JP2015146557A - Image processing apparatus, image processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To solve the problem in which, when determining chromatic color pixels of a scan image, there are cases where impurities are erroneously determined as chromatic color pixels and a highlight color dot original is erroneously determined as a monochromatic original.SOLUTION: Isolated point determination is performed and features (size and number) of an isolated point are calculated. A dot region of a highlight part is determined from the features of the isolated point, and switchover to a coefficient easy to determine a color by chromatic color pixel determination only in the dot region of the highlight part is performed.

Description

  The present invention relates to image processing for identifying whether an input image is a color image or a monochrome image.

  In an image forming apparatus such as an MFP (Multi Function Peripheral) having a scanning function, each pixel of an image obtained by digital reading when a document is scanned in color is chromatic or achromatic. It is determined whether or not. Specifically, the chromatic color or achromatic color is determined by comparing the saturation of each pixel with a predetermined saturation threshold, and the reading target is based on the number of connected pixels determined to be chromatic. It is determined whether the original is a color original or a monochrome original. Such a color determination technique is generally called ACS (Auto Color Select). When it is determined that the document is a color document by the ACS technology, a color image is provided to the user when it is determined that the document is a monochrome document.

  However, ACS technology is not universal, and there are cases where the judgment fails. For example, this is a case where low-quality paper such as recycled paper using 100% used paper is scanned. These low-quality papers have a feature that the appearance frequency of impurities contained in the paper is higher than that of high-quality papers. In the case of such low-quality paper, because the impurity is chromatic, the pixel corresponding to the impurity is determined to be a chromatic pixel, and as a result, the original that should be determined as a monochrome original is a color original. There was a case where it was judged.

JP 2008-35478 A

  As a countermeasure against the erroneous determination as described above, a countermeasure that makes it easy to determine that each pixel is an achromatic color by changing the saturation threshold value used for comparison is also conceivable. However, if such measures are taken, there are cases where a document that should be determined to be a color document is erroneously determined to be a monochrome document.

  In particular, color highlight halftone originals are easily mistaken for monochrome originals. Since each of the color halftone dots included in the highlight halftone document is small, the saturation of each pixel of the read image obtained by reading it is relatively low. Therefore, if it is easy to determine that each pixel is an achromatic color by changing the saturation threshold, a pixel corresponding to such a color halftone dot is erroneously determined to be an achromatic color.

  Incidentally, a vivid color pixel group exists in an area where the density of a color image is medium to high (for example, a Not highlight halftone dot area) or a color character area. Therefore, in these areas, a large number of chromatic pixels are found no matter how the saturation threshold is set, and it can be correctly determined that the original is a color document.

Based on the above points, a saturation threshold that is easily determined to be chromatic is used for each pixel in the highlight halftone dot region, and an achromatic color is used for each pixel in other regions (including the impurity region). It is necessary to use a saturation threshold that is easy to determine.
Note that Patent Document 1 uses a saturation threshold value that is easily determined to be an achromatic color for each pixel in the halftone dot region, and is the reverse of this application.

  An image processing apparatus according to the present invention includes a detection unit that detects isolated points from image data, a counting unit that counts the number of isolated points detected by the detection unit in a predetermined region including a target pixel, and the counting Determining means for determining whether the number of isolated points counted by the means exceeds a first threshold, and determining whether the pixel of interest is a chromatic color or an achromatic color according to a determination result in the determining means Setting means for setting the second threshold value of the second threshold value, and when the determination means determines that the number of the isolated points counted by the counting means exceeds the first threshold value, The second threshold value set is the second threshold value set by the setting means when the determination means determines that the number of isolated points counted by the counting means does not exceed the first threshold value. Threshold of 2 Remote, wherein the pixel of interest is the more likely to be determined as chromatic color threshold.

  According to the present invention, highly accurate ACS processing can be easily realized.

