JP2010074318A - Image processing apparatus and method, and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To satisfy a request of a user who wants to change setting when being output. <P>SOLUTION: A multifunction machine 100 includes a scanner 101 for input of image data, an area extracting part 121 for recognizing the type of each area included in the image data for the image data, an HDD 106 for storing the image data and the type of each area, a specifying part 146 for specifying one type from area types stored in the HDD 106 on the basis of an image division mode of the image data, and a printer γ part 142 for performing correction processing suitable for the specified type of the image data stored in the HDD 106. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image processing apparatus that performs image processing on image data, an image processing method, and an image processing program.

  2. Description of the Related Art Conventionally, when image processing is performed on optically read image data, the content of the image processing is changed according to the type of image data.

  For example, for image data mainly composed of characters, binarization processing or the like is performed so that the edges are clear, and for image data mainly composed of photographs or the like, the gradation of the color of the image data Image processing is performed to protect the image. For this reason, it is important to appropriately determine the contents described in the image data.

  For example, in the technique described in Patent Document 1, a determination criterion for determining whether image data is a line drawing or a halftone image is instructed. As a result, it is possible to determine whether the image reflects the user's preference.

JP-A-3-64257

  In the conventional technology including Patent Document 1 as described above, when the image data stored on the storage device is reprinted, the image data obtained as the first determination result is printed again. On the other hand, even for image data that has been printed once, there is a demand for changing the determination criterion according to the use after printing.

  However, the conventional technique has a problem in that it is not possible to change the determination criterion for image data that has been read once, and if it is desired to change the determination criterion, it is necessary to read the original again. .

  The present invention has been made in view of the above, and provides an image processing apparatus, an image processing method, and an image processing program capable of changing image data output according to the use even if the image data has been printed once. The purpose is to provide.

  In order to solve the above-described problems and achieve the object, an image processing apparatus according to the present invention includes an image data input unit that inputs image data, and each region included in the image data with respect to the image data. Recognizing means for recognizing a type, storage means for storing the image data, and the type of each area recognized by the recognizing means, and storing in the storage means based on the output setting of the image data. A specifying unit that specifies one type from the type of each of the areas, and an image processing unit that performs image processing suitable for the specified type on the image data stored in the storage unit; .

  The image processing method according to the present invention includes an image data input step in which the image data input means inputs the image data, and a recognition means for each type of each area included in the image data for the image data. A recognition step for recognizing the image data, a storage step for storing the type of each area recognized by the recognition means in a storage means, and a specifying means based on the output setting of the image data, A specifying step for specifying one type from the types of the respective areas stored in the storage unit, and an image processing unit for the specified type of the image data stored in the storage unit. And an image processing step for performing suitable image processing.

  An image processing program according to the present invention includes an image data input step for inputting image data, a recognition step for recognizing the type of each area included in the image data, and the image data. And a storage step of storing the type of each area recognized by the recognition unit in a storage unit, and a type of each area stored in the storage unit based on an output setting of the image data, A computer is caused to execute a specifying step of specifying one type and an image processing step of performing image processing suitable for the specified type on the image data stored in the storage unit.

  According to the present invention, in order to perform appropriate image processing on the specified area after storing the image data, the input of the image data is not required every time an output is requested. Since it is possible to output appropriate image data, there is an effect that convenience is improved.

  Exemplary embodiments of an image processing apparatus, an image processing method, and an image processing program according to the present invention are explained in detail below with reference to the accompanying drawings.

  Exemplary embodiments of an image processing apparatus, an image processing method, and an image forming apparatus to which an image processing program according to the present invention is applied will be explained below in detail with reference to the accompanying drawings. The embodiment described below is not limited to the image forming apparatus, and can be applied to various apparatuses such as a facsimile apparatus.

  According to an embodiment of the present invention, an image forming apparatus includes a copy function, a facsimile (FAX) function, a print function, a scanner function, and an input image (an original image read by the scanner function or an image input by a printer or a FAX function). An example of application to a multifunction device 100 called a so-called MFP (Multi Function Peripheral) that combines functions and the like to distribute the content.

(First embodiment)
FIG. 1 is a block diagram illustrating a schematic configuration of a multifunction peripheral 100 according to the present embodiment. As shown in the figure, the MFP 100 includes a scanner 101, a scanner correction unit 102, a compression processing unit 103, a controller 104, a NIC 105, an HDD 106, an expansion processing unit 107, and a printer correction unit 108. The plotter 109 and the input device 110 are connected to the external PC terminal 130 via a network.

  The HDD 106 stores image data and information indicated by various signals. In this embodiment, an HDD (Hard Disk Drive) is used, but it can be configured by any commonly used storage means such as an optical disc, a memory card, and a RAM (Random Access Memory).

  The input device 110 is a device for a user to input an operation. When the user operates the input device 110, the multi-function device 100 can execute a copy process or the like.

  In addition, the multifunction peripheral 100 stores image data obtained by scanning a document in the HDD 106. When performing the copying process or the like, the multifunction peripheral 100 receives a selection of an image separation mode from the user via the input device 110, and performs a process for printing according to the received image separation mode.

  Image separation mode refers to the priority of the type specified for each area when specifying each area of the image data as a character area or a pattern area (for example, a certain area may be a character or a pattern) In this case, a mode for designating a character area or a picture area is designated. In the present embodiment, the user needs to select from the standard mode and the character mode as the image separation mode. The image separation mode is a setting input from the user for outputting image data, in other words, corresponds to an output setting. The image separation mode may be used as a setting for input image data.

  The character mode that can be selected in the image separation mode is a mode that preferentially extracts an area that may be a character (or that includes a character) as a character edge area. Even if there is a possibility of image processing, image processing is performed as a character area.

  The standard mode that can be selected in the image separation mode is a mode that preferentially extracts an area having a possibility of a pattern (or including a drawing) as a pattern area. Even if there is a possibility, image processing is performed as a pattern area.

  When the multifunction peripheral 100 performs a copying process, the scanner 101 optically reads a document, converts an analog signal obtained by optical reading into a digital signal (for example, 600 dpi), and then outputs the digital signal as image data. .

  The scanner correction unit 102 includes an area extraction unit 121, a scanner γ unit 122, and a filter processing unit 123. The scanner correction unit 102 extracts characters, line drawings, photographs, and the like for each area from the image data output from the scanner 101. Image processing such as filter processing is performed on the RGB data of the image data.

  The region extraction unit 121 extracts regions for each visually different type based on the input image data (reflectance linear). Any method may be used for this extraction method. For example, the extraction method used in Japanese Patent Laid-Open No. 2003-259115 may be used.

  As a result, the region extraction unit 121 extracts two types of regions, an edge region and other (photo region) pattern regions. Then, the region extraction unit 121 gives an image region separation signal to each pixel of each extracted region. The region extraction unit 121 recognizes whether each region included in the image data is an edge region or other (photo region) pattern region, and gives the recognition result as an image region separation signal. That is, it means that the area extraction unit 121 functions as a recognition unit in other words.

  The edge region is a region where an edge considered as a character is detected. The picture area is an area other than that, and includes, for example, a photograph area.

  The image area separation signal is a signal including information for identifying each area. The image area separation signal according to the present embodiment is composed of 3-bit information, specifically, a character separation signal (2 bits) and a color area signal (1 bit). The type of the area of each pixel can be specified by the image area separation signal.

  The character separation signal is a signal including information (1 bit) indicating whether or not each pixel is a character edge and information (1 bit) indicating whether or not it is a picture area. In the information indicating whether or not it is a picture area, information indicating a picture area is set when it is determined that there is a white background or a halftone dot. A method for determining the presence or absence of a white background and a method for determining the presence or absence of a halftone dot will be described later.

  The color area signal is a signal including information indicating whether each pixel is a color area (a color other than black on the white ground).

  FIG. 2 is an explanatory diagram showing the concept of each region. As shown in FIG. 2, the input image data 201 is stored as it is in the HDD 106 as stored image data. On the other hand, the region extraction unit 121 extracts a pattern region and an edge region from the image data. The extracted pattern area, edge area, and accumulated image data are accumulated in the HDD 106.

  Then, when a request for printing using image data stored in the HDD 106 is received, for each pixel in the edge area and the picture area, according to the image separation mode input by the user at the time of printing request, A color character edge region, a black character edge region, or a pattern region is specified.

  The black character edge region is a region where a black character edge is detected on the white ground. The color character edge region is a region where a character edge of a color other than black is detected on the white ground.

  For example, when the character mode is selected as the image separation mode, the region 202 including the “new sale” that is the edge region and the color region is determined as the color character edge region. As a result, “new sale” is processed as an outline character. When the standard mode is selected as the image separation mode, the area 202 including the “new sale” that is the edge area and the color area is determined as the pattern area. As described above, in the present embodiment, the determination criterion varies depending on whether the image separation mode is the character mode or the standard mode.

