JP2007043572A - Image processor and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processor capable of highly precisely detecting the middle part of a character, and to provide a program. <P>SOLUTION: A character edge area and a color area are separated in image area from inputted image data so as to be precisely detected. When the middle part of the character is detected, the image data filtered used. Consequently, a character determining means 705 defines only a dark part as "the middle part of the character" which means the inner side of the character edge, i.e., the inner part of a character line width, through the use of not dot information but data filtered (smoothed since the area is not the character edge area). Thus, the determination result of the character constituted with the dots is reduced so as to highly precisely detect the middle part of the character. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing apparatus used for an image forming apparatus such as a color digital copying machine or a scanner distribution apparatus, and more particularly to an image processing apparatus and program for performing appropriate image processing on black characters.

  In recent years, copying machines have been networked, and the functions of copying machines can be used from other terminals connected to the network. For example, a function for distributing image data (for example, image data read from a document by a scanner unit) input to a copying machine to other terminals such as a computer connected to a digital color copying machine over a network has been proposed. Has begun to be utilized.

  In the example of distributing scanned image data when this distribution function is used, various processing conditions are set from the copying machine side or the computer terminal that is the distribution destination, and the scanner is operated and read in accordance with the set processing conditions. The document image data is subjected to a predetermined process such as conversion and transferred to a distribution destination.

  Patent Document 1 can be shown as a conventional example related to image reading and image processing performed in accordance with the setting of processing conditions when this distribution scanner function is used.

  Patent Document 1 discloses a system equipped with an expansion box based on the architecture of a general-purpose computer system in order to expand functions as a print server or a scanned image server in an image forming apparatus such as a copying machine. Proposed. Here, it is shown that the scan image is stored in the hard disk device in the expansion box, the image file stored therein is shared by a computer system connected to the network, and its use can be realized by each server function.

  Japanese Patent Application Laid-Open No. 2004-151561 discloses scan image processing when a scan box function (one of functions for distributing a scan image to a client computer) is used. Here, the document reading and the scanned document image processing are performed according to the processing conditions set by the operation input. However, since the scan box function is used when the print output is not necessarily planned, the print output Without generating the YMCK data format required for the scan, that is, omitting the color coordinate conversion of the scanned image from the RGB system to the YMCK system, gradation correction, image data compression processing, etc. RGB data is stored in the scan box. Thereafter, the client computer of the network extracts the image data from the scan box as RGB data at the time of storage, and transfers it to a local disk or the like that is the storage destination of the image data. In the client computer, the scanned image can be viewed on a monitor / display based on the transferred RGB data.

  On the other hand, in recent years, with the spread of color image processing apparatuses such as color printers and color copying machines, improvement in output quality of color images has been demanded. For example, if the original is only black, yellow, magenta, cyan, and black signals are generated as black reproduction signals. Bleeding may occur and appear blurred.

  Therefore, in order to prevent such a decrease in output quality, a method has been proposed in which characteristics of black characters and black lines in an image are utilized by switching filter processing for image correction and image quality adjustment. Examples of the switching of the filter processing include switching according to the black character edge region, the color character edge region, and the photograph region, which are the image region separation processing results.

JP 2000-333026 A

  By the way, as the switching of the filter processing by the image area separation signal as described above, sharpening processing is performed with emphasis on legibility in a character edge area (black character edge area and color character edge area), and in a photographic area, an image is displayed. A sharp density change in the data is used as an edge amount, and smoothing processing or sharpening processing is performed according to the edge amount. The sharp edges are sharpened to make the characters in the picture easier to read. As described above, the image quality of the output image can be greatly improved by performing various image processing on the image data according to the image area separation result as to which region the pixel of interest belongs to.

  However, in the image area separation process, there is a problem that a character composed of halftone dots may or may not become a character edge area when the halftone dot area is small.

  In addition, in an image processing apparatus that stores RGB data after scan image processing in a scan box as described in Patent Document 1, image area separation processing is performed on RGB data of a scan image. For this reason, there is a problem that a high-density region in the pattern is detected as a character when detecting “character inside” meaning the inside of the character edge, that is, within the character line width.

  In particular, since the leading end of a 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 determination of whether the character is halfway is obtained. .

  The present invention has been made in view of the above, and an object of the present invention is to provide an image processing apparatus and program capable of detecting a character with high accuracy.

