data includes a description relating to the presence or absence of a text-only document, it is possible to increase the compression rate of the text-only document in the image data after the stored data.

  The image file composition unit 5358 outputs an output (MMR) from the binary image generation unit 5353, an output (MMR) from the black image generation unit 5352, an output (jpg) from the background image generation unit 5356, and a character. The four images with the output (jpg) from the image generation unit 5357 are combined into one file for file formation. The file format at this time may be a general-purpose format such as a PDF file.

The binarization unit 5351 performs binarization by extracting a plurality of feature amounts.
The following processes are sequential processes. When one process is completed, the adjacent pixel is processed. One line is processed from the beginning of the next line, and the process is continued at the end of the image. The RGB image data is black when the number is large and white when the number is small.
This will be described in more detail with reference to FIG.

1) Character resolution conversion Character edge area and color area signals that are decompressed by the compression / decompression processing unit 52 are subjected to resolution conversion (here, 300 dpi) at the same resolution as that applied to the image, and image data and pixel density Are the same. The output here is the character edge and color.

2) Binarization unit This unit includes an adaptive binarization unit that binarizes by changing a threshold value for each line, and an isolated point removal 1 that removes an isolated point from the output of adaptive binarization.

2-1) Adaptive binarization In order to extract characters on the color ground and characters on the white background, the edge color is detected and the threshold value is changed for each line. As shown in FIG. 8, the threshold calculation unit 81, the binarization unit 82, and the line memory 83 are configured.

2-1a) Threshold value calculation unit 81
FIG. 15 shows reference pixels for adaptive binarization. In FIG. 15, when the following conditional expression (1) is satisfied with the reference pixels Δ ▽ of the two left and right pixels with respect to the main scanning direction of the pixel of interest ○, it is determined as a binarization threshold target pixel. Note that th2 is a fixed value determined by the input characteristics of the pixel.
(○-▽)> th2 or (○-△)> th2 (1)
An average is obtained for each of the binarization target pixels in one line, and the average value is set as a threshold value. When there is no binarization target pixel in one line, a predetermined threshold value is set.

2-1b) Binarization unit 82
If even one RGB value in the input image RGB exceeds the threshold value with respect to the threshold value obtained by the threshold value calculation unit 81, it is determined as black (on), and when it is not black (on), white (off ) And output.

  Note that the adaptive binarization unit of this embodiment shown in FIG. 15 includes a line memory 83. This is because the processing is shifted by one line when it is attempted to binarize with the result calculated by the threshold value calculation unit 81, so that the line memory 83 delays one line so as not to shift the line. By changing the threshold value for each line, it is possible to satisfactorily extract characters on the ground and characters on the white without depending on the color of the background or background.

2-2) Isolated point removal 1
As a result of the adaptive binarization, since there are many isolated points, the isolated points are removed.
As shown in FIG. 16, when the patterns match, the isolated point is removed by inverting the target pixel.

3) Mask part 3-1) N-value conversion This N-value conversion is performed by N detection in halftone detection in 3-2) and 3-3) described later and gray detection in 3-4) and 3-5). The value is used in common.
Data with a small RGB difference (bk) is a black character when the value is greater than thabk, and the colors are divided into 6 hues of data YMCBGR with a small RGB difference, and threshold values (thay, tham, thac, thab, thag, thar). ), And binarization processing is performed. Binarization processing is performed using a dark color as an active pixel (character). The method of dividing the hue may be simply based on the magnitude relationship of RGB or may be determined by the ratio of RGB colors. This is determined by the characteristics of the input image. However, the output result is held for each hue. Here, it is defined as follows. The parentheses are bit display.
Dtah = 0 (000): Not applicable
Dtah = 1 (001): Yellow
Dtah = 2 (010): Magenta
Dtah = 3 (011): Red
Dtah = 4 (100): Cyan
Dtah = 5 (101): Green
Dtah = 6 (110): Blue
Dtah = 7 (111): Black

  Further, the white level is also binarized in the same manner. When the data with small RGB difference (bk) is smaller than thbbk, the color is divided into 6 hues of data YMCBGR with small RGB difference as white pixels, and the threshold value (thby, thbm, thbc, thbb, thbg) for each hue , Thbr), and binarization processing is performed, and binarization processing is performed with a light-colored pixel as an active pixel (white pixel). Moreover, what is contained in black and which is obtained by extracting a black (dark) color is used as a dark black and is used during black extraction.