  In the present embodiment, the color character edge region and the pattern region are switched and extracted according to the image separation mode selected by the user. However, the color character edge region and other intermediate processes are used. Switching extraction may be performed.

  As described above, when the image separation mode is the standard mode, “new sale” is determined as a picture, and when the character is a small character, the legibility may be low. Therefore, as shown in FIG. 2, when the image separation mode is the character mode, “newly released” is determined as a character, and therefore, processing suitable for the character is performed for a region that may be a character. , Improve legibility.

  As described above, when the stored image data is printed again, by selecting the image separation mode, output according to the preference of the operator is possible.

  The area extraction unit 121 outputs image data of an edge area, image data indicating a picture area, accumulated image data, and an image area separation signal of each pixel.

  FIG. 3 is a block diagram illustrating a configuration of the region extraction unit 121 according to the first embodiment. The region extraction unit 121 includes a filter 321, an edge extraction unit 322, a white region extraction unit 323, a halftone dot extraction unit 324, a color determination unit 325, and an overall determination unit 326.

  The filter 321 emphasizes and corrects the G image data generated by the scanner mainly for character edge extraction.

  The edge extraction unit 322 includes a ternarization unit 322a, a black pixel continuous detection unit 322b, a white pixel continuous detection unit 322c, a neighboring pixel detection unit 322d, and an isolated point removal unit 322e. In the present embodiment, an example in which G (Green) image data is referred to when performing edge extraction has been described. However, the present invention is not limited to the G image data, and can be applied to any signal that expresses shading such as luminance data. .

  By the way, the character region has many high-level density pixels and low-level density pixels (hereinafter referred to as black pixels and white pixels), and these black pixels and white pixels are continuous at the edge portion. have. Therefore, after the black pixel continuous detection unit 322b and the white pixel continuous detection unit 322c of the edge extraction unit 322 detect the continuity of each of the black pixel and the white pixel, the neighboring pixel detection unit 322d detects the neighboring pixel, The removal unit 322e removes an isolated pixel (matching a predetermined condition). Thereafter, the edge extraction unit 322 determines an edge region based on such a processing result.

  The white area extraction unit 323 determines that the area written on the white background of the image data is a white area, determines a dark black character periphery as a white area, and determines a low density area as a non-white area.

  A halftone dot extraction unit 324 extracts a halftone dot of the image data and determines that it is a halftone dot region.

  The color determination unit 325 includes a hue division unit 325a, a c memory 325b, an m memory 325c, a y memory 325d, a w memory 325e, and a color pixel determination unit 325f. Then, the hue dividing unit 325a divides each pixel into cyan, magenta, yellow, and white hues, and stores them in the c memory 325b, the m memory 325c, the y memory 325d, and the w memory 325e. Then, the color pixel determination unit 325f determines a color (chromatic) pixel or a black (achromatic) pixel in the image data based on the information stored in each memory.

  The overall determination unit 326 comprehensively determines the area of each pixel. FIG. 4 is a block diagram illustrating a configuration of the comprehensive determination unit 326. As shown in FIG. 4, the comprehensive determination unit 326 includes a character determination unit 326a, an expansion processing unit 326b, and a decoding unit 326c.

  If the result of the edge extraction unit 322 is that there is an edge, the result of the halftone dot extraction unit 324 is that there is no halftone dot, and the result of the white region extraction unit 323 is that there is a white region, the character determination unit 326a determines that it is a character edge. In other cases, it is determined as a non-character edge (in a pattern or a character).

  The expansion processing unit 326b performs an OR (logical sum) process of 8 × 8 blocks on the result of the character determination unit 326a, and then performs an AND (logical product) process of 3 × 3 blocks to perform a 4-pixel expansion process. That is, if any pixel of 8 × 8 pixels centered on the target pixel is a character edge, it is assumed that the target pixel is also a character edge region, and all 3 × 3 blocks centered on the target pixel are assumed. Is a character edge region, the pixel of interest is determined to be a character edge, and a total of five pixels including the pixel of interest and the four pixels adjacent thereto are set as the character edge region.

  The result of the expansion processing unit 326b is output to the decoding unit 326c as a character edge signal. Such processing of the expansion processing unit 326b prevents the separation result from being different and the character area from being thinned.

  The decoding unit 326c finally outputs a character separation signal (C / P signal in FIG. 4). The overall determination unit 326 outputs the color determination result as a color area signal (B / C signal in FIG. 4). A total of 3 bits of information including the character separation signal (2 bits for each pixel) and the color area signal (1 bit for each pixel) are output. In this way, an image area separation signal including a character separation signal and a color area signal is output.

  Returning to FIG. 1, the scanner γ unit 122 converts the image data (accumulated image data, edge region, and pattern region image data) input from the region extraction unit 121 from reflectance linear to density linear data. To do.

  The filter processing unit 123 switches the filter processing to be applied for each pixel according to the image area separation signal. The filter processing unit 123 performs edge enhancement processing (sharpening processing) on character edge regions (including black character edge regions and color character edge regions) with emphasis on legibility.

  Further, the filter processing unit 123 performs a smoothing process or an edge enhancement process (sharpening process) on a color area such as a photographic area, using a steep density change in the image data as an edge amount, according to the edge amount. . The sharp edges are emphasized in order to make the characters included in the photograph, figure or graph easy to read. Further, the character edge region can be combined with the color region, and the binarization threshold value can be changed between the color character edge region and the black character edge region.

  The compression processing unit 103 compresses the RGB corrected 8-bit image data, the character separation signal (2 bits), and the color area signal (1 bit), and sends them to the general-purpose bus. The compressed image data, character separation signal (2 bits), and color area signal (1 bit) are transmitted to the controller 104 via a general-purpose bus. In this embodiment, the image data, the character separation signal (2 bits), and the color area signal (1 bit) are compressed. If the bandwidth of the general-purpose bus is sufficiently wide and the capacity of the HDD 106 to be stored is large, It may be handled in an uncompressed state.

  The controller 104 includes a page memory 131, a compression / decompression processing unit 132, an output format conversion unit 133, an input format conversion unit 135, a data i / f unit 134, and a device i / f unit 136. The controller 104 outputs image data stored in the HDD 106 to the external PC terminal 130 or inputs image data from the external PC terminal 130. In addition, the controller 104 performs an operation input process from the input device 110.

  The device i / f unit 136 processes information input from the input device 110. In addition, the device i / f unit 136 receives an input of the image separation mode input from the input device 110. Further, the device i / f unit 136 receives an input of the image processing mode input from the input device 110.

  The image processing mode is processing information of the read document, and there are three types, that is, a character mode in which character-oriented processing is performed, a standard mode in which characters and photos are compatible, and a photo mode in which processing with emphasis on photos is performed.

  Further, the device i / f unit 136 can display the image data by outputting the image data to the input device 110. The displayable image data may be any image data, for example, image data after being corrected by the printer correction unit 108.

  The controller 104 stores the input image data in the HDD 106. As the accumulated data, in addition to the image data, the image size is included as bibliographic information, and information held by the character separation signal (2 bits) and the color area signal (1 bit) is stored. When the controller 104 accepts input of the image separation mode and the image processing mode during image input, the controller 104 may store the input modes.

  The page memory 131 temporarily stores input image data, a character separation signal (2 bits), a color area signal (1 bit), and the like.

  The controller 104 stores the image data input from the compression processing unit 103 in the HDD 106. Thereafter, when using the image data, the controller 104 reads the image data stored in the HDD 106 into the page memory 131.

  The compression / decompression processing unit 132 decompresses the compressed image data in the page memory 131 to the original 8-bit data for each color and outputs it to the output format conversion unit 133.

  The output format conversion unit 133 performs color conversion on the RGB data of the input image data into sRGB data that is a standard color space, and converts the RGB data into a general-purpose image format such as JPEG format or TIFF format.

  FIG. 5 is a block diagram showing the configuration of the output format conversion unit 133. As shown in FIG. 5, the output format conversion unit 133 includes a color conversion unit 501, a resolution conversion unit 502, a TIF format generation unit 503, a JPG format generation unit 504, a compression format generation unit 505, data i / f portion 506.

  The color conversion unit 501 performs data conversion between RGB data. The resolution conversion unit 502 performs pixel density conversion such as 300 dpi and 200 dpi on the image data after the RGB data conversion. This embodiment is an example of conversion to 300 dpi.

  The TIF format generation unit 503, the JPG format generation unit 504, and the compression format generation unit 505 perform processing for converting the resolution-converted image into each format. Next, the compression format generation unit 505 will be described.

  The compression format generation unit 505 includes a binarization unit 511, a black image generation unit 513, a binary image generation unit 512, a first resolution conversion unit 514, a second resolution conversion unit 515, and a background image generation unit 516. And a character image generation unit 517 and an image file composition unit 518.

