JP2014060681A - Image processor, program, and image forming apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processor capable of improving the identifiability of a monochromatic image after conversion, when a multi-color image is converted into the monochromatic image.SOLUTION: This invention relates to the image processor. The image processor includes means for extracting an edge pixel constituting the edge of a character or a line from the multi-color image expressed by a plurality of color component values, means for determining whether each pixel of the multi-color image is a color pixel or a colorless pixel, means for converting the multi-color image into the monochromatic image which can be expressed by one color component value, and means for applying emphasis processing to each edge pixel of the monochromatic image and applying stronger emphasis processing to the color edge pixel than to the colorless edge pixel.

Description

  The present invention relates to an image processing apparatus, a program, and an image forming apparatus. For example, an image expressed by a plurality of color components (for example, three color components of RGB) (hereinafter referred to as “color image” or “multicolor”). It can be applied to image processing for generating an image expressed by a single color component (hereinafter also referred to as “monochrome image” or “monochromatic image”).

  2. Description of the Related Art Conventionally, in an image forming apparatus such as a copying machine or a printer, there is an apparatus that reads a document as a color image and prints it as a monochrome image. In the conventional image forming apparatus, for example, the luminance component is calculated from the input RGB data using the following equation (1), and the density of the monochrome output is determined from the luminance component.

Luminance Y = 0.29891 × R + 0.58661 × G + 0.11448 × B (1)
However, in the conventional image forming apparatus that determines the density of the monochrome output from the luminance component as described above, the density of the color portion may decrease. For example, when a black text that is often seen in a general document is displayed in a monochrome image with an original that displays the highlighted portion in red or other color characters, the density of the color characters decreases. There was a case. Further, in a conventional image forming apparatus, there is a case where a dot dropout occurs in a portion where the density of a color image is reduced by performing a halftone process such as dithering. In particular, small characters may be harder to recognize in a color other than black than in black.

  In the following description, black characters in a document are represented as “black characters”, and characters other than black in a document are represented as “color characters”.

  And as a prior art which solves the above problems, there is a technology described in Patent Document 1.

  In the image forming apparatus described in Japanese Patent Application Laid-Open No. H10-228561, the read original is recognized and characters are further discriminated. The image forming apparatus disclosed in Patent Document 1 is configured to perform color enhancement on a color character and print it as a monochrome image with a printer.

JP 2003-219189 A

  However, in the conventional image forming apparatus, even when the emphasis processing is performed on the color characters, the monochrome image is printed without being able to recognize the portion where the characters are not recognized, and the desired print quality may not be obtained.

  Therefore, when a color image (multicolor image) is converted into a monochrome image (single color image), an image processing apparatus and program that can improve the discrimination of the converted monochrome image, and an image forming apparatus are desired. ing.

  The image processing apparatus according to the first aspect of the present invention includes: (1) an edge pixel extraction unit that extracts edge pixels constituting the edge of a character or line from a multicolor image represented by a plurality of color component values; Color determination means for determining whether each pixel of the multicolor image is a chromatic color or an achromatic color; and (3) a single color image capable of expressing the multicolor image by one color component value. A monochrome image converting means for converting, and (4) performing enhancement processing for each edge pixel of the monochrome image, and having a stronger degree for chromatic edge pixels than for achromatic edge pixels. And emphasis processing means for performing emphasis processing.

  An image processing program according to a second aspect of the present invention includes: (1) an edge pixel extraction unit that extracts edge pixels that form edges of characters or lines from a multicolor image expressed by a plurality of color component values; (2) color determination means for determining whether each pixel of the multicolor image is a chromatic color or an achromatic color; and (3) the multicolor image can be expressed by one color component value. A monochrome image converting means for converting to a monochrome image; and (4) performing enhancement processing for each edge pixel in the monochrome image, and more for chromatic edge pixels than for achromatic edge pixels. It is characterized by functioning as an emphasis processing means for performing emphasis processing of a strong degree.

  According to a third aspect of the present invention, there is provided an image forming apparatus comprising: an image processing apparatus; and an image forming unit that forms an image processed by using the image processing apparatus on a recording medium. It is characterized by having applied.

  According to the present invention, when a multicolor image is converted into a single color image, it is possible to provide an image processing apparatus that improves the discrimination of the converted single color image.