1 is a block diagram illustrating an example of a configuration of an MFP according to Embodiment 1. FIG. It is a functional block diagram which shows the internal structure of an image process part. It is a flowchart which shows the flow of a process in an image process part. 3 is a flowchart illustrating a flow of image area separation processing according to the first embodiment. It is a flowchart which shows the flow of a highlight halftone area | region determination process. It is a table showing an example of a determination target pattern in highlight halftone dot determination processing, It is a figure explaining an isolated point determination. It is a figure which shows an example of the result at the time of performing a highlight halftone area | region determination process. It is a figure which shows an example of the result at the time of performing a highlight halftone area | region determination process. It is a figure which shows an example of the result at the time of performing a highlight halftone area | region determination process. It is a flowchart which shows the flow of ACS processing. 6 is a flowchart illustrating details of a chromatic color pixel determination process according to the first embodiment. It is a figure explaining a mode that it is judged using a different judgment coefficient whether an attention pixel is a chromatic color pixel or an achromatic color pixel. 10 is a flowchart illustrating details of a chromatic color pixel determination process according to the second embodiment.

  Hereinafter, the present invention will be described in detail according to preferred embodiments with reference to the accompanying drawings. In addition, the structure shown in the following Examples is only an example, and this invention is not limited to the structure shown in figure.

  Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram illustrating an example of the configuration of an MFP as an image forming apparatus according to the present embodiment.

  The MFP 100 includes a CPU 101, a memory 102, an HDD 103, a scanner unit 104, an image processing unit 105, a printer unit 106, and a display unit 107 that are connected to each other via an internal bus 109, and is connected to a network 110 via a network I / F 108. Has been.

  The CPU 101 is a processor that comprehensively controls the MFP 100 and controls each unit connected via the internal bus 109.

  The memory 102 includes a ROM that stores various commands (including application programs) and various data executed by the CPU 101 to control the MFP 100, and a RAM that functions as a work area of the CPU 101.

  The scanner unit 104 has a function of optically reading a document set on a document table (not shown) and acquiring scanned image data. Here, the scanner unit 104 can read a document with a resolution of a maximum of 600 dpi. To do.

  The image processing unit 105 performs necessary image processing on the scanned image data acquired by the scanner unit 104. Details of the image processing unit 105 will be described later.

  The printer unit 106 has a function of printing an image on a recording medium such as paper.

  The HDD 103 temporarily stores scanned image data acquired by the scanner unit 104.

  The display unit 107 is configured by a liquid crystal panel having a touch screen function, and displays various information, and the user gives a scan instruction via a screen displayed on the display unit 107.

  The network interface 108 is an interface for performing communication such as transmission / reception of print data with a PC (not shown) connected via a network 110 such as a LAN or the Internet.

  Note that the components of the image forming apparatus are not limited to those described above. For example, instead of the touch screen, an input unit including a mouse and a keyboard for performing various operations by the user may be provided. The configuration of the image forming apparatus may be appropriately added or changed according to the application. It can be done.

  FIG. 2 is a functional block diagram showing the internal configuration of the image processing unit 105. The image processing unit 105 includes an image area separation processing unit 201, a first color conversion processing unit 202, an ACS processing unit 203, a filter processing unit 204, a background removal processing unit 205, a second color conversion processing unit 206, and a gradation correction processing unit. 207 and a halftone processing unit 208.

  The image area separation processing unit 201 performs processing for generating image area information by determining the attributes (characters, halftone dots, etc.) of the scanned image as the input image for each pixel. In the image area information in this embodiment, data of 1 bit (“1” for a highlight halftone dot and “0” for a highlight halftone dot) indicating whether each pixel is a highlight halftone dot is used. Shall be included. The final image area information may be data of an arbitrary number of bits including the determination result after performing character determination processing and the like. Details of the image area separation processing will be described later.

  The first color conversion processing unit 202 converts image data in a color space (here, RGB color space) depending on the input side device (scanner) into a device-independent color space (for example, L * a * b * or Lch). Convert to image data.

  The ACS processing unit 203 performs ACS processing on the image data converted into the device-independent color space using the above-described image area information. Details of the ACS processing will be described later.

  The filter processing unit 204 performs filter processing according to the attribute of the image data converted into the device-independent color space. For example, processing using an edge enhancement filter is performed for a character region, and processing using a smoothing filter is performed for a region other than the character region.