  The binarization unit 511 outputs a binary image + mask image data (2 bits) and black character image data (1 bit) for identifying a character area and a non-character area on the basis of brightness and darkness of the image density.

  The binarization unit 511 performs binarization based on a plurality of feature amounts. FIG. 6 is a block diagram illustrating a configuration of the binarization unit 511. As shown in FIG. 6, the binarization unit 511 includes a character resolution conversion unit 601, an adaptive binarization unit 602, an isolated point removal unit 603, an N-value conversion unit 604, and a first halftone dot detection unit 605. A second halftone dot detection unit 606, a first gray detection unit 607, a second gray detection unit 608, and a character determination unit 609.

  Then, the binarization unit 511 performs the processing of the adjacent pixels when the processing is completed for one pixel value for each line from the top line in the sequential processing, and the processing is continued to the end of the image data. In the present embodiment, RGB image data is used. The RGB image data is data that becomes darker as the pixel value increases and becomes lighter as the pixel value decreases.

  The character resolution conversion unit 601 converts the character edge region and the color region signal, which are image data expanded by the compression / decompression processing unit 132, to the same resolution as that applied to the image data (for example, 300 dpi), and Unify pixel density. Then, the character resolution conversion unit 601 outputs information on the character edge and color.

  The adaptive binarization unit 602 includes a threshold selection unit 621 and a binarization execution unit 622, and performs binarization processing.

  The threshold selection unit 621 sets a binarization threshold for each of the character edge region and the other region, and switches the threshold according to the region to be processed. It should be noted that a parameter that makes it easier to determine the character is set for the character edge region than for the other regions.

  Then, the binarization execution unit 622 performs binarization processing on each region with the selected threshold value. For example, the binarization execution unit 622 determines that the value of the input image RGB of each pixel is black (on) when at least one of the values exceeds the threshold, and determines that none of the values exceeds the threshold. Is determined to be white (off). For example, when R = 128, G = 120, and B = 118 are set as threshold values, and the pixels of the input image data are R = 121, G = 121, and B = 121, the binarization execution unit 622 Judge as black. When the pixels of the input image data are R = 110, G = 110, and B = 110, the binarization execution unit 622 determines that the pixel is white.

  In this way, the threshold value is switched between the character edge region and the other region based on the background color. That is, if the character written on the background color other than white is dark and the character written on the white background is thin with respect to image data, any background color of The upper character cannot be determined to be black (on).

  Therefore, the adaptive binarization unit 602 according to the present embodiment switches the threshold value between the character edge region and the other region. Thereby, since the threshold value for the white ground character and the threshold value for the upper character other than the white background color are different, the light character on the white background and the color ground character can be appropriately determined to be black (on). Thereby, appropriate binarization processing becomes possible.

  In the present embodiment, as will be described later, edge enhancement processing (sharpening processing) is performed on the character edge region for the image data to be binarized, and other than the character edge region, depending on the edge amount Since the image processing is performed, the picture area is smoothed. In this case, since the smoothing process is performed on the background area of the color ground character, binarization can be satisfactorily performed.

  The isolated point removal unit 603 removes isolated pixels because there are many isolated pixels in the processing result of the adaptive binarization unit 602. The isolated point removal unit 603 removes an isolated pixel by performing inversion processing on the pixel of interest when it matches each pattern shown in FIG.

  The N-value conversion unit 604, the first halftone dot detection unit 605, the second halftone dot detection unit 606, the first gray detection unit 607, and the second gray detection unit 608 constitute a mask unit.

  The N-value conversion unit 604 uses each pixel of the image data in common in order to perform halftone dot detection by the halftone detection units 605 and 606 described later and to perform gray detection by the gray detection units 607 and 608. Convert to N value.

  When the pixel (bk) having a small difference between RGB is larger than the threshold thabk, the N-value conversion unit 604 sets the black character. Further, the N-value conversion unit 604 divides pixels having a large difference between RGB into six hues of YMCBGR, and uses a threshold for each hue (thay, tham, thac, thab, thag, thar) for each hue. Perform binarization processing. Thereby, a pixel having a dark color in each hue is determined as an active pixel (character). The method of dividing the hue may be simply based on the magnitude relationship of RGB or may be determined by the ratio of RGB colors. This is determined by the characteristics of the input image. The output result is held for each hue.

  N in the N-value conversion unit 604 according to the present embodiment is set to “8”, and the following values are set for each pixel. In the parentheses, it is assumed that bits are displayed.

  N values are as follows: Dtah = 0 (000): “Not applicable”, Dtah = 1 (001): “Yellow”, Dtah = 2 (010): “Magenta”, Dtah = 3 (011): “Red Dtah = 4 (100): “Cyan”, Dtah = 5 (101): “Green”, Dtah = 6 (110): “Blue”, Dtah = 7 (111): “Black”.

  Further, the N-value conversion unit 604 performs binarization processing on the white level as well. The N-value conversion unit 604 sets a white pixel when a pixel (bk) having a small difference between RGB has a value smaller than the threshold thbbk. Further, in the case of a pixel having a large difference between RGB, the N-value conversion unit 604 divides the pixel into six hues of YMCBGR, and uses two threshold values for each hue (thby, thbm, thbc, thbb, thbg, thbr). Perform value processing. Then, a pixel having a light color in each hue is determined as an active pixel (white pixel).

  In addition, among the pixels included in black, a pixel obtained by extracting a black (darker) color is used as a dark black and used during black extraction. FIG. 8 is a diagram showing the relationship between the gray area and the character area. A reference numeral 801 shown in FIG. 8 is a character area, and a reference numeral 802 is a gray area.

  The first halftone dot detection unit 605 scans image data in the forward direction to detect halftone dots. In other words, fine halftone dots in the image data have been eliminated by the smoothing process by the scanner correction unit 102, but rough halftone dots such as newspaper photographs are not smoothed, and the halftone dots are not smoothed. The dot shape remains. Therefore, the first halftone dot detection unit 605 detects this coarse halftone dot. The first halftone dot detection unit 605 according to the present embodiment performs halftone dot pattern matching in order to detect halftone dots. In this embodiment, a black pixel is set when Dtah ≠ 0, and an N-valued white pixel is set as a white pixel. A detailed detection procedure will be described later.

  The second halftone dot detector 606 scans the image data in the reverse direction to detect halftone dots. In other words, the halftone dot is detected by the first halftone dot detection unit 605 by reverse-reading a portion where the halftone dot is not taken by scanning in the forward direction.

  The first halftone dot detection unit 605 and the second halftone dot detection unit 606 detect a halftone dot when there is a certain halftone dot pattern between the white pattern and the white pattern. Furthermore, by determining that the halftone dot pattern is a non-halftone dot when the interval between the halftone dot pattern is wide, it is possible to determine a white character with a dark black gradation background as a non-halftone dot. For example, the first halftone dot detection unit 605 and the second halftone dot detection unit 606 determine the white characters in the image data shown in FIG. 9 as non-halftone dots. When halftone detection is performed on the image data shown in FIG. 10, the first halftone dot detection unit 605 and the second halftone dot detection unit 606 have almost no halftone dot shape in a dark background. to decide. Further, the first halftone dot detection unit 605 and the second halftone dot detection unit 606 determine that the dark character on the background with a light gradation has almost no halftone dot shape, and therefore, it is determined as a non-halftone dot.

  By the way, since a general character is written on the white ground, the halftone dot pattern in the white ground character is only near the edge of the character, so that the character on the white ground is hardly erroneously detected as a halftone dot region. .

  In this embodiment, pattern matching is performed for white and other than white, but the Y component, M component, and C component may be performed independently. By performing halftone dot detection processing independently for each of the Y component, the M component, and the C component, since the ink component of printing is YMC, it is possible to accurately detect the ink dot reproduction.

  Returning to FIG. 6, the first gray detection unit 607 and the second gray detection unit 608 use the fact that the character region is dark and the region around the character is thin, so that the region is lighter than the character region and darker than the character region. Is determined as medium density gray. Note that the white background used in the gray determination is an N-valued white pixel.

  The first gray detection unit 607 performs gray detection processing on the image data in the forward direction, whereas the second gray detection unit 608 performs gray detection processing on the reverse direction. The second gray detection unit 608 performs processing in the reverse direction, so that an area where the tip of the gray area is not great can be determined as gray.

  In general, since a region including characters is composed of a dark pixel region and a light (white) pixel region, the first gray detection unit 607 and the second gray detection unit 608 do not detect gray. On the other hand, since the pattern area (for example, a photograph) that does not exist in the character part has colors of various gradations, the first gray detection unit 607 and the second gray detection unit 608 make the medium density region gray. Detect as. The region determined to be gray by the first gray detection unit 607 and the second gray detection unit 608 is assumed to be until the number of white pixels exceeds a certain value for the peripheral pixels in the region.