1 is a block diagram illustrating a functional configuration of a copying apparatus according to a first embodiment. 1 is an external perspective view of a copying apparatus according to a first embodiment. 3 is an explanatory diagram showing an example of a Sobel filter used in the copying apparatus according to the first embodiment. FIG. 3 is an explanatory diagram showing an example of a Laplacian filter used in the copying apparatus according to the first embodiment. FIG. 3 is a flowchart illustrating the operation of the copying apparatus according to the first embodiment. FIG. 6 is an explanatory diagram illustrating an example of enhancement processing performed by the copying apparatus according to the first embodiment. FIG. 6 is an explanatory diagram showing a result when emphasis processing is performed in the copying apparatus according to the first embodiment. It is explanatory drawing shown about the functional structure of the image processing apparatus which concerns on 2nd Embodiment. It is explanatory drawing shown about the sample pattern used with the copying apparatus which concerns on 2nd Embodiment. 10 is a flowchart illustrating the operation of the copying apparatus according to the second embodiment.

(A) First Embodiment Hereinafter, an image processing apparatus, a program, and an image forming apparatus according to a first embodiment of the present invention will be described in detail with reference to the drawings. In the first embodiment, an example in which an image forming apparatus including the image processing apparatus of the present invention is applied to a copying apparatus will be described.

(A-1) Configuration of First Embodiment FIG. 1 is a block diagram showing a functional configuration of a copying apparatus 1 according to this embodiment. FIG. 2 is a perspective view of the copying apparatus 1.

  The copying apparatus 1 includes an image reading unit 101, an image data storage unit 102, an edge extraction unit 103, a color determination unit 104, a monochrome processing unit 105, an edge enhancement unit 106, a printing unit 107, and an operation unit 108. . Note that in the copying apparatus 1, components that mainly perform image processing (the edge extraction unit 103, the color determination unit 104, the monochrome processing unit 105, and the edge enhancement unit 106) are implemented in a computer having a processor and a memory. The image processing program may be installed and executed, and may be realized by software, or some or all of the components may be realized by hardware (for example, a dedicated chip). That is, in the copying apparatus 1, the image data storage unit 102, the edge extraction unit 103, the color determination unit 104, the monochrome processing unit 105, and the edge enhancement unit 106 form the image processing apparatus of the embodiment.

  The image reading unit 101 is a reading device (scanner) composed of a CCD sensor or the like, and has a function of optically reading a document and generating image data. Hereinafter, image data generated by the image reading unit 101 reading a document is referred to as “original image data”. Here, it is assumed that the original image data is a color image represented by three color components of RGB.

  The image data storage unit 102 is a data storage unit configured using, for example, a hard disk or a RAM, and stores at least the original image data generated by the image reading unit 101.

The monochrome processing unit 105 serving as “monochromatic image conversion means” converts the pixels (color pixels) in the original image data stored in the image data storage unit 102 into monochrome (converts them into monochrome pixels). In the following, it is assumed that the monochrome processing unit 105 refers to the image data obtained by converting the original image data into monochrome data as “monochrome image data”. The method by which the monochrome processing unit 105 converts color pixels into monochrome pixels is limited. Is not. In this embodiment, the monochrome processing unit 105 calculates the luminance component for each pixel of the original image data using the above equation (1), and obtains the density based on the calculated luminance. Specifically, it is assumed that the monochrome processing unit 105 sets the density of the pixel higher as the luminance of the pixel is lower. For example, for each pixel of the original image data, the luminance value obtained by the above equation (1) is represented by any value from 0 to 255 (256 gradations). The density determined by the monochrome processing unit 105 for each pixel also applies the same range (0 to 255) as the luminance. Then, the monochrome processing unit 105 may determine the density of each pixel such that the density of a pixel with 0 brightness is 255, the density of a pixel with 1 brightness is 254,. Further, the monochrome processing unit 105 may hold a table in which a density corresponding to each luminance is set in advance, and perform a process of converting from luminance to density based on the table.