  The background removal processing unit 205 performs background removal processing for removing the background of the filtered scan image data.

  The second color conversion processing unit 206 converts the image data in the device-independent color space into image data in a color space (here, CMYK color space) depending on the output side device (printer).

  The gradation correction processing unit 207 corrects the gradation characteristics of each color of CMYK using the 1D-LUT. Here, the 1D-LUT is a one-dimensional LUT (Look Up Table) that defines an output gradation value with respect to an input gradation value for each color of CMYK.

  The halftone processing unit 208 performs halftone processing (halftone processing) such as screen processing and error diffusion processing to generate binary CMYK image data.

  Next, the flow of processing in the image processing unit 105 will be described. FIG. 3 is a flowchart showing the flow of processing in the image processing unit 105. This series of processing is carried out by reading a computer-executable program describing the following procedure from the ROM into the RAM and then executing the program by the CPU 101.

  In step 301, the image processing unit 105 acquires input image data. There are two types of input image data at this time: scan image data obtained by reading a document with the scanner unit 104 and printer image data sent together with a print instruction from a PC (not shown). The printer image data in this embodiment is assumed to be image data in the CMYK color space.

  In step 302, the image processing unit 105 determines the type of the acquired input image data. If the acquired input image data is scan image data, the image data is sent to the image area separation processing unit 201 (proceeds to step 303). On the other hand, if the acquired input image data is a printer image, the image data is sent to the gradation correction processing unit 206 (proceeds to step 309).

  In step 303, the image area separation processing unit 201 performs image area separation processing to generate image area information (in this embodiment, 1-bit data indicating whether each pixel is a highlight halftone dot) from the scanned image. To do.

  In step 304, the first color conversion processing unit 202 converts the device-dependent color space (RGB) in the scanned image into a device-independent color space (L * a * b * or Lch).

  In step 305, the ACS processing unit 203 performs ACS processing on the scanned image data converted into the device-independent color space using the image area information.

  In step 306, the filter processing unit 204 performs a filter process on the scanned image data converted into the device-independent color space.

  In step 307, the background removal processing unit 205 removes the background of the scanned image that has been filtered.

  In step 308, the second color conversion processing unit 206 converts the color space in the scanned image from which the background is removed into a device-dependent color space (CMYK).

  In step 309, the gradation correction processing unit 207 corrects the gradation characteristics of each color of CMYK using a 1D-LUT on the printer image as input image data or the scanned image on which various processes in and after step 303 are performed. .

  In step 310, the halftone processing unit 208 performs predetermined halftone processing to generate binary CMYK image data.

  The above is the processing flow in the image processing unit 105. The generated image data is output to the printer unit 106 and the like.

<Image area separation processing>
Next, details of the image area separation processing will be described. FIG. 4 is a flowchart showing the flow of image area separation processing according to the present embodiment.

  In step 401, the image area separation processing unit 201 acquires a pixel value from the scanned image data. In this embodiment, since the scan image is an image in the RGB color space, the pixel value of each RGB channel is acquired.

  In step 402, the image area separation processing unit 201 generates an image area separation determination signal from the acquired pixel value of the scanned image. For example, (R + 2 × G + B) / 4 is calculated using the acquired pixel values of each RGB channel, and a 256-scale (8-bit) grayscale image is generated as a determination signal. Here, the number of gray scale bits is arbitrary. Further, the determination signal may be generated by other methods, for example, using only the G channel pixel value.

  In step 403, the image area separation processing unit 201 determines a target pixel to be processed.

  In step 404, the image area separation processing unit 201 performs a process of determining whether or not the determined pixel of interest is a pixel in the highlight halftone area (highlight halftone area determination process). Details of the highlight halftone dot region determination process will be described later.

  In step 405, the image area separation processing unit 201 generates image area information based on the determination result of the highlight halftone area determination process. The generated image area information data is stored in a RAM or the like in the memory 102.

  In step 406, the image area separation processing unit 201 determines whether there is a pixel that has not yet been processed. If there is an unprocessed pixel, the process returns to step 403 to determine the next pixel as a target pixel, and the processing of step 404 and step 405 is repeated.

