JP4584805B2 - Image processing apparatus, image processing method, and image processing program - Google Patents

Description

The present invention relates to an image processing apparatus, an image processing method, and an image processing program , and more particularly to determination of a document color type in a document image compression process.

  When a document image is handled, the data size may be a problem. For example, when storing a large amount of document images, the larger the data size per image, the smaller the number of images that can be stored in a certain storage area. In addition, when a document image is attached to an e-mail and distributed, the larger the image data size, the higher the load on the network, and the storage capacity of the mail receiving box at the distribution destination.

  Image data compression methods such as JPEG (Joint Photographic Coding Experts Group) are known as data size reduction means for color images. However, the amount of size reduction while maintaining image quality that does not affect the readability of the document There is a limit.

  In Patent Documents 1 and 2, two multi-value image data with high compression efficiency and binary data with high resolution of reversible compression are provided in one file, and two multi-value image data are binary with high resolution. A technology that enables image files with high compression efficiency to be created while the resolution of characters is high by selectively switching images based on data (character area) so that the edges of characters are output in binary resolution. Is disclosed. However, in the case of a monochrome original only with characters, two pieces of multi-valued image data are unnecessary, and compression efficiency is lowered.

  On the other hand, a method such as MMR (Modified Modified READ (Relative Element ADdress)) compression is known as a data size reduction means for a binary image. Many of the paper originals from which the document image is based are two-color originals (for example, black and white) having a background color corresponding to the paper color and a foreground color corresponding to the character color. Therefore, for a two-color document, the image data size is generally much smaller when the MMR compression is handled as a binary image than when the JPEG compression is handled as a color image.

Therefore, in Patent Document 3, it is determined whether the input document is color or monochrome, and the compression method is switched according to the result. In Patent Documents 4 to 7, a color original or a monochrome original is discriminated, and the printing means for paper is changed according to the result.
JP 2002-368986 A Japanese Patent No. 3193086 Japanese Patent No. 2791314 Japanese Examined Patent Publication No. 6-14213 Japanese Patent Laid-Open No. 2002-10094 JP-A-10-155076 JP-A-8-65530

  As described above, in Patent Document 3, it is determined whether the input document is color or monochrome, and the compression method is switched according to the result. In this case, it is determined whether the document is superficially monochrome or color. However, a two-color document other than black and white, for example, a document printed using colored paper, is treated as a color document. Therefore, such a two-color document other than black and white is handled as a color document, and MMR compression with high compression efficiency cannot be used. Therefore, there is a problem that effective compression processing cannot be performed. There are several techniques for identifying the document type, such as Patent Documents 4 to 7, but none of them considers the compression efficiency.

The present invention has been proposed in view of the above-described conventional problems, and the object of the present invention is to provide a wide range of two-color originals including originals printed using colored paper, and the like. An object of the present invention is to provide an image processing apparatus, an image processing method, and an image processing program that can be classified into other color originals and can select an appropriate compression method according to the classification result.

In order to solve the above-described problem, in the present invention, as described in claim 1, the G component value of the RGB components of each pixel on the color image is compared with a predetermined threshold value to obtain two values. The color generation frequency is 1 for the pixel belonging to the first category classified by the category classification means for classifying each pixel on the color image into two categories by the value conversion. A first color number calculating means for calculating the first color number as 1 when concentrated on colors, and a first color number calculating means for calculating the first color number as 2 or more in other cases; For the pixels belonging to the second category classified by the above, the second number of colors is calculated as 1 when the frequency of color occurrence is concentrated in one color, and in the other cases A second color number calculating means for calculating the number of colors to be 2 or more, the first color number and the previous When both of the second colors are 1, it is determined that the original color type of the color image is a two-color original, and in other cases, an original color type determining unit that determines that the original is a multi-color original. The gist is an image processing apparatus.

Further, as described in claim 2, the image processing apparatus according to claim 1, wherein the categorization means may be one that includes a process to remove pixels corresponding to the boundary portion of the categories from the classification target.

According to a third aspect of the present invention, in the image processing device according to the second aspect , the pixel corresponding to the boundary portion of the category may be a character outline pixel.