  The first gray detection unit 607 and the second gray detection unit 608 also detect dark pixels as gray pixels. Further, the first gray detection unit 607 and the second gray detection unit 608 detect as non-gray pixels when a predetermined number or more of blacks continue in the gray region. Here, the pixel area determined to be gray is defined as a gray area. As a result, it is possible to detect white characters with a black background as a non-gray area.

  The character determination unit 609 includes a black character determination unit 611. After determining the black character region and the color character region, the character determination unit 609 outputs a binary image (for switching the region used in the image separation mode) as an output of the binarization unit 511. 3 bits of a binarized area), a mask area (halftone area or gray area), and a black character determination area are output for each pixel.

  The binary output from the isolated point removal unit 603 is used as information indicating whether or not it is a character area. Further, the information output from the isolated point removal unit 603 is a pixel included in the character region and is included in the halftone dot region detected by the first halftone dot detection unit 605 and the second halftone dot detection unit 606. First, it is not included in the gray area detected by the first gray detection unit 607 and the second gray detection unit 608 and is not a background area (output of background detection) and is not a black character (a black character determination result described later). , Pixels in a color character. It should be noted that any known method may be used for detecting the background.

  In addition, when determining the character area, the logical operation with the background area, the halftone dot area, and the gray area is performed because the character determination result is a picture area that does not originally require a resolution. This is because of the correction. In particular, the photographic area contains a large number of isolated points, and by performing this correction, the compression rate of the character image is improved, and the image and the character non-character are less mixed, so that the image quality can be improved.

  The reason why the character determination unit 609 excludes the black character determination result from the character determination result is that the determination result is output separately for black characters, and the character image is set to a fixed value in order to improve the compression rate. is there.

  The black character determination unit 611 determines whether the area is a black character area. FIG. 11 is a block diagram illustrating a configuration of the black character determination unit 611. As illustrated in FIG. 11, the black character determination unit 611 includes a character determination unit 1101, a 3-line OR unit 1102, a pattern determination unit 1103, a black determination unit 1104, a first extraction unit 1105, and a second extraction unit 1106. , First mirror 1107, second mirror 1108, and determination unit 1109.

  The character determination unit 1101 performs a logical operation of the character edge region result and the color determination result, which are output results of the region extraction unit 121 in the previous stage, and performs a black character edge region if the character edge region is not a color region. Output.

  The 3-line OR unit 1102 takes an OR of 3 lines × 1 pixel of a black character edge as a result of character determination. Originally, instead of this three-line OR, it is necessary to delay the two lines after the extraction by the first extraction unit 1105 to match the extraction by the second extraction unit 1106 with the line delay, but the line after the first extraction unit 1105 When the delay occurs, it becomes necessary to delay the image data. Therefore, the line delay is absorbed by taking the 3-line OR here.

  The pattern determination unit 1103 includes a color determination result that is an output result of the preceding region extraction unit 121, a result of the first gray detection unit 607, a result of the second gray detection unit 608, a result of the first halftone detection unit 605, If any one of the results of the two-dot detection unit 606 is “on”, it is determined as a picture.

  When the color determination result, which is the output result of the previous region extraction unit 121, is not a color other than black and white and is determined to be black (Bk or dark black) by N-value conversion, the black determination unit 1104 judge.

  The first extraction unit 1105 determines whether each pixel is a pattern region, an intermediate region, or a black character region based on the determination results of the character determination unit 1101, the 3-line OR unit 1102, and the pattern determination unit 1103. A detailed processing flow will be described later.

  The first mirror 1107 generates a reverse elephant (mirror) image. The second extraction unit 1106 performs black character determination using a reverse image (mirror) image. The second mirror 1108 restores the reverse image (mirror). In this case, mirror processing is performed before and after the second extraction unit 1106 in order to realize processing with an inverse image by pipeline processing. Note that the processing performed by the second extraction unit 1106 is the same as that of the first extraction unit 1105, and a description thereof will be omitted.

  If the outputs from the first extraction unit 1105 and the second mirror 1108 after the second extraction unit 1106 are both black character areas and the output after the processing result by the isolated point removal unit 603 is a character, the determination unit 1109 Judged as black characters.

  Thus, by referring to the state of the image of the surrounding pixels and determining whether or not the character is a black character, it is possible to determine whether the character is in the size image area.

  In the present embodiment, since the color, halftone dot, and the like are detected based on the character edge region and the color region, it can be detected with high accuracy. In addition, the smoothed data is used as the density information for black character determination because the halftone dot area is small for a character composed of halftone dots and may not be determined as a character edge area. Instead, using data after smoothing filter processing (smoothed because it is not a character edge region), only a dark region is determined as a character. In addition, halftone dots with low screen lines, such as newspaper photos, remain halftone even after smoothing, so halftone dots are detected, and halftone dots with high screen lines in general manuscripts such as catalogs are not Since the halftone dot shape disappears because it is smoothed, a region having a halftone dot area ratio of about 30% to 60% is detected as a gray region.

  By the way, since the leading end of the character is narrow, it is difficult to form a halftone dot (non-character region). For example, if the leading end is a character edge region and the center of the character is determined to be a halftone dot, the black character determination is halfway and unsightly. Become. Therefore, in the MFP 100 according to the present embodiment, it is possible to avoid being unsightly by performing the above-described processing.

  Returning to FIG. 5, the binary image generation unit 512 performs MMR compression, which is reversible conversion, on the binary image + mask image. The black image generation unit 513 performs MMR compression that is reversible conversion on the black character image.

  FIG. 12 is a diagram illustrating the concept of image data converted by the output format conversion unit 133. As shown in FIG. 12, a black character image, a mask image, and a binary image are generated by the binarization unit 511 from the input image data 201.

  The first resolution conversion unit 514 and the second resolution conversion unit 515 perform resolution conversion on the image data, and generate image data with a low resolution (for example, 150 dpi).

  The background image generation unit 516 is a binary image output from the binarization unit 511, and is an image region that is not masked by the mask image and that is configured with constant pixel values corresponding to white in the image data. As image data, lossy compression (for example, JPG compression) is performed.

  The character image generation unit 517 performs irreversible compression (for example, JPG compression) using image data other than the binary image as image data having a fixed pixel value.

  In the present embodiment, the reason why the background image is data having a constant pixel value is to improve the compression rate. In addition, the reason why the background area is set to a constant pixel value in the character image data is to improve the compression rate.

  In the resolution conversion performed by the resolution conversion unit 502, the character image does not require the same resolution as the background image. For this reason, the resolution of the character image may be about 75 dpi. When the image processing mode is the character mode, the resolution conversion unit 502 generates a JPG format image file with a resolution of 75 dpi for the background image and the character image. The reason why the resolution is reduced with respect to characters is that the resolution of the characters is guaranteed by the reversible compression MMR, so that it does not matter if the resolution of the JPG image is lowered to deteriorate the gradation. In the MFP 100 according to the present embodiment, the file size can be reduced by reducing the resolution of the character image. In this embodiment, the file size is reduced by reducing the resolution of the character image. However, the file size may be reduced by reducing the image quality (other than the resolution) such as the number of gradations of the image data. .

  In addition to the image data stored in the HDD 106, an image processing mode is stored as bibliographic information. When the image processing mode is the character mode, it is possible to increase the compression rate for all the regions extracted as characters in the accumulated image data.

  In the present embodiment, a background image can be generated by superimposing a mask image on a stored image data, and a character image can be generated by superimposing a binary image. The same information may be included between the generated character image and background image. As described above, the reason why the configuration of the character image and the background image is redundant is that it is necessary for the input format conversion unit 135 to switch processing according to the image separation mode.

  The JPG compression of the background image generation unit 516 and the character image generation unit 517 is performed using a quantization table having different characteristics. Note that JPG compression may be performed using an existing technique, and may be performed as described in, for example, Japanese Patent Application Laid-Open No. 2005-303979.

  In the JPG compression of the background image generation unit 516 and the character image generation unit 517, after the image data is cut out in block units (for example, 8 × 8 pixel units), discrete cosine transform is performed on the cut out DCT block data. Convert to frequency space.

  At this time, in the quantization process that affects the compression level, the quantization process is performed using different reference quantization tables for the Y component and the CbCr component.

The quantization table value Q′ij that is actually used for quantization with respect to the reference quantization table value Qij
Is calculated using the quality factor (qf). Note that qf is a value between 0 and 100. And when qf is smaller than 50, it calculates by Formula (1).
Q′ij = Qij ÷ qf (1)
Further, when qf is 50 or more, it is calculated by the equation (2).
Q′ij = Qij × (100−qf) ÷ 50 (2)

  By the way, a general reference quantization table is created based on the property that human vision is sensitive to low frequencies and insensitive to high frequencies. Furthermore, in a general quantization table, since the color information has a lower discriminating ability than the luminance information, the frequency cut amount is larger than that for the luminance information.