  The above is the content of the image area separation processing according to the present embodiment.

<Highlight dot area determination processing>
FIG. 5 is a flowchart showing the highlight halftone dot region determination process in step 404 described above. Prior to the description of FIG. 5, a pattern to be determined when the resolution of the scanner unit 104 is 600 dpi will be described. FIG. 6 is a table showing an example of a determination target pattern: 1) highlight halftone dot [150 line], 2) highlight halftone dot [error diffusion], 3) impurity [large], and 4) impurity [small]. The characteristics for the four patterns are shown.

  Here, the halftone dot patterns 1) and 2) should be detected as highlight halftone dot areas, while the impurity patterns 3) and 4) should not be detected as highlight halftone dot areas. . In general, the size of impurities contained in a recording medium such as paper is often larger than the halftone dot of the highlight portion (see the “dot shape” column in FIG. 6), while the number of highlights is highlighted. It can be said that the number is smaller than the halftone dots (see the “number of isolated points” column in FIG. 6). In this embodiment, it is determined whether or not each pixel is a pixel in a highlight halftone dot region based on such impurity characteristics.

  In step 501, the image area separation processing unit 201 performs binarization processing on the image area separation determination signal generated in step 402. Specifically, the pixel value of the image area separation determination signal is compared with a predetermined threshold (Th_HiAmi1), and it is converted to a binary signal by determining whether the pixel value exceeds the threshold. The threshold value Th_HiAmi1 in this case may be an arbitrary value based on the whiteness of a specific paper. For example, a value obtained when color scanning is performed on paper having a whiteness of about 50%, which is generally used for recycled paper. The average value of

  In step 502, the image area separation processing unit 201 performs isolated point determination processing of 2 × 2 pixels and 1 × 1 pixels using the binarized values. 7A and 7B are diagrams for explaining isolated point determination in this step. FIG. 7A shows isolated point determination of 2 × 2 pixels, and FIG. 7B shows isolated point determination of 1 × 1 pixel. For the determination of an isolated point of 2 × 2 pixels, pattern matching is performed using pixel values of the target pixel and its surrounding pixels (4 × 4 pixels). In FIG. 7A, a region A is a printed region composed of a 2 × 2 pixel group, and a region B is a non-printed region obtained by removing the pixel of the region A from a 4 × 4 pixel group. . For the determination of an isolated point of 1 × 1 pixel, pattern matching using pixel values of the target pixel and its surrounding pixels (3 × 3 pixels) is performed. In FIG. 7B, a region A is a printed region (one pixel), and a region B is a non-printed region obtained by removing the pixel of the region A from the 3 × 3 pixel group. The bold rectangles in FIGS. 7A and 7B indicate the target pixel. In the present embodiment, as conditions for determining as an isolated point, it is assumed that the pixel values of the region A are all “1” and the pixel values of the region B are all “0”. . However, since the shape of the dot of the halftone dot changes depending on the density, for example, the pattern matching condition may be given a width, and the matching result may be determined at a level such as the degree of approximation. That is, it is desirable to be able to determine a halftone dot area even if the patterns do not completely match. By performing 2 × 2 pixel isolated point determination, for example, it is possible to separate a halftone dot region having a screen line number of 150 lines and a large impurity of 2 × 2 pixels or more in a recording medium in a highlight portion. It becomes. Further, by performing isolated point determination of 1 × 1 pixel, for example, a dot area by an error diffusion method in a highlight portion and a small impurity of less than 2 × 2 pixels (greater than 1 × 1 pixel) in a recording medium. It becomes possible to perform carving.