  Further, background extraction is performed as background detection. The background is the same as that of the white level, but the threshold value is determined by using a white level, a character threshold value, and an intermediate value. FIG. 9 shows the relationship among the background area, gray area, and character area at this time.

  As shown in FIG. 9, there is a density region that extends over the two regions between the darker base region and the lighter gray region. The reason is that the area determination is not performed unless there is an area of a certain size by pattern matching in both the background area and the gray area. In this way, even if the density area of the uniform image in the vicinity of the gray determination is given to the background area and the gray area, if either the background area or the gray area is overlapped, This prevents the situation from falling into the area.

3-2) Halftone dot detection 1
In halftone dot detection 1 and halftone dot detection 2 described later, fine halftone dots have no halftone dot shape as a result of the smoothing process performed by the scanner correction unit. However, a rough halftone dot such as a photograph of a newspaper cannot be sufficiently smoothed, and a dot shape of the halftone dot remains, and the object is to detect this rough halftone dot.

Here, halftone dot pattern matching is performed. Here, when Dtah ≠ 0 defined in the above-described 3-1) N-value conversion is set as a black pixel, an N-value conversion white pixel is set as a white pixel.
FIG. 10 is a flowchart showing the halftone dot detection operation of the present embodiment.

First, it is determined whether the target pixel is a white pattern (step S101). Here, the white pattern is pattern matching of white pixels as shown in FIG. If the pattern is a white pattern (step S101 / Yes), the halftone dot count is initialized (step S102). If it is a white pattern area, the variables shown below are initialized, and the process proceeds to step S108 where non-halftone pixel processing is performed.
count_bk = tha_count
state = 0
SS [I] = 0
tha_count: Distance between white areas (threshold)
SS [I]: Information before one line

  On the other hand, when there is no white pattern (step S101 / No), next, a halftone dot determination process is performed (step S103). Actually, when SS [I] = 1, the result one pixel before is a halftone dot, and count_bk is 0 (1), sate is set to 1. Furthermore, in addition to (1), SS [I] is set to 1 when count_bk is 0.

After the halftone dot determination process, a halftone dot interval determination is performed (step S104). If state = 0 and count> tha_count_s, initialize the following variables:
count_bk = tha_count
SS [I] = 0
tha_count_s: Distance between halftone dot patterns on the non-halftone area (threshold)

Further, when any of count_bk, count_c, count_m, and count_y is 0 and count> tha_count_e, the following variables are initialized.
count_bk = tha_count
state = 0
SS [I] = 0
tha_count_e: Distance (threshold) between halftone dot patterns on non-halftone areas

  After the above determination is completed, count = count + 1 is performed.

  Next, a halftone dot count process for matching halftone dot patterns is performed (step S105). The halftone dot pattern is a pixel pattern as shown in FIG. 13, where ● represents a black pixel, and ◯ represents a non-black pixel. As a result of this collation, if the pattern matches, count is set to 0 and count_bk is set to -1.

  Here, a state determination process is performed to determine whether the dot is a halftone dot (step S106). The determination criterion at this time is the value of state. If state = 1, it is determined as a halftone dot (step S106 / Yes), and the process proceeds to fine line determination. On the other hand, when the state is not 1, the halftone dot is not determined (step S106 / No), the process proceeds to the non-halftone pixel processing (step S108), and the result is output as a non-halftone dot with state = 0. To do.