  The edge extraction unit 103 as “edge pixel extraction means” performs processing for extracting pixels of edge portions constituting elements such as characters and lines in the original image data stored in the image data storage unit 102. . An edge pixel extraction method by the edge extraction unit 103 is not limited, but in this embodiment, a method based on a filter process using a Sobel filter is adopted. FIG. 3 shows an example of a 3 × 3 Sobel filter (coefficient matrix) for the edge extraction unit 103 to extract edge pixels from original image data.

  The Sobel filter is a filter (coefficient matrix) that can extract a density difference in the vertical direction or the horizontal direction. In an image including an edge portion such as a character or a line, the pixels constituting the edge portion are often present in a portion where the density difference from the surrounding pixels is large. Therefore, using the Sobel filter, the density difference from the surrounding pixels is calculated. By calculating, an edge pixel can be extracted.

  FIG. 3A shows a filter (coefficient matrix) that extracts a density difference in the horizontal direction in the original image data. FIG. 3B shows a filter for extracting a density difference in the vertical direction in the original image data. When extracting an edge pixel by a Sobel filter, a filter for extracting a density difference between the vertical direction and the horizontal direction is used as shown in FIG.

  For each pixel, the edge extraction unit 103 determines the density of each pixel and the surrounding pixels (the density of each pixel in the monochrome image data generated by the monochrome processing unit 105) with reference to FIGS. ) To calculate the density difference between the pixels in the vertical and horizontal directions centered on the pixel. When the horizontal direction or horizontal density difference of the pixel is greater than or equal to the threshold value, the pixel is determined to be an edge pixel.

  The color determination unit 104 as “color determination unit” determines whether each pixel of the original image data stored in the image data storage unit 102 is a chromatic color or an achromatic color. The determination method by the color determination unit 104 is not limited. In this embodiment, the color determination unit 104 first converts the RGB signal values of each pixel into color difference components Cb and Cr of the YcbCr signal according to the following equations (2) and (3). The color determination unit 104 determines that each pixel is a chromatic color if both of the color difference components Cb and Cr are larger than a predetermined threshold, and an achromatic color if at least one is smaller than the predetermined threshold.

Cb = −0.16874 × R−0.33126 × G + 0.50000 × B (2)
Cr = 0.50,000 × R−0.41869 × G−0.08131 × B (3)
The edge enhancement unit 106 as “enhancement processing means” performs image data (hereinafter referred to as “enhancement processing”) that has been subjected to enhancement processing for each pixel determined to be an edge pixel in monochrome image data (hereinafter referred to as “enhancement processing”). Edge-enhanced image data ”). Specifically, the edge enhancement unit 106 performs processing for amplifying a density difference (brightness difference) with the surrounding pixels for each edge pixel in the monochrome image data, and converts the edge pixel portion into a non-edge pixel portion. Edge-enhanced image data is generated by making the image clearer (increasing the density) than the portion.

  Further, the edge enhancement unit 106 applies different enhancement levels (enhancement levels) between the pixel determined to be a chromatic color by the color determination unit 104 and the pixel determined to be an achromatic color by the color determination unit 104. Specifically, the color determination unit 104 performs a process of emphasizing a pixel determined to be a chromatic color to a higher degree than a pixel determined to be an achromatic color.

  Although the specific method of the enhancement processing performed by the edge enhancement unit 106 is not limited, in this embodiment, the enhancement processing is performed using a 3 × 3 Laplacian filter. By applying the Laplacian filter to the enhancement process, the density difference (luminance difference) is amplified between the edge pixel portion and the peripheral pixels (peripheral non-edge pixels), and the edge pixel portion becomes clear. is there.

  FIG. 4 shows an example of a 3 × 3 Laplacian filter (coefficient matrix) for the edge enhancement unit 106 to enhance edge pixels of monochrome image data.

  FIG. 4A shows a filter for emphasizing edge pixels that are chromatic colors in the original image data (a filter having a higher enhancement level than that in FIG. 4B). FIG. 4A shows a filter for emphasizing edge pixels that were achromatic in the original image data (a filter having a lower enhancement level than that in FIG. 4A). Hereinafter, the filter in FIG. 4B is referred to as a “first filter” (first coefficient), and the filter in FIG. 4A is referred to as a “second filter” (second coefficient). To do.