  On the other hand, the background image generation unit 516 according to the present embodiment compresses image data at about qf = 20 to 30 when performing the quantization process. For this reason, if a general quantization table is used, block noise is likely to occur. In particular, the block noise of the basic unit (8 × 8) of JPG is greatly influenced by the value of the DC component representing the average density in the block. In order to reduce the block noise of the basic unit of JPG, a reference quantization table storing DC components for both luminance difference and color difference as shown in FIG. 13 is used. When qf = 25 is set, the quantization table shown in FIG. 14 is calculated from the equation (1) and the reference quantization table shown in FIG. Therefore, the background image generation unit 516 performs a quantization process using the quantization table shown in FIG.

  When the character image generation unit 517 performs JPG compression using a general reference quantization table, color mixing may occur. For example, when JPG compression is performed using a general reference quantization table on an 8 × 8 block in which a plurality of colors (red, blue) exist as shown in FIG. 15, high frequency components are cut. Therefore, color mixing occurs between red and blue due to the effect of aliasing distortion. In order to avoid this problem, the character image generation unit 517 uses the reference quantization table shown in FIG. The reference quantization table shown in FIG. 16 is a reference quantization table that stores color difference components that store the entire frequency of the color difference components. Then, the quantization table shown in FIG. 17 is calculated based on the reference quantization table shown in FIG. 16 and the value of qf = 20. The luminance component in this quantization table is not so important because it is determined by the MMR resolution as the character resolution as described above. Then, the character image generation unit 517 performs quantization processing using the quantization table shown in FIG.

  That is, the quantization table of the background image uses a quantization table that stores the DC component for both the luminance difference and the color difference, thereby reducing block noise in a smooth portion of the image. The quantization table that stores the color difference component of the character image uses a quantization table that stores high frequencies as compared to the quantization table that stores the luminance of the background image. Is suppressed.

  In other words, the relationship shown in FIG. That is, in the quantization table for character images, both the luminance and the color difference are emphasized on the DC component, and in the quantization table for the background image, the luminance is standard and the color difference is emphasized on the frequency.

  The image file composition unit 518 outputs the binary image generation unit 512 (MMR), the black image generation unit 513 (MMR), the background image generation unit 516 (jpg), and the character image generation unit 517 (jpg). ) Are combined to generate one image data. A general-purpose format (such as a PDF file) may be used as the file format at this time. In addition, the image file composition unit 518 may output each of the four image data when the image file composition unit 518 delivers the image data to the input format conversion unit 135.

  The data i / f unit 506 outputs image data in a format to be output to the NIC 105 or outputs four image data to be output to the input format conversion unit 135.

  Returning to FIG. 1, the data i / f unit 134 outputs the image data input from the output format conversion unit 133 to the NIC 105 or the input format conversion unit 135.

  The input format conversion unit 135 converts the image data into an arbitrary format and outputs it.

  FIG. 19 is a block diagram showing the configuration of the input format conversion unit 135. As shown in FIG. 19, the input format conversion unit 135 includes a TIF format expansion unit 1801, a JPG format expansion unit 1802, a compression format expansion unit 1803, and an output selection unit 1804.

  The TIF format expansion unit 1801, the JPG format expansion unit 1802, and the compression format expansion unit 1803 expand the bit map of each format.

  The output selection unit selects one of the three formats and simultaneously converts the RGB data into YMCBk.

  For example, if the input image data is in the TIF format, the TIF format expansion unit 1801 expands it into bitmap data. In the case of the JPG format, the JPG format expansion unit 1802 expands the bitmap data. Furthermore, if it is a compression format, the compression format expansion unit 1803 expands it.

  The compression format developing unit 1803 includes an image file developing unit 1811, a black image developing unit 1812, a binary image developing unit 1813, a background image developing unit 1814, a character image developing unit 1815, and an image file combining unit 1816. A selection unit 1817 is included. The compression format expansion unit 1803 performs processing using the four image data input from the output format conversion unit 133.

  The image file development unit 1811 converts four files among the files generated by the compression format generation unit 505 shown in FIG. 5 into a black image development unit 1812, a binary image development unit 1813, a background image development unit 1814, a character image, and so on. The image data is output as image data corresponding to the expansion unit 1815.

  A binary image developing unit 1813 expands the MMR to expand the binary image and the mask image into a bitmap.

  The black image developing unit 1812 expands the MMR and develops a black character image into a bitmap.

  The background image development unit 1814 develops a JPG background image into a bitmap. The character image expansion unit 1815 expands the character image JPG into a bitmap.

  The composition selection unit 1817 selects a development and composition method according to the image separation mode input by the device i / f unit 136.

  The image file composition unit 1816 synthesizes one piece of bitmap data from the four developed bitmap data according to the composition method selected by the composition selection unit 1817.

  When the composition selection unit 1817 selects the standard mode as the image separation mode, the binary image development unit 1813 outputs a corrected binary image when there is a binary image and no mask image. Then, when the corrected binary image is input, the image file composition unit 1816 outputs the pixel of the image data that is the output result of the character image development unit 1815. Also, the image file composition unit 1816 outputs the pixel of the image data that is the output result of the background image development unit 1814 if the output of the binary image development unit 1813 is not a corrected binary image. Further, if the output result of the black image development unit 1812 is a black character, a black pixel is output as a pixel of the image data. One piece of image data is generated from the output pixels. Note that the resolution of characters and non-characters is the resolution of the binary image.

  On the other hand, when the composition selection unit 1817 selects the character mode as the image separation mode, the binary image development unit 1813 outputs a corrected binary image when there is a binary image. Then, when the corrected binary image is input, the image file composition unit 1816 outputs the pixel of the image data that is the output result of the character image development unit 1815. Also, the image file composition unit 1816 outputs the pixel of the image data that is the output result of the background image development unit 1814 if the output of the binary image development unit 1813 is not a corrected binary image. At this time, the mask image (background image) at the boundary between the corrected binary image and the mask image has character image information (character information on the background image is mixed by image compression). Replace the region with the image of the surrounding image. Further, if the output result of the black image development unit 1812 is a black character, a black pixel is output as a pixel of the image data. One piece of image data is generated from the output pixels. Note that the resolution of characters and non-characters is the resolution of the binary image.

  In the explanatory diagram shown in FIG. 12, when the image separation mode is the standard mode, the character “newly released” is determined as a design, so that it may be difficult to read when the character is small. On the other hand, when the image separation mode is the character mode, the “newly released” character is determined as a character, so that an appropriate process is performed as the character, and the character readability is improved.

  Thus, by generating image data based on the image separation mode selected by the user and the determination result of each area in the image data, it is possible to generate image data according to the user's preference. Is possible. Note that the generation of the image data is applicable not only when printing on paper but also when displaying on a monitor.

  The generated image data may be compressed by the compression / decompression processing unit 132 and stored in the HDD 106 in association with each signal, or output to the expansion processing unit 107 together with each signal via a general-purpose bus. The printing process may be performed.

  Returning to FIG. 1, the controller 104 sends the image data of the HDD 106 to the decompression processing unit 107 via the general-purpose bus.

  The decompression processing unit 107 decompresses the compressed image data into the original RGB 8-bit data, the character separation signal (2 bits), and the color area signal (1 bit), and sends them to the printer correction unit 108. The image data stored in the decompression processing unit 107 may be image data extracted for each area stored in the HDD 106 or image data already synthesized by the input format conversion unit 135. In the following description, a case where image data extracted for each area stored in the HDD 106 is input will be described.

  The printer correction unit 108 includes a halftone processing unit 141, a printer γ unit 142, a color correction processing unit 143, an edge amount detection unit 144, a reference storage unit 145, and a specifying unit 146, and corrects image data. Process.

  In accordance with the image separation mode, the reference storage unit 145 includes a character separation signal (including information (1 bit) indicating whether or not a character edge (edge region) and information (1 bit) indicating whether or not a character region) And a reference for converting from a color area signal (whether or not it is a color area) into a character edge area signal (“present” or “none”).

  FIG. 20 is a diagram illustrating a correspondence relationship of each signal stored in the reference storage unit 145 when the image separation mode is the standard mode. For example, in the case of the standard mode, the record 1901 is an edge area (the edge area is “present”), and is a picture area (the picture area is “present”). This indicates that the character edge area signal is “none”.

  FIG. 21 is a diagram illustrating a correspondence relationship of each signal stored in the reference storage unit 145 when the image separation mode is the character mode. For example, in the case of the character mode, the record 2001 is an edge region (the edge region is “present”), and when it is a design region (the design region is “present”), it is a color character edge region regardless of the color region. It is determined that the character edge area signal is “present”.

  As described above, in the present embodiment, in the area where the edge area is “present” and the pattern area is “present”, the character area is specified as the edge area, and the pattern area is specified when priority is given to the pattern. Identified as

  The specifying unit 146 converts the character separation signal (2 bits) into a character edge region signal (1 bit) according to the correspondence relationship stored in the reference storage unit 145 and the image separation mode input by the user. That is, the specifying unit 146 specifies whether each area is a character area based on the converted character edge area signal (1 bit).