Further, according to a fourth aspect of the present invention, in the image processing apparatus according to any one of the first to third aspects, the original color type determining means is a dark and light original in which the color image is composed of light and shades of similar colors. Or a process for determining whether the foreground and the background are two-color originals each having one color.

In addition, as described in claim 5 , in the image processing apparatus according to any one of claims 1 to 4 , one of the first color number calculation unit and the second color number calculation unit or Both can include a smoothing process that divides the color image into sub-regions and targets each pixel in the sub-region belonging to the category in each sub-region.

In addition, as described in claim 6 , in the image processing apparatus according to claim 5 , the division into the sub-regions can be performed except for a peripheral portion of the image.

In addition, as described in claim 7, each pixel on the color image is binarized by comparing the value of the G component of the RGB components of each pixel on the color image with a predetermined threshold value. For the pixels belonging to the classified first category, and when the color occurrence frequency is concentrated in one color, the first color number is calculated as 1, In other cases, the step of calculating the number of first colors as 2 or more and the case where the color occurrence frequency is concentrated on one color for the pixels belonging to the classified second category are the first. The number of colors of 2 is calculated as 1; otherwise, the step of calculating the number of second colors as 2 or more, and when both the first number of colors and the second number of colors are 1, The original color type of the color image is determined to be a two-color original, otherwise it is a multi-color original. It can be configured as an image processing method comprising the steps of: a constant.

In addition, as described in claim 8 , in the image processing method according to claim 7 , the step of classifying each pixel on the input color image into two categories includes a pixel corresponding to a boundary portion of the category. It can include a process of removing from the classification target.

In addition, as described in claim 9 , in the image processing method according to claim 8 , the pixel corresponding to the boundary portion of the category may be a character outline pixel.

In addition, as described in claim 10 , in the image processing method according to any one of claims 7 to 9 , in the step of determining the document color type, the color image is composed of shades of similar colors. It is possible to include a process for determining whether the original is a gray original or a two-color original consisting of one foreground and one background.

In addition, as described in claim 11 , in the image processing method according to any one of claims 7 to 10 , the step of calculating the first number of colors and the number of second colors are calculated. One or both of the steps may include a smoothing process that divides the color image into sub-regions and targets each pixel in the sub-region belonging to the category in each sub-region.

In addition, as described in claim 12 , in the image processing method according to claim 11 , the division into the sub-regions can be performed except for a peripheral portion of the image.

Further, as described in claim 13 , it is possible to configure as an image processing program for executing each step described in any one of claims 7 to 12 on a computer.

In the image processing apparatus, the image processing method, and the image processing program of the present invention, the input image is a two-color original for the input of various two-color originals including an original printed on colored paper. Can be determined. Furthermore, by configuring an appropriate output image according to the original color type, the data size can be efficiently reduced.

  Preferred embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a diagram illustrating a configuration example of an image processing apparatus according to the present invention. In FIG. 1, an image processing apparatus 1 includes a color image buffer 11 for storing color image data, a binary image buffer 12 for storing binarized binary image data created in the process, and an original document. A color image input unit 13 comprising a scanner or the like for converting from color to image data, an original color type determining unit 14 for determining the original color type of the color image, and an output for determining an output image configuration method based on the original color type An image configuration method determining unit 15 and an output image configuration unit 16 that configures an output image by the determined method are provided. In operation, the color image input unit 13 converts the original document into color image data, and stores the color image in the color image buffer 11. The document color type determination unit 14 creates binary image data in the course of processing, and stores the binary image data in the binary image buffer 12. Then, the document color type determination unit 14 determines the document color type of the color image, the output image configuration method determination unit 15 determines the output image configuration method based on the document color type, and the output image configuration unit 16 is determined. The output image is constructed by the method described above, and the output image is output therefrom.