  The edge enhancement unit 106 selects the first filter or the second filter for each edge pixel of the monochrome image data according to the determination result of the color determination unit 104. Then, the edge enhancement unit 106 selects, for each edge pixel, a filter that selects the density of the edge pixel and pixels around the edge pixel (the density of each pixel in the monochrome image data generated by the monochrome processing unit 105) ( (Laplacian filter coefficient matrix) and the density of the edge pixel after enhancement is calculated.

  The printing unit 107 prints (image forms) an image (monochrome image) of edge-enhanced image data supplied from the edge enhancement unit 106 on a printing paper (medium). Here, it is assumed that the printing unit 107 is configured using an electrophotographic image forming unit. In an electrophotographic image forming unit, an electrostatic latent image is formed on a photosensitive drum, and printing (image formation) is performed by copying the electrostatic latent image onto printing paper with toner (developer). Here, it is assumed that the printing unit 107 performs printing on printing paper using black toner.

  The operation unit 108 is an operation panel composed of a display device such as an LCD display or LED and a switch, for example, and displays information to the user and accepts an operation from the user.

(A-2) Operation of the First Embodiment Next, the operation of the copying apparatus 1 of the first embodiment having the above configuration will be described.

  FIG. 5 is a flowchart showing the operation of the copying apparatus 1 in the first embodiment.

  First, it is assumed that a document sheet is set on the reading surface of the image reading unit 101 by the user. Then, it is assumed that a copy instruction operation has been performed on the operation unit 108 by the user. When the user performs a copy instruction operation, the image reading unit 101 generates original image data by scanning the set original paper, and stores the original image data in the image data storage unit 102 (S101).

  Then, the monochrome processing unit 105 calculates monochrome for the original image data to generate monochrome image data (S102).

  Then, the edge extraction unit 103, the color determination unit 104, and the edge enhancement unit 106 perform processing in steps S103 to S109 described later for each pixel of the original image data, and edge enhancement based on the original image data and the monochrome image data. Generate finished image data.

  First, the edge extraction unit 103 selects one pixel as a pixel to be processed in the current loop processing. Hereinafter, the selected pixel is referred to as a “target pixel”.

  Then, the edge extraction unit 103 calculates a density difference between the target pixel and the surrounding pixels using a Sobel filter (S103).

  Then, the edge extraction unit 103 determines whether the pixel of interest is an edge pixel based on the calculated density difference (S104). If it is determined that the target pixel is an edge pixel, the copying apparatus 1 operates from step S105 described later. If it is determined that the target pixel is not an edge pixel, the copying apparatus 1 operates from step S109 described later.

  When it is determined in step S104 described above that the target pixel is an edge pixel, the color determination unit 104 calculates a color difference component (Cb, Cr) in the original image data for the target pixel (S105).

  Then, the color determination unit 104 determines whether the target pixel is a chromatic color or an achromatic color based on the calculated color difference component (S106).

  If it is determined in step S106 described above that the pixel of interest is a chromatic color, the edge enhancement unit 106 performs enhancement processing on the pixel of interest using the second filter having a high enhancement level (S107). .

  On the other hand, when it is determined in step S106 described above that the pixel of interest is an achromatic color, the edge enhancement unit 106 performs an enhancement process on the pixel of interest using the first filter with a low enhancement level ( S108).

  Then, the copying apparatus 1 (the edge extraction unit 103, the color determination unit 104, and the edge enhancement unit 106) checks whether or not all the pixels have been processed (S109), and if all the pixels have been processed. The operation starts from the processing in step S110 described later, and when there remains an unprocessed pixel, the operation returns to the processing in step S103 described above.

  As described above, by the processing in steps S101 to S109, the edge enhancement unit 106 obtains edge-enhanced image data obtained by enhancing the pixels of the edge portion from the monochrome image data. Then, the edge enhancement unit 106 supplies the completed edge enhanced image data to the printing unit 107. The printing unit 107 outputs the edge-enhanced image data in black and white with black toner (printed on the printing paper) (S110).

(A-3) Effects of First Embodiment According to the first embodiment, the following effects can be achieved.

(A-3-1) In the copying apparatus 1, the achromatic edge pixel is emphasized by the second filter, and the chromatic edge pixel is emphasized by the first filter. As a result, in the edge-enhanced image data output from the copying apparatus 1, the edge character of the color character has a density closer to the density of the edge pixel of the black character. In other words, the edge-enhanced image data output from the copying apparatus 1 emphasizes (darkens) the edge pixels of color characters with a strong degree, so that the color characters have the same level of discrimination as black characters for viewers. To prepare.