  8 to 10 show different input images (highlight halftone dot [150 lines]: FIG. 8A, impurities: FIG. 9A, highlight halftone dot [error diffusion]: FIG. 10A). FIG. 8 is a diagram showing a result when highlight dot area determination processing is performed. First, the result of the isolated point determination of 2 × 2 pixels is as shown in FIGS. 8B, 9B, and 10B. In the case of an original with 150 screen lines, isolated points are detected periodically as shown in FIG. As for the impurities in the recording medium, only relatively small impurities of 2 × 2 pixels are detected as isolated points as shown in FIG. 9B. Further, in the case of a document subjected to halftone processing by the error diffusion method, no isolated point is detected as shown in FIG. Next, the results of the 1 × 1 pixel isolated point determination are as shown in FIGS. 8D, 9D, and 10D. In the case of a document having 150 screen lines, no isolated point is detected as shown in FIG. As for the impurities in the recording medium, only the smallest impurities are detected as isolated points as shown in FIG. Further, in the case of a document subjected to halftone processing by the error diffusion method, only pixels that are not connected to other pixels are detected as isolated points as shown in FIG.

  In step 503, the image area separation processing unit 201 performs integration processing (counting processing) on each isolated point determination result in step 502, and derives the total number of isolated points in a predetermined region (integration region). Here, the predetermined area is a 16 × 16 pixel area, but the size is arbitrary. For example, the isolated points of 2 × 2 pixels may have any size as long as the number of isolated points corresponding to the screen line number of halftone dots can be detected. Further, the isolated points of 1 × 1 pixels may have any size as long as the halftone dot area ratio can be estimated.

  In step 504, the image area separation processing unit 201 compares the total number of isolated points counted in step 503 with a predetermined threshold value to determine whether the target pixel is a pixel in the halftone dot area of the highlight part. Each of the isolated points of × 2 pixels and the isolated points of 1 × 1 pixels is determined. Here, the predetermined threshold (Th_HiAmi2) for the isolated point of 2 × 2 pixels is the number of halftone cells that can be represented by 150 screen lines in the integration region in step 503. In this embodiment, the integration area is an area of 16 × 16 pixels, and 15 isolated points can be detected in the area, so “15” is set as the threshold Th_HiAmi2. Thus, if the total number of isolated points of 2 × 2 pixels derived in step 503 is 15, the target pixel is determined to be a pixel in the highlight halftone area. Note that the value of the threshold Th_HiAmi2 only needs to be a value that can determine the halftone dot region of the highlight portion, and may be a value other than the above. Similarly, the predetermined threshold (Th_HiAmi3) for the isolated point of 1 × 1 pixel is the number of isolated points in a predetermined range derived from the halftone dot area ratio to be determined as the area in the integration region in step 503. The reason why the threshold Th_HiAmi3 has a width in this way is as follows. First, the upper limit is set, for example, when the dot area ratio is 20%, there is a print area of 80 pixels within 20 × 20 pixels. However, in the error diffusion method, connected pixels are generated and the number of isolated points is not 80. This is because there is a possibility. In the present embodiment, when the number is greatly higher than 80, the dot area ratio is high, and thus there is a possibility of a high-density high-line-number screen. Therefore, the upper limit is set to 80. The reason why the lower limit is set is to eliminate the possibility of impurities contained in the recording medium. In the present embodiment, the number is set to five in consideration of correctly identifying the impurity [small] in FIG. Of course, the above upper limit value and lower limit value are merely examples, and may be set in a range other than the above.

  For a 2 × 2 pixel isolated point, in the case of a document having a screen line number of 150 lines, an isolated point is periodically detected, so that it is determined as a halftone dot region of the highlight portion (FIG. 8C). reference). On the other hand, in the case of impurities in the recording medium, since the number of isolated points detected is small, it is not determined as a halftone dot region of the highlight portion (see FIG. 9C). Similarly, in the case of a document subjected to halftone processing by the error diffusion method, since there is no isolated point to be detected, it is not determined as a halftone dot region of a highlight portion (see FIG. 10C).

  For an isolated point of 1 × 1 pixel, if the document has a screen line number of 150 lines, an isolated point is not detected, so that it is not determined as a halftone dot region of a highlight portion (see FIG. 8E). On the other hand, in the case of impurities in the recording medium, although small impurities are detected as isolated points, the number thereof is small, so that it is not determined as a halftone dot region in the highlight portion (see FIG. 9E). Then, in the case of a document subjected to halftone processing by the error diffusion method, since a number of isolated points within a specified range are detected, it is determined as a halftone dot region of a highlight portion (see FIG. 10E). ).