  On the other hand, as described above, when it is determined as a halftone dot in Step S106 (Step S106 / Yes), fine line determination processing is performed (Step S107). If the above-described white pattern exists on both sides of the pixel of interest (12 pixels) on both sides and count_x is an initial value, it is determined as a thin line and SS [I] = 0. Finally, halftone pixel processing is performed (step S109), and the result is output as a halftone dot with state = 1.

3-3) Halftone detection 2
In halftone detection 1, image data is processed in the forward direction, but in halftone detection 2, processing is performed in the reverse direction.
In the halftone dot detection 1, a portion where the tip of the halftone dot does not become a halftone dot is reversely read in the halftone dot detection 2 so as to become a halftone dot.

  By performing halftone dot detection 1 and halftone dot detection 2 in this manner, when a certain halftone dot pattern exists between the white pattern and the white pattern, it is detected as a halftone dot. Further, when the interval between the halftone dot pattern and the ruled dot pattern is wide, non-halftone dots are used, so that white characters formed in a dark background with black gradation are made non-halftone dots as shown in FIG. be able to. A dark background has almost no halftone dot shape and is a non-halftone dot. Further, even in the case of a dark character formed in a background with a light gradation, as shown in FIG. 21, there is almost no halftone dot shape and a non-halftone dot.

  Further, since the character is generally a white ground character formed on the white ground, the halftone dot pattern is only near the edge of the character, so that it is hardly detected erroneously. Further, the pattern matching of the present embodiment has been described by exemplifying the case of white and other than white. However, for example, the Y component, the M component, and the C component may be performed independently. If it develops to each component of Y, M, and C, since the ink components of printing are Y, M, and C, it becomes possible to accurately extract the ink dot reproduction.

3-4) Gray detection 1
In the gray detection 1 and the gray detection 2 described later, the character area is dark and the area around the character is thin, so that the density is lower than the character area and darker than the area around the character. Is determined as gray. The white background used in the gray determination is an N-valued white pixel.

FIG. 11 is a flowchart showing the gray pattern detection operation of the present embodiment. In FIG. 11, MS indicates the processing result of the previous pixel, and SS [i] indicates the processing result of the previous line.
First, as preprocessing, MS and SS [i] are compared, and a larger value is used among the processing result of the previous line and the processing result of the previous pixel (step S201). The value of MS is the number of white pixels after gray pattern detection described later.

  Next, a gray pattern matching process is performed on the target pixel to determine whether or not it matches the gray pattern (step S202). Note that the gray pattern is a pixel pattern as shown in FIG. 12. If the gray pattern matches the gray pattern (Yes in step S202), the process proceeds to step S207 in which the pixel is determined as a gray pixel.

  In this determination, if the medium density matches the gray pattern, it is determined as a gray image with MS = 5 and S [i]. This medium density refers to the case of Dtah = 0 and non-white pixels in the above-described 3-1) N-value conversion.

  If the target pixel does not match the gray pattern (step S202 / No), it is next determined whether it is a white pixel (step S203). Here, the white pixel means an N-valued white pixel. If the target pixel is not a white pixel (step S203 / No), the MS value is checked (step S204). If MS> 0 (step S204 / Yes), the result is output as the target pixel is a gray pixel. (Step S207). On the other hand, if MS> 0 is not satisfied (step S204 / No), the result is output as the target pixel being a non-gray pixel (step S208).

  Also, when the target pixel is a white pixel (step S203 / Yes), the MS value is checked (step S205). If MS> 0 (step S205 / Yes), the MS value is decremented by 1, and the process proceeds to step S204. On the other hand, if MS> 0 is not satisfied (step S205 / No), the result is output with the target pixel as a non-gray pixel (step S208).

  When the results are output from step S207 and step S208, post-processing is performed (step S209). As post-processing, SS [I] update processing is first performed. If the color background is white and MS> 1, perform SS [I] = MS-1. If it is a Bk pixel and MS> 0, SS [I] = MS−1 is performed.