  That is, when the edge enhancement unit 106 of the copying apparatus 1 performs edge pixel enhancement, if the edge pixel is a chromatic color in the original image data, the enhancement is performed with a higher degree of enhancement than the case of an achromatic color. There is an effect that characters (images of characters that were color characters in the original image data) are not difficult to read in the finished image data.

  6 and 7 are explanatory diagrams showing the result of the emphasis process in the copying apparatus 1. FIG.

  In FIG. 6, the original image of the kanji character “sentence” shown in FIG. 6A is subjected to the enhancement process using the second filter before the enhancement process (FIG. 6B) (FIG. 6 ( c)), each of cases where the enhancement process is performed using the first filter (FIG. 6D). FIGS. 6B to 6D each show a matrix indicating the pixel value (density) of each pixel related to the area A101 in FIG. 6A. In FIG. 6B to FIG. 6D, each pixel value is indicated by a numerical value from 0 to 255 (the higher the numerical value, the darker the density). Then, as shown in FIG. 6, the enhancement process is performed using the second filter having a higher enhancement degree than the case where the enhancement process is performed using the first filter having a lower enhancement degree (FIG. 6C). In the case (FIG. 6D), the density of the edge portion of the character is emphasized.

  FIG. 7 shows an example in which enhancement processing is performed on images of character strings “black characters” and “colors” shown in FIG. FIG. 7A shows an image (monochrome image data image) before the enhancement process. FIG. 7B shows an image (edge-enhanced image data) after the edge enhancement unit 106 performs enhancement processing on the area A201 (a part of the image “black character”) in FIG. 7A. Show. Further, FIG. 7C shows an image (edge-enhanced image data) after the edge enhancement unit 106 performs enhancement processing on the area A202 (a part of the image “color”) in FIG. 7A. Show. FIG. 7B and FIG. 7C illustrate a matrix of pixel values (density) of each pixel in the region in the same format as FIG.

  The image of the character string “black character” shown in FIG. 7A is drawn with black characters (achromatic color) in the original image data. In addition, the image of the character string “color” shown in FIG. 7A is drawn with color characters (chromatic colors) in the original image data. Therefore, in the edge enhancement unit 106, Laplacian filters having different emphasis levels are separately used for the edge pixel of the character string “black character” and the edge pixel of the character string “color”. Specifically, in the edge enhancement unit 106, the second filter with a low emphasis degree is applied to the edge pixel of the character string “black character” and the emphasis degree is strong to the edge pixel of the character string “color”. The first filter will be applied. As a result, as shown in FIGS. 7B and 7C, the edge portion of the character string “color” has a density closer to the edge portion of the character string “black character”. As described above, in the edge-enhanced image data generated by the copying apparatus 1, the color characters (chromatic characters) are almost the same as the black characters (achromatic characters) and are easy to read.

(A-3-2) Since the copying apparatus 1 does not need to hold character recognition pattern data or predetermined font data when highlighting an image relating to a character, it is possible to generate color characters with a simple configuration. The quality of monochrome output can be improved.

(A-3-3) Since the copying apparatus 1 performs the enhancement process for each pixel, it is possible to improve the quality of monochrome output at a location such as a color line drawing that is not recognized as a character.

(A-3-4) The edge enhancement unit 106 of the copying apparatus 1 does not change the display area of the image related to the character, such as changing the thickness of the image related to the character. Therefore, the monochrome output (edge-enhanced image data) of the copying apparatus 1 does not result in an image that is far from the original image data, for example, the font of characters is significantly different from that of the original image data.

(B) Second Embodiment Hereinafter, an image processing apparatus, a program, and an image forming apparatus according to a second embodiment of the present invention will be described in detail with reference to the drawings. In the second embodiment, an example in which an image forming apparatus equipped with the image processing apparatus of the present invention is applied to a copying apparatus will be described.

(B-1) Configuration of Second Embodiment FIG. 8 is a block diagram showing a functional configuration of the copying apparatus 1A of the second embodiment. In FIG. 8, the same or corresponding reference numerals are given to the same or corresponding parts as in FIG.