  FIG. 2 is a diagram illustrating a configuration example of the document color type determination unit 14. In FIG. 2, the document color type determination unit 14 is based on the binarization unit 141 that binarizes the color image data on the color image buffer 11, and the contents on the color image buffer 11 and the binary image buffer 12. A background color number calculation unit 142 that calculates the number of colors, a foreground color number calculation unit 143 that calculates the number of foreground colors based on the contents on the color image buffer 11 and the binary image buffer 12, and the number of background colors and the number of foreground colors A document color type determination unit 144 that determines the document color type of the input image. In operation, the binarization unit 141 binarizes the color image data on the color image buffer 11 and stores the binary image data in the binary image buffer 12. The background color number calculation unit 142 calculates the number of background colors based on the contents of the color image buffer 11 and the binary image buffer 12, and similarly, the foreground color number calculation unit 143 calculates the foreground color number. Then, the document color type determination unit 144 determines the document color type of the input image from the number of background colors and the number of foreground colors, and outputs the document color type. FIG. 3 is a diagram illustrating a hardware configuration example of the image processing apparatus 1. In FIG. 3, the image processing apparatus 1 includes a CPU 101, a memory 102, a hard disk 103, a communication device 104, a scanner 105, a display 106, a keyboard 107, and a CD-ROM drive 108. A program for executing the processing of the present invention is stored in the hard disk 103 in the image processing apparatus 1 via a recording medium such as the CD-ROM 109 or a network via the communication apparatus 104. When the execution of the program is instructed, the program code and other necessary resources are loaded onto the memory 102, and the program is executed by the CPU 101 in accordance with the described contents. The input image is loaded onto the memory 102 directly or temporarily stored in the hard disk 103 via a network via the recording medium such as the scanner 105 or the CD-ROM 109 or the communication device 104. The execution result of the program is output to the display 106, stored in the hard disk 103, or transmitted to the network via the communication device 104.

  Hereinafter, processing contents of the present invention will be described.

<First Embodiment>
FIG. 4 is a flowchart showing document color type determination processing according to the first embodiment. In the following, an example of determining whether an input image is a two-color original composed of one foreground color and one background color or not is described with reference to FIG.

Now, assuming that a color digital image composed of RGB (Red. Green, Blue) components each having a pixel value in the range of 0 (zero luminance) to 255 (maximum luminance) is input, first the G component of the input image is fixed. A binary image is created by comparison with the threshold value “110” (step S101). That is,
G ≦ 110 → black pixel G> 110 → white pixel. This binarization method is merely an example, and the threshold value may be dynamically determined using a known discriminant analysis method or the like.

  As a result of the binarization, pixels on the input image are classified into two categories of black (foreground) / white (background).

Subsequently, the number of background colors is determined for the pixel on the input image corresponding to the white pixel of the obtained binary image (step S102). Here, each component of RGB is quantized in three stages to obtain corresponding indexes (R _i , G _i , B _i ). That is,
R _i = R * 3/256
G _i = G * 3/256
B _i = B * 3/256
And

If both are rounded down, the possible index values are
0 ≦ R _i ≦ 2
0 ≦ G _i ≦ 2
0 ≦ B _i ≦ 2
An integer in the range of.

It is possible to obtain the distribution f _B (R _i , G _i , B _i ) of the occurrence frequency of the index (R _i , G _i , B _i ) for the pixels on the input image corresponding to the white pixels of the binary image. If a majority of the frequencies are concentrated on the index corresponding to the background color, it is determined that the background is one color, and if not, the background is two or more colors. That is,
(1) For one index (x, y, z)
f _B (x, y, z)> 0.5 * Σ [R _i = 0,1,2] Σ [G _i = 0,1,2] Σ [B _i = 0,1,2] f _B (Ri, Gi, Bi)
If this holds, the number of background colors = 1
(2) If the above (1) is not met, the number of background colors is 2 or more.

Similarly, the distribution f _F (R _i , G _i , B _i ) of the occurrence frequency of the index (R _i , G _i , B _i ) is targeted for the pixel on the input image corresponding to the black pixel of the binary image. Can be sought. If the majority of the frequencies are concentrated in the index corresponding to the foreground color, it is determined that the foreground color is one color, and if not, the foreground color is determined to be two or more colors. That is,
(1) For one index (x, y, z)
f _F (x, y, z)> 0.5 * Σ [R _i = 0,1,2] Σ [G _i = 0,1,2] Σ [B _i = 0,1,2] f _F (R _i , G _i , B _i )
If foreground color number = 1
(2) If the above (1) is not satisfied, the number of foreground colors is set to 2 or more (step S103).