  Also, bk count processing is performed. If the number of consecutive bk pixels is counted and the number of consecutive is greater than or equal to thg_count1, it is assumed that there are consecutive bk pixels. For example, when thg_count is 12 and the number of consecutive is N, bk pixels are continuous in N−thg_count + 1 times. When there are consecutive pixels, MS = MS-1 is performed.

3-5) Gray detection 2
In gray detection 1, image data is processed in the forward direction, but in gray detection 2, it is processed in the reverse direction.
A portion of the gray detection 1 where the tip of the gray area is not gray is grayed by processing in the reverse direction in the gray detection 2.

  The character portion is generally composed of dark data and light (white) data, and a medium-density block, which is a feature of a photograph not found in the character portion, is detected as gray. In the present embodiment, the peripheral pixels are gray pixels until the number of white pixels exceeds a certain value, so even a dark color is a gray pixel. However, if more than a predetermined number of blacks are continuous in the gray area, the pixel is set as a non-gray pixel. The result obtained in this manner is a gray pixel. As a result, it is possible to make a white character with a black background a non-gray area.

3-6) Background Detection When the threshold value is switched for each line by adaptive binarization, characters may be determined even in a thin area. In this case, there is no problem if all the thin areas are character-determined. However, if the image is in an area where the threshold is thin, the result of the binarization section has many black-and-white change points. The size will increase. If the lower limit value (white side) of the gray determination area is simply shifted to white, the character on the color ground cannot be determined, so the background is detected here.

  A 4 × 5 AND (logical product operation) is performed on the background, and then a 2 × 3 OR (logical sum operation) is performed. In this way, the background for the input data is reduced. Therefore, in the background around the character, the boundary between the character and the background is also the background, and since the background area is reduced, it is difficult to include the character in the background, so that the background can be detected satisfactorily.

5) Character determination + character determination 5-1) Character determination In FIG. 7, a character area (output from isolated point removal 1) and halftone dot areas 1 and 2 (output from halftone detection 1 and 2) If the character is not a gray region (output from gray detection 1 or 2), a background region (output from background detection), and is not a character (character determination result described later), it is determined as a character. .

  For the character area determination, logical operations are performed on the background area, halftone dot area, and gray area because the character determination result is originally a photo area that does not require resolution. Yes. In particular, the photographic region includes a large number of isolated points, and by performing this correction, the compression rate of the character image is improved, and the image is less mixed with characters and non-characters, so that the image quality can be improved.

  The reason why the character determination result is excluded from the character determination result is that black characters are output in a single black color, so that the character image is fixed and the compression rate is improved.

5-2) Judgment of character 5-2a) Judgment of character As shown in FIG. 17, the character judgment unit 171, the 3-line OR unit 172, the picture judgment unit 173, and the black judgment unit 174 , An extraction unit A175, an extraction unit B176, and two mirrors 177a and 177b.

  The character determination unit 171 performs a logical operation on the character determination result and the color determination result, which is the output result of the image area separation in the previous stage, and outputs a character with a black character edge if it is not a color. . The 3-line OR unit 172 ORs 3 lines × 1 pixel of the black character edge that is the result of character determination. Originally, instead of this 3-line OR, it is necessary to perform a 2-line delay after the extraction 1 to match the line delay with the extraction 2. However, if line delay is performed after extraction 1, it becomes necessary to delay the image data. Therefore, the line delay is absorbed by ORing three lines here.

  The pattern determination unit 173 includes a color determination result, which is an output result of the previous image area separation, a result of gray detection 1, a result of gray detection 2, a result of halftone detection 1, and a result of halftone detection 2. If any one of them is ON, it is determined as a picture. The black determination unit 174 determines black if the color determination result, which is the output result of the image area separation in the previous stage, is non-color and black (Bk or dark black) in N-value.