  The copying apparatus 1A is different from the first embodiment in that a halftone dot determination unit 109 is added.

  The halftone dot determination unit 109 is a part of components that perform image processing in the copying apparatus 1A. The halftone dot determination unit 109 may be configured as software as part of the image processing program of the second embodiment, or may be realized by hardware (for example, a dedicated chip). That is, in the copying apparatus 1A, the image data storage unit 102, the edge extraction unit 103, the color determination unit 104, the monochrome processing unit 105, the edge enhancement unit 106, and the halftone determination unit 109 form the image processing apparatus of the embodiment. ing.

  A halftone dot determination unit 109 serving as a “halftone dot determination unit” is a pixel in which each pixel in the original image data stored in the image data storage unit 102 constitutes a halftone dot image having a predetermined pattern (pattern) (hereinafter referred to as “dot”). It is determined whether it is called “halftone pixel”.

  The method by which the halftone dot determination unit 109 determines whether each pixel is a halftone dot pixel is not limited. In this embodiment, the halftone dot determination unit 109 holds one or a plurality of pattern image samples (hereinafter referred to as “sample patterns”), an image of a predetermined region centered on the pixel of interest, and a sample. The pattern is collated, and it is determined whether or not the pixel of interest is a halftone pixel based on the degree of coincidence.

  Specifically, it is assumed that the halftone dot determination unit 109 holds sample pattern data in a format as shown in FIG. 8, for example.

  The sample pattern in FIG. 8 includes data of pixels corresponding to 11 × 11 pixels centered on the target pixel. Each square frame in FIG. 8 represents a pixel of the sample pattern, and the attached numerical value of 1 or 0 represents the pixel value of the pixel.

  The halftone dot determination unit 109 binarizes 11 × 11 pixels centered on the pixel of interest, compares it with the sample pattern, and counts the number of pixels with matching values. For example, the halftone dot determination unit 109 sets the pixel value of the pixel to 1 when the corresponding pixel of the original image data is an edge pixel (when the edge extraction unit 103 determines that the pixel is an edge pixel), otherwise May be binarized by setting the pixel value of the pixel to 0. Then, the halftone dot determination unit 109 has a predetermined number of pixels whose pixel values match between an image obtained by binarizing the pixels of the original image data (11 × 11 pixels centered on the target pixel) and the sample pattern. Only when the threshold value is equal to or greater than the threshold value, the target pixel is determined as a halftone pixel. If the halftone dot determination unit 109 holds a plurality of sample patterns, the halftone dot determination unit 109 determines that the target pixel is a halftone dot pixel based on the result of matching with any sample pattern. In this case, the final determination result of the target pixel is also a halftone pixel.

  In the second embodiment, the edge enhancement unit 106 is a pixel determined to be a halftone pixel by the halftone determination unit 109 even if it is determined to be an edge pixel by the edge extraction unit 103. Is different from the first embodiment in that no enhancement processing is performed.

(B-2) Operation of Second Embodiment Next, the operation of the copying apparatus 1A of the second embodiment having the above-described configuration will be described.

  FIG. 10 is a flowchart showing the operation of the copying apparatus 1 in the second embodiment. In FIG. 10, steps that perform the same operations as those in the first embodiment (FIG. 5 described above) are denoted by the same reference numerals (step numbers).

  The second embodiment is different from the first embodiment in that the operations of steps S201 and S202 are added.

  When it is determined in step S104 described above that the pixel of interest is an edge pixel, the halftone dot determination unit 109 binarizes a predetermined range of pixels (11 × 11 pixels) centered on the pixel of interest. The determined data is retained and checked with the sample pattern (S201). Then, the halftone dot determination unit 109 confirms the determination result of whether or not the target pixel is a halftone dot pixel (S202).

  If the target pixel is a halftone pixel, the copying apparatus 1A (the edge extraction unit 103, the color determination unit 104, and the edge enhancement unit 106) proceeds to the process of S109 described above, and otherwise. Then, the process proceeds to step S105 described above.

(B-3) Effects of Second Embodiment According to the second embodiment, the following effects can be obtained in addition to the effects of the first embodiment.

  In the copying apparatus 1A, among the edge pixels, halftone dots can be excluded from the target of the enhancement process, so that the image quality of the monochrome output is deteriorated due to the enhancement process of the low-line number halftone image. Absent.