After obtaining the number of background colors and the number of foreground colors in this way, the document color type is determined as follows (step S104).
(1) If the number of foreground colors = 1 and the number of background colors = 1, a two-color document (step S105)
(2) If the above (1) is not met, the multicolor document (step S106)
In this way, by determining the number of colors for the foreground and the background separately, it is possible to more accurately determine the document color type without confusing each other's color distribution.

<Second Embodiment>
FIG. 5 is a flowchart showing document color type determination processing according to the second embodiment. Since it is almost the same as the first embodiment described above, only the difference from the first embodiment will be described.

  The difference from the first embodiment is that after creating a binary image from an input color image (step S201), before calculating the number of background colors and the number of foreground colors (steps S203 and S204), black pixels / white pixels Is a thickening process (step S202).

  Regardless of the document color type, the pixel value generally changes in steps over several pixels from the foreground to the background as shown in FIG. 6 near the outline of the character pattern included in the color image. For this reason, if the pixel value of the character outline part is included in the calculation target of the number of background colors and the number of foreground colors, the occurrence frequency distribution of the RGB index extends over a wide range, which is a cause of misidentifying a two-color document as multicolor. .

  Therefore, for example, after a binary image as shown in FIG. 7A is obtained, a process of replacing a 3 × 3 pixel range with a black pixel around each black pixel on the binary image is performed. A black pixel thickening processing result image as shown in (b) is obtained. Similarly, processing for replacing the 3 × 3 pixel range with white pixels is performed around each white pixel on the binary image to obtain a white pixel thickening processing result image as shown in FIG.

  The white pixel portion in the black pixel thickening processing result is set as the background region, and the black pixel portion in the white pixel thickening processing result is set as the foreground region. Character outline pixels that fall under the boundary between the foreground region and the background region, which do not correspond to any of them, are not classified.

  In the subsequent background color number calculation in FIG. 5 (step S203), pixels belonging to the background area (inside the thick black line in FIG. 7D) are targeted, and in the foreground color number calculation (step S204), A pixel belonging to the foreground area (within the white thick line in FIG. 7E) is targeted. In this way, it is possible to reduce the influence of the character outline portion.

<Third Embodiment>
FIG. 8 is a flowchart showing document color type determination processing according to the third embodiment.

  The steps up to the step of creating a binary image from the input color image (step S301) and calculating the number of background colors and the number of foreground colors (steps S302 and S303) are the same as those in the first embodiment. I will omit the explanation.

Even if the number of foreground colors and the number of background colors are both 1, if the original is a gray scale with intermediate brightness, it is practically uncomfortable to classify it as a two-color original with foreground = black and background = white. There may be. Therefore, after obtaining the number of background colors and the number of foreground colors, the original color type is primarily determined as follows (step S304).
(1) If the number of foreground colors = 1 and the number of background colors = 1, a two-color original or a dark original
(2) If the above (1) does not apply, multicolor original
If the condition corresponds to (2), the result is confirmed as a multicolor original (step S305). If the condition corresponds to (1), the process proceeds to the following secondary determination.

For each pixel on the color image corresponding to the black pixel of the binary image, the occurrence frequency distribution of the index G _i related to the G component described above is obtained as the foreground luminance distribution I _F (G _i ) (step S306).

Similarly, the background luminance distribution I _B (G _i ) is obtained for each pixel on the color image corresponding to the white pixel of the binary image (step S307). Then, an overall luminance distribution I (Gi) is obtained by superimposing the foreground luminance distribution and the background luminance distribution (step S308). That is,
I (G _i ) = I _F (G _i ) + I _B (G _i ) (G _i = 0,1,2)
And

If a majority of the frequencies are concentrated on I (1) corresponding to the intermediate luminance, it is determined that the original is a light and dark original, and if not, it is determined as a two-color original (step S309). That is,
(1) If I (1)> I (0) + I (2) is satisfied, the dark and light original (step S310)
(2) If I (1) ≦ I (0) + I (2) holds, a two-color original (step S311)
And

  As a result, the input image can be classified into a multicolor original, a dark original, and a two-color original, and a more detailed original color type can be obtained.