The extraction unit A175 extracts characters.
Here, the extraction operation for characters in the extraction unit A175 will be described with reference to FIG.
In the following description, it is assumed that the output of the 3-line OR unit 172 is a black character edge, the result of the pattern determination unit 173 is a pattern, and the result of the black determination unit 174 is black.

  First, when a character determination operation is started, a target pixel is determined (step S301). When it is determined that the character edge is a black character (step S301 / black character edge), the character is defined as a region. If it is determined that the pattern is a pattern (step S301 / pattern), the pattern area is set. Note that the character area and the picture area are not both turned on by the image area separation algorithm.

  If it is determined in step S301 that the target pixel is neither a black character edge nor a picture, a high density determination is performed (step S302). If the result of black pixel determination in the target line is not black (step S302 / No) ), The intermediate area. On the other hand, when the result of the black pixel determination is black (step S302 / Yes), the determination result of one line before is checked (step S303).

  If the determination result one line before the line segment processing is a pattern area (step S303 / pattern), the pattern area is determined. If the determination result of the previous line is not a picture area (step S303 / other than the picture), the determination result of the previous pixel is checked (step S304). Here, if the determination result of one pixel before is a picture area (step S304 / picture), it is set as a picture area. On the other hand, if the determination result of one pixel before is not a pattern area (step S304 / other than pattern), it is checked whether the determination one line before the line segment processing is a character area (step S305).

  If the determination result one line before the line segment processing is an area that is not a character (step S305 / character), it is determined to be an area that is a character. If the determination result one line before is not a character region (step S303 / other than character), the determination result one pixel before is checked (step S306). Here, if the determination result of one pixel before is a character area (step S306 / character), it is set as a picture area. On the other hand, if the determination result of one pixel before is not a character or a region (step S306 / other than a character), it is determined as an intermediate region.

  Thus, after it is determined that the area is a character area, a pattern area, or an intermediate area, line segment processing is finally performed. Here, if the color determination result is not a color and if there are 128 or more continuous high-density pixels, they are corrected as an intermediate region.

The extraction unit B 176 determines whether there is a character in the reverse image using the mirrors 177a and 177b.
Note that mirrors 177a and 177b are respectively arranged before and after the extraction unit B176 in order to realize processing with an inverse image by pipeline processing. Note that the operation of the extraction unit B 176 is the same as that of the extraction unit A 175, and thus description thereof is omitted.

  Then, in the determination unit 178, if both the output of the extraction unit A175 and the output of the mirror of the extraction unit B176 are characters, and the output from the binarization unit is a character, it is determined as a black character.

  In this way, it is possible to determine whether a character is in a large image area by referring to the state of the image of the surrounding pixels and determining whether the character is a character. The edge character area and color area can accurately detect colors and halftone dots in the read image, but if the smoothed data is used as density information for character detection, it is composed of halftone dots. There are few halftone dot areas for the characters, and they may not become edge character areas. Therefore, not the halftone dot information but the data after filtering (smoothed because it is not an edge character area), only the dark portion is set as the character.

  A halftone dot with a low screen line number, such as a photograph of a newspaper, is detected by halftone dot detection because a halftone dot shape remains even after smoothing. In addition, halftone dots with a high screen line number in general manuscripts such as catalogs are smoothed and the halftone dot shape is lost, and those with a dot area ratio of about 30% to 60% are detected as gray by gray judgment. To do. This is because, especially, the leading edge of the character is narrow, so that it is difficult to form a halftone dot (non-character area). This is to avoid odd results and unsightly results.

Next, the input format conversion unit will be described with reference to the drawings. FIG. 6 is a block diagram illustrating a configuration of the output format conversion unit 54.
The output format conversion unit 54 includes a TIF format expansion unit 541, a Jpg format expansion unit 542, a compression format expansion unit 543, and an output selection unit 544.