  In step 505, the image area separation processing unit 201 specifies whether or not the target pixel is a pixel in the highlight halftone dot area using the result of the threshold determination in step 504. Specifically, if any of 2 × 2 pixels and 1 × 1 pixels is determined to be a highlight halftone dot region, the target pixel is specified as a pixel in the highlight halftone dot region.

  The above is the content of the highlight part halftone dot region determination process. By such a process, for example, a document pattern having a screen line number of 150 lines or a halftone-processed document pattern is determined as a highlight halftone area, and impurities in the recording medium are not a highlight halftone area. It will be determined. The highlight halftone dot region determination process may be any method as long as the halftone dot region of the highlight portion can be determined from the number of isolated points obtained by the isolated point determination. For example, pattern matching may be performed using various patterns in consideration of density, screen line number, screen shape, and the like. In this embodiment, binary data obtained by binarizing pixel values is used as an input value for pattern matching. However, edge information obtained by binarizing a filtered value is used. It doesn't matter.

<ACS processing>
Next, details of processing (ACS processing) for determining whether a scanned document is a color document or a monochrome document will be described. FIG. 11 is a flowchart showing the flow of ACS processing. The color mode is switched according to the result of the ACS processing.

  In step 1101, the ACS processing unit 203 performs a chromatic color pixel determination process using the image area information generated by the above-described image area separation process. Specifically, a chromatic color pixel or an achromatic color pixel is used for each pixel using a determination coefficient included in the image area information (a coefficient corresponding to a signal indicating whether each pixel is a highlight halftone area pixel). It is determined whether it is. FIG. 12 is a flowchart illustrating details of the chromatic color pixel determination processing according to the present embodiment.

  In step 1201, the ACS processing unit 203 acquires image area information.

  In step 1202, the ACS processing unit 203 converts the image data converted into the device-independent color space in step 304 described above into a color space for chromatic color pixel determination. In this embodiment, the color space is converted to the L * a * b * color space. However, it may be converted into a color space such as LCh or RGB.

  In step 1203, the ACS processing unit 203 determines a target pixel to be processed.

  In step 1204, the ACS processing unit 203 sets a coefficient (threshold value) used for chromatic color pixel determination for the pixel of interest based on the image area information acquired in step 1201. Specifically, if the target pixel is a pixel in the highlight halftone dot region, the coefficient used for chromatic color pixel determination is set to the first chromatic color pixel determination coefficient (threshold Th_C1), and the target pixel is the highlight portion. If the pixel is not in the halftone dot region, the second chromatic color pixel determination coefficient (threshold Th_C2) is set. Here, in the first chromatic color pixel determination coefficient and the second chromatic color pixel determination coefficient, the second chromatic color pixel determination coefficient can more easily determine the halftone dot of the highlight portion as the chromatic color pixel. It is a coefficient.

  In step 1205, the ACS processing unit 203 determines whether the pixel of interest is a chromatic pixel or an achromatic pixel using the determination coefficient set in step 1204. FIG. 13A shows a state of determination using the first chromatic color pixel determination coefficient, and FIG. 13B shows a state of determination using the second chromatic color pixel determination coefficient. In FIGS. 13A and 13B, the horizontal axis represents lightness (L *), and the vertical axis represents saturation (C *). In this case, the saturation C * can be obtained by the following equation (1).

  In the determination using the first chromatic color pixel determination coefficient (threshold Th_C1), the saturation C * is obtained from the L * a * b * value converted in step 1202 by the above equation (1), and the obtained saturation C Whether or not the pixel is a chromatic pixel is determined by whether or not * is greater than or equal to the threshold Th_C1. That is, if the saturation C * is greater than or equal to the threshold Th_C1, it is determined as a chromatic pixel, and if the saturation C * is less than the threshold Th_C1, it is determined as an achromatic pixel. The same applies to the determination using the second chromatic color pixel determination coefficient (threshold value Th_C2). As is apparent from FIG. 13, the chromatic color pixel is more effective when the second chromatic color pixel determination coefficient (threshold Th_C2) is used than when the first chromatic color pixel determination coefficient (threshold Th_C1) is used. A high percentage is determined. That is, in the case of the threshold value Th_C2, it can be seen that even if the threshold value Th_C1, the low chromaticity value that is determined as an achromatic color can be determined as a chromatic color. In the present embodiment, the threshold values Th_C1 and Th_C2 are uniform values that do not depend on the lightness, but may be different values depending on the lightness. Further, the threshold values Th_C1 and Th_C2 may be switched for each hue.