  The color correction processing unit 143 converts the RGB image data into YMCBk data and replaces the “existing” character edge region signal and the “not” color region signal with black color Bk monochromatic data.

  Specifically, the color correction processing unit 143 converts the RGB image data into CMY data by a primary density masking method or the like except for the black character edge region. Thereafter, in order to improve color reproduction of the image data, the color correction processing unit 143 generates Bk data by performing UCR (under color removal) processing on the common part of the C, M, and Y data, and outputs the CMYBk data. .

  Further, the color correction processing unit 143 reduces the readability when the black character of the original is colored due to the RGB reading position deviation of the scanner in the black character edge region, or when there is an overlay position deviation when printing the YMCBk of the plotter. A signal corresponding to luminance only in the edge region is output as Bk single color data (C, M, and Y are unprinted data).

  The printer γ unit 142 performs γ correction processing on the image data in accordance with the character edge region signal (in other words, whether the region is an edge region) converted by the specifying unit 146 and the γ characteristic of the plotter. . The printer γ unit 142 according to the present embodiment selects γ with the contrast enhanced in the color character edge region and the black character edge region according to the γ characteristic, and in other cases (pattern), the γ is faithful to the input. Select. Then, γ correction processing is performed using the selected γ characteristic.

  As described above, in this embodiment, the contrast enhancement process is performed when the edge region is determined, and the γ correction process based on the faithful γ characteristic is performed when the edge region is determined.

  In the present embodiment, the example in which the γ correction processing is changed according to the type of each area specified by the specifying unit 511 has been described. However, the image processing is not limited to γ correction.

  The edge amount detection unit 144 detects a steep density change in the image data as an edge amount.

  The halftone processing unit 141 performs tone correction on the image data by performing quantization such as dither processing and error diffusion processing. In this way, correction processing and gradation conversion processing based on the light / dark characteristics of the plotter 109 are performed. In this gradation conversion process, image data is converted from 8-bit to 2-bit for each color using error diffusion or dither processing.

  The halftone processing unit 141 according to the present embodiment performs quantization such as dither processing according to the gradation characteristics and edge amount of the plotter according to the image processing mode input by the user. When performing quantization processing, the color character edge region and the black character edge region emphasize quantization and perform resolution processing with emphasis on resolving power, and the other (picture) perform quantization processing with emphasis on gradation. . This improves the legibility of the characters.

  FIG. 22 is a diagram showing the processing contents executed in each area in each image processing mode. As shown in FIG. 22, the processing content in each region changes according to the image processing mode according to the standard mode, character mode, or photo mode. In FIG. 22, fields 2101 and 2102 are different from the standard.

  Returning to FIG. 1, the plotter 109 is a transfer paper printing unit using a laser beam writing process, and draws 2-bit image data as a latent image on a photosensitive member. After image formation / transfer processing with toner, a copy image is printed on the transfer paper. Form.

  The NIC 105 transmits and receives data to and from the external PC terminal 130. Examples of data to be transmitted / received include image data.

  When operating as a distribution scanner that distributes image data to the external PC terminal 130 via the network, the image data is sent to the controller 104 via a general-purpose bus. The controller 104 performs color conversion processing, formatting processing, and the like. In the gradation processing, gradation conversion processing is performed according to the mode during the distribution scanner operation. In the format process, general-purpose image format conversion to JPEG or TIFF format is performed. Thereafter, the image data is distributed to the external PC terminal 130 via the NIC (network interface controller) 105.

  The NIC 105 has a function of transmitting the image data corrected by the printer correction unit 108 to another network printer or the like. That is, when the image data generated by the printer correction unit 108 is transmitted to the NIC 105 via a communication path (not shown), the NIC 105 transmits the image data to another device.

  Further, when operating as a printer that prints out from the external PC terminal 130 via the network, the controller 104 analyzes an image and a command for instructing printing from the data received by the NIC 105, and is ready to print as image data. Bitmap expansion is performed, and the expanded data is compressed to accumulate data. The accumulated data is written to the HDD 106 which is a large capacity storage device as needed. Bibliographic information is also written to the HDD 106 when image data is stored.

  A data flow for outputting image data from the external PC terminal 130 to the plotter will be described. A command instructed from the external PC terminal 130 is analyzed by a CPU (not shown) and written in the page memory 131. When the data i / f unit 134 receives image data, it outputs the image data to the input format conversion unit 135. Then, the input format conversion unit 135 expands the image data into bitmap data, compresses the compressed data into the compression / decompression processing unit 132, and writes the compressed data into the page memory 131. Thereafter, it is stored in the HDD 106. The image developed by the input format conversion unit 135 is natural image data in a format format such as JPG or TIFF.

  Next, the controller 104 sends the image data of the HDD 106 to the decompression processing unit 107 via the general-purpose bus. The decompression processing unit 107 decompresses the compressed image data to the original 8-bit data and sends it to the printer correction unit 108. In the printer correction unit 108, if the input is RGB, the color correction processing unit converts it into YMCBk data. Next, γ correction processing, halftone processing, and the like are performed independently for each YMCBk, and the plotter brightness characteristic correction processing and the tone number conversion processing are performed. In the tone number conversion process here, image data is converted from 8 bits to 2 bits using error diffusion or dither processing. The plotter is a transfer paper printing unit using a laser beam writing process. It draws 2-bit image data as a latent image on a photoconductor, and forms a copy image on the transfer paper after image formation / transfer processing with toner.

  In the multifunction device 100, a document is generally read by a scanner, image data is converted into digital data, and an image area of the document is classified into areas having different characteristics. Various image processing is performed on the image data according to the determination result as to which region the pixel of interest belongs to. This greatly improves the image quality of the output image.

  Next, a process of reading an original from the MFP 100 according to this embodiment and storing it in the HDD will be described. FIG. 23 is a flowchart illustrating a procedure of the above-described processing in the multifunction peripheral 100 according to the present embodiment.

  First, the scanner 101 reads a document and generates image data (step S2301). Next, the region extraction unit 121 of the scanner correction unit 102 extracts regions of visually different types from the image data (step S2302). The area extraction unit 121 outputs an image area separation signal and a color area signal for each pixel. In addition, the extracted areas are three types of areas: a black character edge area, a color character edge area, and other (photo area) picture areas.

  Thereafter, the scanner γ unit 122 and the filter processing unit 123 convert the image data (accumulated image data, edge region, and image region image data) from reflectance linear to density linear data and image region separation. Filtering switched to each pixel according to the signal is executed (step S2303).

  Then, the compression processing unit 103 performs compression processing on the image data (accumulated image data, edge region, and image region image data) (step S2304).

  Next, the controller 104 stores the image data in the HDD 106 (step S2305).

  The image data indicating the extracted area is stored in the HDD 106 by the processing procedure described above.

  Next, processing from image data stored in the HDD 106 in the multifunction peripheral 100 according to the present embodiment to processing by the controller 104 and printing by the plotter 109 will be described. FIG. 24 is a flowchart illustrating a procedure of the above-described processing in the multifunction peripheral 100 according to the present embodiment.

  First, the decompression processing unit 107 receives input of image data (stored image data, edge area, and image area image data) read from the HDD 106 by the controller 104, an image area separation signal, and a color area signal, and Data decompression processing is performed (step S2401). Thereafter, the printer correction unit 108 receives input of an image processing mode and an image separation mode from the controller 104. It is assumed that the image processing mode and the image separation mode are input from the input device 110.

  Next, the identification unit 146 converts the character separation signal (2 bits) into the character edge region signal (1 bit) based on the correspondence relationship stored in the reference storage unit 145 and the separation mode input to the user. Whether it is a character area or not is specified (step S2402).

  Then, the color correction processing unit 143, the printer γ unit 142, and the halftone processing unit 141 perform image processing on each region specified by the character edge region signal (1 bit) and the color region signal (step S2403). In particular, the printer γ unit 142 performs contrast enhancement when it is an edge region, and performs image processing corresponding to the region by performing γ correction processing with faithful γ characteristics when it is determined as a picture. To do.

  Thereafter, the plotter 109 performs print processing using the image data that has been subjected to image processing (step S2404).

  In MFP 100 according to the present embodiment, every time image data stored in HDD 106 is printed, image processing differs according to the input image processing mode and image separation mode. Processing can be executed.

  Next, a halftone dot detection process in the first halftone dot detection unit 605 of the binarization unit 511 of the output format conversion unit 133 according to the present embodiment will be described. FIG. 25 is a flowchart showing the above-described processing procedure in the first halftone dot detection unit 605 according to the present embodiment. In the present embodiment, a pixel to be processed is a target pixel.

  First, the first halftone dot detection unit 605 determines whether or not a block having a predetermined size including the target pixel matches the white pattern (step S2501). FIG. 26 is a diagram illustrating an example of a block representing a white pattern.