  The TIF format expansion unit 541, the Jpg format expansion unit 542, and the compression format expansion unit 543 have a function of expanding each format into a bitmap, and the output selection unit 544 has one of the above three formats. Select and convert RGB data to YMCBk simultaneously with output. That is, if the input image data is in the TIF format, the TIF format development unit develops it with bitmap data. If it is Jpg format, it will be expanded with bitmap data in Jpg format expansion part. Furthermore, if it is a compression format, it expand | deploys in a compression format expansion | deployment part.

Here, the compression format expansion unit 543, which is a main part of the present embodiment, will be described.
The compression format expansion unit 543 includes an image file expansion unit 5431, a black image expansion unit 5432, a binary image expansion unit 5433, a background image expansion unit 5434, a character image expansion unit 5435, and an image file composition unit 5436. I have.

  In the image file development unit 5431, four files among the files generated by the compression format generation unit 535 in FIG. 5 are converted into a black image development unit 5432, a binary image development unit 5433, a background image development unit 5434, and a character image development unit. Image data corresponding to 5435 is output. The black image expansion unit 5432 expands the MMR to expand it into a bitmap, the binary image expansion unit 5433 expands the MMR into a bitmap, and the background image expansion unit 5434 converts the background image JPG into a bitmap. In addition, the character image expansion unit 5435 expands each JPG of the character image into a bitmap. The developed four bitmap data are synthesized into one piece of bitmap data by the image file synthesis unit 5436.

  In the image file development unit 5431, if the output of the binary image development unit 5433 is a character region, the image data output from the character image development unit 5435 is output, and the output of the binary image development unit 5433 is a non-character region. If there is, the image data that is the output of the background image development unit 5434 is output. Further, if the output of the black image development unit 5432 is a black character, it is output in black. In this way, one image is generated. Note that the resolution of characters and non-characters is the resolution of the binary image. FIG. 19 shows an image diagram at this time.

  In FIG. 19, the characters “disc top” that is black characters, the characters “new sale” that is red characters, and the PC image that is the background image (pattern) are input as input images. The input images are stored as “Disctop” as a black character image, “Newly released” (red) as a character image, “Newly released” (black) as a binary image, and PC design as a background image. Is done. When this image is output to the outside, the black character image, the character image, the binary image, and the background image are combined and output.

  The present embodiment can be used in a system that realizes the above-described embodiment, or can be provided as software stored in a computer-readable storage medium.

As described above, according to the image processing apparatus, the image transmission apparatus, the image forming apparatus, the program, and the recording medium of the present embodiment, in order to detect a photograph (natural image), a gray area is determined by gray pattern matching of a medium density block. By detecting, if a predetermined number or more of a specific color pixel (black) continues, it is regarded as equivalent to a white pixel, and by measuring the white pixel, it becomes a gray pixel (photograph pixel) until the predetermined number or more is reached. Thus, it is possible to perform character determination (non-pattern determination) for white characters on a specific color pixel (black).
Further, it is possible to improve the compression rate by correcting the determination of a gray pixel as a non-character.

Further, in order to detect a halftone dot, a white area is detected by white pixel pattern matching, an isolated dot between the white area and the white area is measured, and if there are a predetermined number or more, a halftone dot is obtained. If the distance between the isolated dots is wide, the measured value is initialized (0), so that the background on a dark background such as a gradation of a specific color (black) or a character on a light background such as a gradation is made non-character. The compression rate can be improved.
Further, the compression rate can be improved by correcting the character determined to be a halftone dot as a non-character.

  Furthermore, it can be provided as an image forming device such as a scanner distribution device or a copying machine, or provided as software, so that it is possible to perform compression with a high compression rate by detecting a non-character area and reduce the file size. The image processing apparatus, the image transmission apparatus, the image forming apparatus, the program, and the recording medium of the embodiment can be provided.