<Fourth Embodiment>
FIG. 9 is a flowchart showing document color type determination processing according to the fourth embodiment. Since it is almost the same as the first embodiment described above, only the difference from the first embodiment will be described.

  The difference from the first embodiment is that after a binary image is created from an input color image (step S401), the color image is smoothed before calculating the number of background colors and the number of foreground colors (steps S403 and S404). The process (step S402) is performed.

  As a smoothing process, first, a color image is divided into sub-regions every 8 × 8 pixels. At that time, the width corresponding to 30 pixels in the peripheral portion of the image is removed. In FIG. 10, sub-region division is performed starting from the lower left except for the 30 pixels in the peripheral portion. Depending on the image size, the width / height of the division at the right end or upper end of the division may be less than 8 pixels.

  When a colored paper document is read by a scanner, white and black noise areas are formed at the peripheral edge due to punch holes as shown in FIG. 11A and inclination / deviation of the document during scanning as shown in FIG. May appear and contribute to misidentifying the original color type. Therefore, by removing the peripheral portion from the sub-region division target, it is made difficult to be affected by these noises.

For each sub-region, the RGB pixel values of the pixel i on the sub-region k corresponding to the white pixel (background) of the binary image are represented by (R (k, i), G (k, i), B (k , i)), the average pixel value (R _mean (k), G _mean (k), B _mean (k)) of the sub-region k / background equivalent portion is obtained. That is,
R _mean (k) = Σ [i] R (k, i) / Σ [i] 1
G _mean (k) = Σ [i] G (k, i) / Σ [i] 1
B _mean (k) = Σ [i] B (k, i) / Σ [i] 1
And

Then, all pixel values in the sub-region k / background equivalent portion are replaced with the average pixel value. That is,
R (k, i) ← R _mean (k)
G (k, i) ← G _mean (k)
B (k, i) ← B _mean (k)
And

Similarly, all pixel values on the sub-region k corresponding to the black pixels (foreground) of the binary image are replaced with the average pixel values of the sub-region k and the foreground equivalent portion. That is, j is each pixel corresponding to a black pixel on the binary image,
R (k, j) ← Σ [j] R (k, j) / Σ [j] 1
G (k, j) ← Σ [j] G (k, j) / Σ [j] 1
B (k, j) ← Σ [j] B (k, j) / Σ [j] 1
And

  After performing the smoothing process for each sub-region in this way, the number of background colors and the number of foreground colors are calculated.

  The distribution of the color components of the color image is determined by the fluctuation of the pixel value for each pixel that occurs during scanning and the change in the pixel value for each pixel that occurs when the color image is irreversibly compressed (for example, stored in JPEG format) It becomes wider than the actual situation. That is, the occurrence frequency distribution of the RGB index extends over a wide range, which is a cause of misidentifying a two-color document as multicolor.

  By performing smoothing processing in units of sub-regions, the foreground color and background color are locally unified, and the spread of the color component distribution resulting from pixel value fluctuation and change for each pixel is suppressed. The risk of misidentifying as multicolor can be reduced.

<Fifth Embodiment>
FIG. 12 is a flowchart showing output image composition processing according to the document color type according to the fifth embodiment. In the case of a two-color manuscript, it is better to store the input color image with appropriate compression as a binary image consisting of the foreground color = ON bit and the background color = OFF bit, rather than storing it as a full color image as it is Since the size is much smaller, when it is determined that the document is a two-color document, the foreground color information and the background color information are obtained and then MMR compression is performed as a binary image.

  In FIG. 12, after inputting a color image (step S501), the document color type is determined (step S502). The document color type is determined using the method described in the first to fourth embodiments.

  It is determined whether the document color type is a two-color document (step S503). If the result of determination is that the document is not a two-color document (multi-color document or dark document), the input image is directly subjected to JPEG compression and output as a full-color image. (Step S504).