  If it is determined that the pattern matches the white pattern (step S2501: Yes), the first halftone dot detection unit 605 initializes the halftone dot count (step S2502). The parameters to be initialized are count_bk = tha_count, state = 0, SS [I] = 0 (note that tha_count: distance between white areas (threshold), SS [I]: information one line before).

  On the other hand, if it is determined that the pattern does not match the white pattern (step S2501: No), the first halftone dot detection unit 605 performs a halftone dot determination process (step S2503).

In step S2503, state is set to 1 under the following conditions.
・ SS [I] = 1
-The result one pixel before is a halftone dot.
・ When count_bk is 0.

  Further, in step S2503, when count_bk is 0, SS [I] is set to 1.

Thereafter, the first halftone dot detection unit 605 determines a halftone dot interval (step S2504). In step S2504, if state = 0 and count> tha_count_s (where tha_count_s is a distance (threshold) between halftone dot patterns on a non-halftone area), the following variables are initialized.
count_bk = tha_count
SS [I] = 0

In step S2504, any of count_bk, count_c, count_m, and count_y is 0 and count> tha_count_e (where tha_count_e is a distance (threshold) between halftone dot patterns on a non-halftone dot region). For example, the following variables are initialized.
count_bk = tha_count
state = 0
SS [I] = 0

  In step S2504, after the above determination and initialization are completed, count = count + 1 is performed.

  Next, the first halftone dot detection unit 605 performs halftone dot count using the halftone dot pattern (step S2505). FIG. 27 is a diagram showing an example of a halftone dot pattern. When the block including the target pixel matches the halftone dot pattern, the first halftone dot detection unit 605 sets count to 0 and count_bk to -1.

  Then, the first halftone dot detection unit 605 determines whether or not it is a halftone dot (step S2506). In this processing procedure, if state = 1, it is determined as a halftone dot.

  When the halftone dot is determined (step S2506: halftone dot), the first halftone dot detection unit 605 determines that the white pattern of step S2501 exists on both sides of the target pixel (12 pixels) on both sides and count_x is the initial value. For example, SS [I] = 0 is determined as a thin line (step S2507).

  Thereafter, the first halftone dot detection unit 605 sets state = 1 and outputs the result as a halftone dot (step S2509).

  On the other hand, if it is determined that it is not a halftone dot (step S2506: non-halftone dot), the first halftone dot detector 605 sets state = 0 and outputs the result as a non-halftone dot (step S2508).

  By the processing procedure described above, the first halftone dot detection unit 605 can detect halftone dots.

  Next, gray detection processing in the first gray detection unit 607 and the second gray detection unit 608 according to the present embodiment will be described. FIG. 28 is a flowchart showing the above-described processing procedure in the first gray detection unit 607 or the second gray detection unit 608 according to the present embodiment. In this processing procedure, the case of the first gray detection unit 607 will be described, but the second gray detection unit 608 also has the same processing procedure.

  First, the first gray detection unit 607 performs preprocessing (step S2801). Note that the variable MS shown below is the processing result up to one pixel, and is the number of white pixels after gray detection. The array SS [i] is the processing result of the previous line. Then, the first gray detection unit 607 compares the variable MS and the array SS [i] as preprocessing, and acquires a larger value from the processing result of the previous line and the processing result of the previous pixel. Note that a pixel to be processed is a target pixel.

  The first gray detection unit 607 matches whether or not the block including the target pixel matches the gray pattern (step S2802). FIG. 29 is a diagram illustrating an example of a gray pattern. That is, when the pixel value of the block including the target pixel is medium density and matches the gray pattern, the variable MS = 5 and S [i] is set as a gray pixel. Note that the pixel value having the medium density is an N-valued pixel value, and corresponds to a non-white pixel when the threshold value Dtah = 0.

  When not matching with the gray pattern (step S2802: No), the first gray detection unit 607 determines whether or not the target pixel is a white pixel when N-valued (step S2803). If it is determined that the pixel is a white pixel (step S2803: YES), the first gray detection unit 607 determines whether or not the variable MS> 0 (step S2804).

  If it is determined that the variable MS> 0 (step S2804: Yes), the first gray detecting unit 607 subtracts ‘1’ from the variable MS (step S2805).

  On the other hand, if it is determined that the variable MS> 0 is not satisfied (step S2804: NO), the first gray detection unit proceeds to step S2808.

  If it is determined that the pixel is not a white pixel (step S2803: NO), and after the process of step S2805 is completed, the first gray detection unit 607 determines whether or not the variable MS> 0 (step S2806).

  If it is determined that the variable MS> 0 is not satisfied (step S2806: NO, step S2804: NO), the target pixel is determined to be a non-gray pixel (step S2808).

  If the gray pattern is matched (step S2802: YES), and if MS> 0 is determined (step S2806: YES), the first gray detection unit 607 determines that the pixel of interest is a gray pixel (step S2807). ).

  Thereafter, the first gray detection unit 607 performs post-processing (step S2809). As post-processing, the first gray detection unit 607 sets SS [I] = MS-1 if the color background is white or the variable MS> 1. Furthermore, if the first gray detection unit 607 is a Bk pixel and MS> 0, SS [I] = MS−1 is set.

  Further, the first gray detection unit 607 performs bk count. For example, the number of continuous bk pixels is counted, and if the number of continuous is equal to or greater than the threshold thg_count1, it is determined that there is bk continuous. For example, when the threshold thg_count is 12 and the number of continuations is N, b-k continuation is N-thg_count + 1 times. The first gray detection unit 607 subtracts “1” from the MS when there is a continuous number.

  Next, an area determination process such as a black character in the determination unit 1109 in the black character determination unit 611 of the binarization unit 511 of the output format conversion unit 133 according to the present embodiment will be described. FIG. 30 is a flowchart showing a procedure of the above-described processing in the determination unit 1109 according to this embodiment. In this processing procedure, the description will be made assuming that the output of the 3-line OR unit 1102 is a black character edge, the determination result of the pattern determination unit 1103 is a pattern, and the determination result of the black determination unit 1104 is black.

  First, the determination unit 1109 determines whether the target pixel is a black character edge, a picture, or the other (step S3001). If it is determined that the edge is a black character, a black character area is set (step S3009). If it is determined as a picture, the target pixel is set as a picture area (step S3008).

  Next, the determination unit 1109 determines whether or not the target line including the target pixel has a high density (black) (step S3002). If the result of black pixel determination for the target line is not high density (black) (step S3002: No), the target pixel is set as an intermediate region (step S3007).

  If the determination unit 1109 determines that the target line has a high density (black) (step S3002: Yes), the determination unit 1109 determines whether the line immediately before the target line is a pattern (step S3003). If it is determined that the determination result one line before the line segment processing is a pattern area (step S3003: pattern), the determination unit 1109 sets the target pixel as the pattern area.

  Next, the determination unit 1109 determines whether or not the pixel is one picture before the target pixel (step S3004). If it is determined that the determination result one pixel before the target pixel is a pattern area, the target pixel is also set as a pattern area (step S3008).

  Then, the determination unit 1109 determines whether or not the previous line is a black character with respect to the target line including the target pixel (step S3005). If it is determined that the character is a black character, the pixel of interest is set as a black character region (step S3009).

  Next, the determination unit 1109 determines whether or not the pixel before the target pixel is a black character (step S3006). If it is determined that the character is a black character, the pixel of interest is set as a black character region (step S3009). If it is determined that the character is not a black character, the target pixel is set as an intermediate region (step S3007).

  Finally, the determination unit 1109 performs line segment processing (step S3010). Furthermore, if the color determination result is not a color and if high-density pixels are continuous for 128 pixels or more, the determination unit 1109 corrects the pattern area.

  With the processing procedure described above, the target pixel can be determined as an appropriate region such as a black character region.

  According to the MFP 100 described above, the image data of the read original is stored in the HDD 106 for each area such as a black character area and a picture area, and each area is determined according to the image processing mode and the image separation mode received from the user. After performing appropriate processing on the printing, the printing processing is performed. This eliminates the need to read the document every time the mode is changed, thus reducing the load on the user and improving the processing speed because it eliminates the need for area extraction that is required every time the document is read. Since printing is performed according to desired conditions each time, convenience is improved.

  Furthermore, in the multi-function device 100, determination criteria such as character emphasis and design emphasis can be selected, so that image data desired by the user can be generated.

  The hardware configuration of the controller 104 according to the MFP 100 described above includes, for example, a CPU, a north bridge (NB), a system memory (MEM-P), a south bridge (SB), and a local memory (MEM-C). , And. The scanner correction unit 102, the compression processing unit 103, the printer correction unit 108, and the expansion processing unit 107 may be stored in an ASIC connected to the controller 104. The multifunction device 100 has a configuration in which the controller 104 and the ASIC are connected by a PCIe (PCI express) bus. The MEM-P further includes a ROM (Read Only Memory) and a RAM (Random Access Memory).