  In step 1206, the ACS processing unit 203 adds data indicating whether the target pixel is a chromatic pixel or an achromatic pixel to the image area information based on the determination result in step 1205. As data in this case, for example, 1-bit data indicating whether each pixel is a chromatic color pixel (“1” for a chromatic pixel or “0” for an achromatic pixel) may be used.

  In step 1207, the ACS processing unit 203 determines whether there is a pixel that has not yet been processed. If there is an unprocessed pixel, the process returns to step 1203 to determine the next pixel as a target pixel, and the processing of step 1204 to step 1206 is repeated.

  The above is the content of the chromatic color pixel determination process in the present embodiment. As described above, the highlight halftone dot area in the original is more easily determined as a chromatic pixel than the other areas, so that the accuracy of the ACS determination of the original having the highlight halftone is improved.

  Returning to the flowchart of FIG.

  In step 1102, the ACS processing unit 203 performs integration processing for obtaining the number of pixels determined to be chromatic pixels for each predetermined unit area. Here, the predetermined unit area is an area of 100 × 100 pixels. The size of the unit area is arbitrary. For example, a 10-point character may be determined to be a color original, but the area needs to be larger than the area of one halftone cell.

  In step 1103, the ACS processing unit 203 determines whether the document related to the input scan image data is a color document based on the number of chromatic pixels obtained in step 1102. Specifically, if the number of chromatic color pixels per unit area exceeds the number given by a predetermined threshold (Th_ACS), the document is determined to be a color document. Here, the threshold value Th_ACS is determined in consideration of the degree of influence on the highlight halftone dot due to characteristics such as the MTF of the scanner unit 104. In this embodiment, the halftone dot area ratio 20 that can be expressed in the unit region. % Is the number of pixels in the highlight halftone dot.

  In step 1104, the ACS processing unit 203 sets a color mode according to the determination result in step 1103. Specifically, if it is determined that the document is a color document, the color mode is set to full color, and this process ends. On the other hand, if it is determined that the document is not a color document (a monochrome document), the color mode is set to monochrome, the input scanned image data is converted to monochrome, and the process ends.

  The above is the content of the ACS processing according to the present embodiment.

  According to the present embodiment, it is possible to perform the ACS determination with high accuracy without depending on the quality of the recording medium.

  In the first embodiment, the dot area of the highlight portion and the impurities in the recording medium are separated using pattern matching. Next, an embodiment in which an impurity region on a recording medium is extracted and the extracted impurity region is not determined as a chromatic pixel will be described as a second embodiment. Note that the description of the contents common to the first embodiment such as the internal configuration of the image processing unit 105 and the basic processing flow (FIG. 3) is omitted, and in the ACS processing that is the difference from the first embodiment below. The chromatic color pixel determination process will be mainly described.

  FIG. 14 is a flowchart illustrating details of the chromatic color pixel determination processing according to the present embodiment.

  In step 1401, the ACS processing unit 203 acquires image area information. The image area information acquired in this embodiment includes data for specifying impurities in addition to data for specifying highlight halftone dots. The data for specifying the impurities corresponds to the isolated points of 2 × 2 pixels and 1 × 1 pixels determined not to satisfy the predetermined threshold in the threshold determination (step 504) in the highlight halftone dot region determination process described above. For example, it is 1-bit data that can specify a pixel.

  In step 1402, the ACS processing unit 203 converts the image data converted into the device-independent color space into a color space for chromatic color pixel determination.

  In step 1403, the ACS processing unit 203 determines a target pixel to be processed.

  Each process so far corresponds to step 1201 to step 1203 in the flowchart of FIG. 12 according to the first embodiment.