(C) Other Embodiments The present invention is not limited to the above-described embodiments, and may include modified embodiments as exemplified below.

  In each of the above-described embodiments, the example in which the image processing apparatus (image forming apparatus) of the present invention is applied to a copying apparatus has been described. However, as long as the apparatus converts a color image into a monochrome image, the image processing apparatus of the present invention is used. The apparatus to be applied is not limited. For example, the image processing apparatus of the present invention may be applied to an image processing apparatus (image forming apparatus) such as a printer, a FAX, or a multifunction peripheral, or image data is simply stored. You may make it apply to the personal computer and workstation which process.

  In each of the above embodiments, the example in which the image processing apparatus (image forming apparatus) of the present invention is applied to a copying apparatus that prints a monochrome image on printing paper has been described. However, the image processing apparatus of the present invention outputs a monochrome image. The form to do is not limited. For example, a monochrome image generated by the image processing apparatus of the present invention may be displayed on a display or the like. Further, for example, a monochrome image generated by the image processing apparatus of the present invention is recorded as data on a storage medium (for example, recorded on a storage medium such as an HDD or a CD-ROM) or output to an external device (via a network). Output).

  DESCRIPTION OF SYMBOLS 1 ... Copy apparatus, 101 ... Image reading part, 102 ... Image data storage part, 103 ... Edge extraction part, 104 ... Color determination part, 105 ... Monochrome processing part, 106 ... Edge emphasis part, 107 ... Printing part, 108 ... Operation part.

Claims (9)

Edge pixel extraction means for extracting edge pixels constituting the edge of a character or line from a multicolor image represented by a plurality of color component values;
Color determination means for determining whether each pixel of the multicolor image is a chromatic color or an achromatic color;
Monochrome image conversion means for converting the multicolor image into a monochrome image that can be expressed by one color component value;
Enhancement processing means for performing enhancement processing for each edge pixel in the single-color image, and performing enhancement processing for a stronger degree for chromatic edge pixels than for achromatic edge pixels. An image processing apparatus.   The image processing apparatus according to claim 1, wherein the enhancement processing unit performs enhancement processing with a higher degree for chromatic edge pixels than for achromatic edge pixels.   The image processing apparatus according to claim 1, wherein the edge pixel extraction unit extracts each pixel as an edge pixel when a difference in density from surrounding pixels is larger than a predetermined value. .   The enhancement processing unit performs enhancement processing on each edge pixel by amplifying a density difference between a peripheral pixel of the edge pixel and the edge pixel by filter processing. The image processing apparatus according to any one of 1 to 3. The enhancement processing means includes a plurality of coefficients used for filter processing related to enhancement processing,
The image processing apparatus according to claim 4, wherein the enhancement processing is performed using different coefficients for edge pixels determined to be chromatic colors and edge pixels determined to be achromatic colors. Further comprising halftone dot determining means for determining whether or not each pixel of the multicolor image is a halftone dot pixel constituting a rope image
The image processing apparatus according to claim 1, wherein the image enhancement processing unit does not perform enhancement processing of pixels determined to be halftone pixels by the halftone determination unit.   For each pixel, the halftone dot determination means determines that the pixel is a halftone pixel based on a matching result between a distribution pattern of edge pixels in a region including the pixel and a peripheral pixel of the pixel and a predetermined sample pattern. The image processing apparatus according to claim 6, wherein it is determined whether or not there is any. Computer
Edge pixel extraction means for extracting edge pixels constituting the edge of a character or line from a multicolor image represented by a plurality of color component values;
Color determination means for determining whether each pixel of the multicolor image is a chromatic color or an achromatic color;
Monochrome image conversion means for converting the multicolor image into a monochrome image that can be expressed by one color component value;
Among the monochromatic images, enhancement processing is performed for each edge pixel, and functions as enhancement processing means for performing stronger enhancement processing for chromatic edge pixels than for achromatic edge pixels. An image processing program characterized in that An image forming apparatus comprising: an image processing apparatus; and an image forming unit that forms an image processed using the image processing apparatus on a recording medium.
An image forming apparatus, wherein the image processing apparatus according to claim 1 is applied as the image processing apparatus.

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