  The CPU performs overall control of the multifunction peripheral 100, has a chip set made up of NB, MEM-P, and SB, and is connected to other devices via this chip set.

  The NB is a bridge for connecting the CPU to the MEM-P, SB, and PCIe, and includes a memory controller that controls reading and writing to the MEM-P and a PCIe master.

  The MEM-P is a system memory used as a memory for storing programs and data, a memory for developing programs and data, a drawing memory for printers, and the like, and includes a ROM and a RAM. The ROM is a read-only memory used as a memory for storing programs and data, and the RAM functions as a page memory 131 and can be written and read as a memory for developing programs and data, a drawing memory for printers, and the like. Memory.

  The ASIC is an integrated circuit (IC) for image processing having hardware elements for image processing.

  Note that the image processing program executed by the ASIC or the controller 104 of the MFP 100 according to the present embodiment is provided by being incorporated in advance in a ROM or the like.

  The image processing program executed by the MFP 100 according to the present embodiment is a file in an installable or executable format, such as a CD-ROM, a flexible disk (FD), a CD-R, a DVD (Digital Versatile Disk), or the like. You may comprise so that it may record and provide on a computer-readable recording medium.

  Further, the image processing program executed by the multifunction peripheral 100 of the present embodiment may be provided by being stored on a computer connected to a network such as the Internet and downloaded via the network. Further, the image processing program executed by the multifunction peripheral 100 of the present embodiment may be provided or distributed via a network such as the Internet.

  The image processing program executed by the multifunction peripheral 100 according to the present embodiment has a module configuration including the above-described units. As actual hardware, a CPU (processor) reads the image processing program from the ROM and executes it. As a result, the above-described units are loaded on the main storage device, and the above-described units are generated on the main storage device.

1 is a block diagram illustrating a schematic configuration of a multifunction machine according to a first embodiment. It is explanatory drawing which showed the pattern area | region, the edge area | region, etc. FIG. It is a block diagram which shows the structure of the area | region extraction part concerning 1st Embodiment. It is a block diagram which shows the structure of a comprehensive determination part. It is the block diagram which showed the structure of the output format conversion part. It is the block diagram which showed the structure of the binarization part. It is the figure which showed the example of the isolated point removal pattern. It is the figure which showed the relationship between a gray area | region and a character area. It is the figure which showed the example of the image data containing a white character. It is the figure which showed the example of the image data containing a black character. It is a block diagram which shows the structure of a black character determination part. It is the figure which showed the concept of the image data converted in an output format conversion part. It is the figure which showed the example of the reference | standard quantization table which preserve | saved DC component. It is the figure which showed the example of the quantization table which a background image generation part uses for a quantization process. It is the figure which showed the example of the 8x8 block in the image data used as a process target. It is the figure which showed the example of the reference | standard quantization table which preserve | saved the color difference component. It is the figure which showed the example of the quantization table which a character image generation part uses for a quantization process. It is the figure which showed the relationship between the classification of an image, and a quantization table. It is a block diagram which shows the structure of an input format conversion part. It is a figure which shows the correspondence of each signal in case the image separation mode is a standard mode which a reference | standard memory | storage part memorize | stores. It is a figure which shows the corresponding relationship of each signal in case a image separation mode is character mode which a reference | standard memory | storage part memorize | stores. It is the figure which showed the processing content performed in each area | region in each image processing mode. 4 is a flowchart illustrating a procedure of processing from reading an original to storing it in an HDD in the multifunction machine according to the first embodiment. 4 is a flowchart illustrating a processing procedure from image data stored in an HDD in the multifunction peripheral according to the first embodiment until processing is performed by a controller unit and then printing is performed by a plotter. It is a flowchart which shows the procedure of the halftone detection process in the 1st halftone detection part of the binarization part of the output format conversion part concerning 1st Embodiment. It is the figure which showed the example of the block showing a white pattern. It is the figure which showed the example of the halftone dot pattern. It is a flowchart which shows the procedure of the gray detection process in the 1st gray detection part concerning a 1st embodiment, or the 2nd gray detection part. It is the figure which showed the example of the gray pattern. It is a flowchart which shows the procedure of area | region determination processing, such as a black character, in the determination part in the black character determination part of the binarization part of the output format conversion part concerning 1st Embodiment.

Explanation of symbols

100 MFP 101 Scanner 102 Scanner Correction Unit 103 Compression Processing Unit 104 Controller 105 NIC
106 HDD
107 Decompression processing unit 108 Printer correction unit 109 Plotter 110 Input device 121 Area extraction unit 122 Scanner γ unit 123 Filter processing unit 130 External PC terminal 131 Page memory 132 Compression / decompression processing unit 133 Output format conversion unit 134 Data i / f unit 135 Input Format conversion unit 136 Device i / f unit 141 Halftone processing unit 142 Printer γ unit 143 Color correction processing unit 144 Edge amount detection unit 145 Reference storage unit 146 Selection unit 321 Filter 322 Edge extraction unit 322a Tri-leveling unit 322b Continuous black pixels Detection unit 322c White pixel continuous detection unit 322d Neighboring pixel detection unit 322e Isolated point removal unit 323 White region extraction unit 324 Halftone dot extraction unit 325 Color determination unit 325a Hue division unit 325b c memory 325c m memory 325d Memory 325e w Memory 325f Color pixel determination unit 326 General determination unit 326a Character determination unit 326b Expansion processing unit 326c Decoding unit 501 Color conversion unit 502 Resolution conversion unit 503 TIF format generation unit 504 JPG format generation unit 505 Compression format generation unit 506 Data i / F section 511 binarization section 512 binary image generation section 513 black image generation section 514 first resolution conversion section 515 second resolution conversion section 516 background image generation section 517 character image generation section 518 file composition section 518 image file composition section 601 Character resolution conversion unit 602 Adaptive binarization unit 603 Isolated point removal unit 604 N-value conversion unit 605 First halftone dot detection unit 606 Second halftone dot detection unit 607 First gray detection unit 608 Second gray detection unit 609 Character determination Part 611 Black character judgment part 6 21 threshold selection unit 622 binarization execution unit 1101 character determination unit 1102 3-line OR unit 1103 picture determination unit 1104 black determination unit 1105 first extraction unit 1106 second extraction unit 1107 first mirror 1108 second mirror 1109 determination unit 1801 TIF Format development unit 1802 JPG format development unit 1803 Compression format development unit 1804 Output selection unit 1811 Image file development unit 1812 Black image development unit 1813 Binary image development unit 1814 Background image development unit 1815 Character image development unit 1816 Image file synthesis unit 1817 Composition Select part

Claims (8)

Image data input means for inputting image data;
Recognizing means for recognizing the type of each area included in the image data with respect to the image data;
Storage means for storing the image data and the type of each area recognized by the recognition means;
Based on the output setting of the image data, from the type of each region stored in the storage means, a specifying unit for specifying one type,
Image processing means for performing image processing suitable for the specified type on the image data stored in the storage means;
An image processing apparatus comprising: The recognizing unit further extracts, from the image data, an edge region including characters and a pattern region including a figure or a drawing,
The storage means further stores the image data of the edge region and the image data of the pattern region,
The image processing means performs different image processing on the image data of the edge region and the image data of the pattern region;
The image processing apparatus according to claim 1. The recognizing means recognizes an edge area including characters and a pattern area including a figure or a picture from the image data,
The specifying unit specifies the edge region as a type to be applied to the image processing when giving priority to characters, and specifies the picture region as a type to be applied to the image processing when giving priority to a design. thing,
The image processing apparatus according to claim 1, wherein:   4. The image processing apparatus according to claim 1, further comprising: an image output unit that forms the image data processed by the image processing unit on a sheet and outputs the image. 5. .   The image processing apparatus according to claim 1, further comprising: a transmission unit that transmits the image data image-processed by the image processing unit to an external device.   The image processing apparatus according to claim 1, further comprising display means for displaying the image data image-processed by the image processing means. An image data input means for inputting image data;
A recognition step for recognizing the type of each area included in the image data with respect to the image data;
A storage step of storing the image data and the type of each area recognized by the recognition unit in a storage unit;
A specifying step of specifying one type from the type of each area stored in the storage unit based on the output setting of the image data;
An image processing step in which image processing means performs image processing suitable for the specified type on the image data stored in the storage means;
An image processing method comprising: An image data input step for inputting image data;
A recognition step for recognizing the type of each area included in the image data with respect to the image data;
A storage step of storing the image data and the type of each area recognized by the recognition unit in a storage unit;
Based on the output setting of the image data, a specifying step of specifying one type from the type of each area stored in the storage unit;
An image processing step for performing image processing suitable for the specified type on the image data stored in the storage unit;
An image processing program for causing a computer to execute.

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