It is a block diagram which shows the image processing apparatus of this embodiment. It is a block diagram which shows the structure of the scanner correction | amendment part of this embodiment. It is a block diagram which shows the structure of the printer correction | amendment part of this embodiment. It is a block diagram which shows the structure of the controller of this embodiment. It is a block diagram which shows the structure of the output format conversion part of this embodiment. It is a block diagram which shows the structure of the input format conversion part of this embodiment. It is a block diagram which shows the structure of the binarization part of this embodiment. It is a block diagram which shows the structure of the adaptive binarization part of this embodiment. It is a conceptual diagram of a ground area, a gray area, and a character area. It is a flowchart which shows the halftone detection operation | movement of this embodiment. It is a flowchart which shows the gray pattern detection operation | movement of this embodiment. It is a figure which shows the gray pattern of this embodiment. It is a figure which shows the halftone dot pattern of this embodiment. It is a figure which shows the white pattern of this embodiment. It is a figure which shows the reference pixel of the adaptive binarization of this embodiment. It is a figure which shows the pixel pattern of the isolated point removal of this embodiment. It is a flowchart which shows the character determination operation | movement of this embodiment. It is a flowchart which shows operation | movement in extraction part A175 of determination operation | movement in the character of this embodiment. It is a figure which shows typically the input image of this embodiment, a file image, and an output image. It is a figure which shows an example of an outline character. It is a figure which shows an example at the time of forming a dark character in the background of a light gradation.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Color image processing apparatus 2 Scanner 3 Scanner correction | amendment part 4 Compression processing part 5 Controller 6 HDD
7 NIC
8 Decompression processing section 9 Printer correction section 10 Plotter

Claims (3)

An image processing apparatus for detecting a character area from input image data,
For each of the N types of colors, a first binarization process is performed in which each pixel of the image data has a dark color as an active pixel, and an output result is held for each of the N types of colors.
N-value conversion means for performing a second binarization process for determining whether each pixel of the image data is a white pixel by binarizing at a white level;
Gray region detecting means for sequentially processing each pixel of the image data for each line and determining whether each pixel is a gray pixel or a non-gray pixel;
The gray area detecting means includes
Determining that the pixel of interest is a gray pixel until pixels determined to be white pixels by the second binarization process continue beyond the first number;
In addition, when the pixel determined to be a black active pixel among the N types of colors by the first binarization process continues beyond the second number, the target pixel is a non-gray pixel. As a result of determining that there is,
The pixels that are gray pixel is detected as a gray area,
further,
An image processing apparatus comprising: a character area detecting unit that determines that the gray area detected by the gray area detecting unit is not a character area. Each pixel of the image data is sequentially processed for each line, a halftone dot pattern is detected from the image data, a region where the halftone dot pattern is detected is a halftone dot region, a halftone dot pattern and a halftone dot pattern Having a halftone dot detecting means for judging that the area is not halftone when the interval is wide;
The image processing apparatus according to claim 1, wherein the character area detecting unit determines that the halftone dot area detected by the halftone dot detecting unit is not a character area. A program for causing a computer to execute image processing for detecting a character area from input image data,
In the computer,
A first binarization process in which each pixel of the image data for each of N types of colors has a dark color as an active pixel;
A process of holding an output result for each of the N colors;
A second binarization process for binarizing each pixel of the image data at a white level;
Gray region detection processing for determining whether each pixel is a gray pixel or a non-gray pixel by sequential processing for each line of each pixel of the image data;
A character area detection process for determining that the gray area detected by the gray area detection process is not a character area; and
The gray area detection process includes:
Determining that the pixel of interest is a gray pixel until pixels determined to be white pixels by the second binarization process continue beyond the first number;
In addition, when the pixel determined to be a black active pixel among the N types of colors by the first binarization process continues beyond the second number, the target pixel is a non-gray pixel. As a result of determining that there is,
A program for detecting a pixel that has become a gray pixel as a gray region.

Images