  On the other hand, if the determination result is a two-color document, first, a binary image is created from the input image (step S505). Here, it is possible to reuse a binary image that has already been created in the document color type determination process.

Subsequently, the foreground average pixel value is obtained for each pixel on the color image corresponding to the black pixel of the binary image (step S506). That is, let i be each pixel corresponding to a black pixel on a binary image,
R _F-mean = Σ [i] R (i) / Σ [i] 1
G _F-mean = Σ [i] G (i) / Σ [i] 1
B _F-mean = Σ [i] B (i) / Σ [i] 1
And

  Then, the obtained foreground average pixel value is output as foreground color information (step S507).

Similarly, a background average pixel value is obtained for each pixel on the color image corresponding to the white pixel of the binary image (step S508). That is, j is each pixel corresponding to a white pixel on the binary image,
R _B-mean = Σ [j] R (j) / Σ [j] 1
G _B-mean = Σ [j] G (j) / Σ [j] 1
B _B-mean = Σ [j] B (j) / Σ [j] 1
And

  The obtained background average pixel value is output as background color information (step S509).

  Finally, the binary image is output after being MMR compressed (step S510).

  In general, if derived from the same color image, the data size of the former is much smaller between the binary image compressed by MMR and the full color image compressed by JPEG. Since the foreground color information and the background color information are two sets of RGB component values, the data is several bytes to about several tens of bytes. Therefore, in the case of a two-color document, the data size can be effectively reduced if the configuration is foreground / background color information + MMR compressed binary image.

  Note that PDF (Portable Document Format) (PDF is a trademark of Adobe) is known as a file format that allows foreground information + background color information + MMR binary image to be configured. When the file is browsed with an existing viewer, a two-color image to which the ON bit = foreground color and OFF bit = background color of the binary image are assigned is displayed.

<Sixth Embodiment>
FIG. 13 is a flowchart showing output image configuration processing according to the document color type according to the sixth embodiment. In the sixth embodiment, when the above-described fifth embodiment is executed, if the document is not a two-color document (a multi-color document or a dark document), the image is separated into a plurality of layers and compressed individually. Then, the file size can be made smaller than by simply compressing with JPEG.

  A case where it is determined that the document is not a two-color original in the processing flow of FIG. 13 will be described, and this embodiment will be described.

  As a result of the document type determination (step S603), if the document is not a two-color document (multi-color document or dark document), the image is composed of three layers (first multi-value image, second multi-value image, binary image) as shown in FIG. (Step S604). A specific method is described in detail in a patent application already filed by the present applicant (Japanese Patent Application No. 2004-358532).

  As a result, as shown in FIG. 14, the image is divided into two multi-value images and one binary image. Then, they are individually compressed and encoded into a form that can be superimposed and displayed (step S605). As a form capable of such expression, there is the PDF format described above.

  The generation of the separated image (step S604) may be divided into four layers as in another patent application (Japanese Patent Application No. 2005-024188) of the present applicant.

  As a result, even when the document is not a two-color document, the file size can be made smaller than when simply compressing with JPEG.

  The present invention has been described above by the preferred embodiments of the present invention. While the invention has been described with reference to specific embodiments, various modifications and changes may be made to the embodiments without departing from the broad spirit and scope of the invention as defined in the claims. Obviously you can. In other words, the present invention should not be construed as being limited by the details of the specific examples and the accompanying drawings.