  In step 1404, the ACS processing unit 203 determines whether or not the target pixel is a chromatic pixel according to a predetermined determination coefficient. That is, unlike the first embodiment, the determination coefficient according to the attribute of the target pixel is not set. The determination coefficient in this step may be any value as long as it can determine that the halftone dot area of the highlight portion is a chromatic pixel.

  In step 1405, the ACS processing unit 203 refers to the determination result in step 1204 and the image area information acquired in step 1401, and determines whether the target pixel is a chromatic pixel or an impurity pixel. If the target pixel is a chromatic pixel and an impurity pixel, the process proceeds to step 1406. On the other hand, in other cases (when the target pixel is an achromatic pixel or not an impurity pixel), the process proceeds to step 1407.

  In step 1406, the ACS processing unit 203 changes the attribute of the target pixel determined to be a chromatic color pixel and an impurity pixel to an achromatic color pixel.

  In step 1907, the ACS processing unit 203 generates data (for example, 1 bit) indicating whether the target pixel is a chromatic pixel or an achromatic pixel based on the determination result in step 1204 and the change result in step 1406. Append to information.

  In step 1408, the ACS processing unit 203 determines whether there is a pixel that has not yet been processed. If there is an unprocessed pixel, the process returns to step 1403 to determine the next pixel as a target pixel, and the processes of steps 1404 to 1407 are repeated.

  The above is the content of the chromatic color pixel determination process in the present embodiment. By such processing, all impurity regions extracted from the recording medium are treated as achromatic pixels.

  According to the present embodiment, an impurity region in the recording medium is specified, and the specified impurity region is not handled as a chromatic color pixel. As a result, ACS processing that is not affected by impurities contained in the recording medium can be performed.

(Other examples)
The present invention is also realized by executing the following processing. That is, software (program) for realizing the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, etc.) of the system or apparatus reads the program. It is a process to be executed.

Claims (7)

Detection means for detecting isolated points from image data;
Counting means for counting the number of isolated points detected by the detection means in a predetermined area including the target pixel;
Determining means for determining whether the number of isolated points counted by the counting means exceeds a first threshold;
Setting means for setting a second threshold value for determining whether the target pixel is a chromatic color or an achromatic color according to a determination result in the determination means;
Have
The second threshold set by the setting unit when the determination unit determines that the number of isolated points counted by the counting unit exceeds the first threshold is counted by the counting unit. A threshold value that makes it easier for the pixel of interest to be determined as a chromatic color than the second threshold value set by the setting means when the determination means determines that the number of isolated points has not exceeded the first threshold value. An image processing apparatus characterized by the above.   The image processing apparatus according to claim 1, wherein the isolated point detected by the detection unit is an isolated point constituting a halftone dot region of a highlight portion in the image data.   3. The isolated points constituting the halftone dot region of the highlight portion are an isolated point of 1 × 1 pixel and an isolated point of 2 × 2 pixels with a resolution of the image data of 600 dpi. The image processing apparatus described.   3. The image processing apparatus according to claim 2, wherein the isolated points constituting the halftone dot area of the highlight portion do not include an isolated point of 3 × 3 pixels with a resolution of the image data of 600 dpi.   It is determined whether each pixel of the image data is a chromatic color using the second threshold set by the setting unit, and whether the image data is color document image data or monochrome document image data according to the determination result The image processing apparatus according to claim 1, further comprising a color document determination unit that determines whether or not A detection step of detecting isolated points from the image data;
A counting step of counting the number of isolated points detected in the detection step in a predetermined area including the target pixel;
A determination step of determining whether the number of isolated points counted in the counting step exceeds a first threshold;
A setting step for setting a second threshold value when determining whether the pixel of interest is a chromatic color or an achromatic color according to a determination result in the determination step;
Have
When the determination step determines that the number of isolated points counted in the counting step exceeds the first threshold, the second threshold set in the setting step is counted in the counting step. Further, when the determination step determines that the number of isolated points has not exceeded the first threshold value, the threshold value at which the target pixel is more likely to be determined as a chromatic color than the second threshold value set in the setting step An image processing method characterized by the above.   A program for causing a computer to function as the image processing apparatus according to any one of claims 1 to 5.

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