It is a figure which shows the structural example of the image processing apparatus of this invention. 6 is a diagram illustrating a configuration example of a document color type determination unit. FIG. It is a figure which shows the hardware structural example of an image processing apparatus. 6 is a flowchart illustrating document color type determination processing according to the first embodiment. 10 is a flowchart illustrating document color type determination processing according to the second embodiment. It is a figure which shows the example of the pixel of the character pattern outline part vicinity. It is a figure which shows the example of the thickening process of a black pixel / white pixel. 10 is a flowchart illustrating document color type determination processing according to the third embodiment. 10 is a flowchart illustrating document color type determination processing according to a fourth embodiment. It is a figure which shows the example of the sub area | region division | segmentation of a color image. It is a figure which shows the example of the noise seen by the image peripheral part. 10 is a flowchart illustrating output image configuration processing according to a document color type according to a fifth embodiment. It is a flowchart which shows the output image structure process according to the document color classification concerning 6th Embodiment. It is a figure which shows the example of a separated image generation.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image processing apparatus 11 Color image buffer 12 Binary image buffer 13 Color image input part 14 Original color type determination part 141 Binarization part 142 Background color number calculation part 143 Foreground color number calculation part 144 Original color type determination part 15 Output image Configuration method determination unit 16 Output image configuration unit 101 CPU
102 Memory 103 Hard Disk 104 Communication Device 105 Scanner 106 Display 107 Keyboard 108 CD-ROM Drive 109 CD-ROM

Claims (13)

Category classification means for classifying each pixel on the color image into two categories by comparing the G component value of the RGB component of each pixel on the color image with a predetermined threshold value,
For pixels belonging to the first category classified by the category classification means, the first color number is calculated as 1 when the frequency of color occurrence is concentrated in one color, and in other cases Is a first color number calculating means for calculating the first color number to be 2 or more;
For the pixels belonging to the second category classified by the category classification means, the second color number is calculated as 1 when the frequency of color occurrence is concentrated in one color, and in other cases A second color number calculating means for calculating the second color number as 2 or more;
When both the first color number and the second color number are 1, it is determined that the original color type of the color image is a two-color original, and in other cases, it is determined that the original is a multi-color original. An image processing apparatus comprising: an original color type determining unit. The image processing apparatus according to claim 1.
The image processing apparatus according to claim 1, wherein the category classification unit includes a process of excluding a pixel corresponding to a category boundary from a classification target. The image processing apparatus according to claim 2,
The image processing apparatus according to claim 1, wherein a pixel corresponding to a boundary portion of the category is a character outline pixel. In the image processing device according to any one of claims 1 to 3,
The document color type determination unit includes a process of determining whether the color image is a light / dark document composed of shades of similar colors or a two-color document composed of one foreground and one background. Image processing device. In the image processing device according to any one of claims 1 to 4,
One or both of the first color number calculation unit and the second color number calculation unit divide the color image into sub-regions, and target each pixel in the sub-region belonging to the category in each sub-region. An image processing apparatus including the smoothing process described above. The image processing apparatus according to claim 5.
The image processing apparatus according to claim 1, wherein the division into the sub-regions is performed except for a peripheral portion of the image. Classifying each pixel on the color image into two categories by comparing the G component value of the RGB component of each pixel on the color image with a predetermined threshold and binarizing;
For the pixels belonging to the classified first category, the first color number is calculated as 1 when the color occurrence frequency is concentrated in one color, and the first color in other cases. Calculating the number as 2 or more;
For pixels belonging to the classified second category, the second color number is calculated as 1 when the color occurrence frequency is concentrated in one color, and the second color in other cases. Calculating the number as 2 or more;
When both the first color number and the second color number are 1, it is determined that the original color type of the color image is a two-color original, and in other cases, it is determined that the original is a multi-color original. An image processing method comprising: a step. The image processing method according to claim 7.
The step of classifying each pixel on the input color image into two categories includes a process of excluding a pixel corresponding to a boundary portion of the category from a classification target. The image processing method according to claim 8.
A pixel corresponding to a boundary portion of the category is a character outline pixel. The image processing method according to any one of claims 7 to 9,
The step of determining the color type of the document includes a process of determining whether the color image is a light / dark document composed of shades of similar colors or a two-color document composed of one color for each of the foreground and the background. An image processing method. In the image processing method according to any one of claims 7 to 10,
One or both of the step of calculating the first number of colors and the step of calculating the second number of colors divide the color image into sub-regions, and in each sub-region, within the sub-region belonging to the category An image processing method comprising a smoothing process for each pixel. The image processing method according to claim 11.
An image processing method according to claim 1, wherein the division into the sub-regions is performed excluding a peripheral portion of the image.   An image processing program that executes each step according to any one of claims 7 to 12 on a computer.

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