  In order to solve the above-described problems and achieve the object, the invention according to claim 1 is characterized in that character edge region separation means for separating a character edge region from input image data, and color from input image data. A color region separating unit for separating an image region, a filter processing unit for performing a filtering process according to an image region separation result in the character edge region separating unit and the color region separating unit, and a filtering process performed by the filter processing unit. Image storage means for storing the executed image data and the image area separation result in a storage section; and a high density area detection means for detecting a high density area for the image data stored in the storage section; Detected by the intermediate density area detecting means for detecting an intermediate density area for the image data stored in the storage unit and the high density area detecting means. By referring to the image state of the peripheral pixels in accordance with the high density area and the intermediate density area detected by the intermediate density area detecting means, it is determined whether the character means the inside of the black character and the character edge, that is, the character line width. Character determination means.

  According to a second aspect of the present invention, in the image processing apparatus according to the first aspect, the high density area detecting means, the intermediate density area detecting means, and the character determining means are stored in the storage unit. This is executed again when the image data is distributed to other terminals connected to the network.

  According to a third aspect of the present invention, in the image processing apparatus according to the first or second aspect, an image formed based on the image data stored in the storage unit is formed on a transfer sheet and output. Forming means is further provided.

  According to a fourth aspect of the present invention, there is provided a program for separating a character edge area from a character edge area from input image data, and a color area separation function for separating a color area from input image data. A filter processing function for performing filter processing according to an image region separation result in the character edge region separation function and the color region separation function, and the image data and the image region subjected to the filter processing by the filter processing function An image accumulation function for accumulating the separation results in the storage unit, a high density area detection function for detecting a high density region for the image data accumulated in the storage unit, and the image accumulated in the storage unit An intermediate density area detection function for detecting an intermediate density area for the data; and the high density area and the intermediate density detected by the high density area detection function. A character determination function that determines whether a character means a black character and a character that is inside the character edge, that is, within the character line width, by referring to the image state of the peripheral pixel according to the intermediate density region detected by the region detection function. Let it run.

  The invention according to claim 5 is the program according to claim 4, wherein the high density area detection function, the intermediate density area detection function, and the character determination function are the image data stored in the storage unit. Is executed again to distribute to other terminals connected to the network.

  According to the first aspect of the present invention, the character edge region and the color region are separated from the input image data, so that the character edge region and the color region can be detected with high accuracy. By using the image data, it is possible to make only the dark part a character by using the data after filtering (smoothed because it is not a character edge region) instead of the halftone information. Mixing of character determination results is reduced, and it is possible to detect characters with high accuracy.

  Further, according to the invention according to claim 2, since the determination of characters necessary for distribution is performed after the image data is stored in the storage unit, it is not necessary to store the determination result of characters unnecessary for copying or the like. There is an effect that the data of the stored image is reduced.

  According to the invention of claim 3, the image forming unit is provided, the character edge region and the color region are performed first, and processing unique to the distribution (high density region detecting unit, intermediate density region detecting unit, and character Since the determination unit) is performed later, an effect is achieved in that it is possible to perform a scanner copy simultaneous operation and the like.

  According to the invention of claim 4, it is possible to detect, and for the detection of characters, by using the image data after the filtering process, not the halftone dot information but the filtering process (since it is not the character edge area, it is smoothed). Data) can be used to make only the dark part a character, so that the mixed judgment result of the character composed of halftone dots is reduced and the character can be detected with high accuracy. There is an effect.

  According to the invention of claim 5, the character edge region and the color region are performed first, and processing unique to the distribution (high density region detection function, intermediate density region detection function, and character determination function) is performed later. As a result, it is possible to perform a scanner copy simultaneous operation and the like. In addition, since the determination of characters necessary for distribution is performed after the image data is stored in the storage unit, it is not necessary to store the determination result of characters that are not necessary for copying or the like, so that the amount of stored image data is reduced. Play.

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

  An embodiment of the present invention will be described with reference to FIGS. In this embodiment, as an image processing apparatus, a copy function, a facsimile (FAX) function, a printer function, and a function for distributing an input image (read original image or an image input by a printer or FAX function) are combined. An example in which a digital color multifunction peripheral, which is a multifunction peripheral, is applied will be described.

  FIG. 1 is a block diagram showing a system configuration of a digital color multifunction peripheral 100 according to the present embodiment. A digital color multifunction peripheral 100 shown in FIG. 1 includes a main controller 117 having a microcomputer configuration, and the main controller 117 centrally controls the entire digital color multifunction peripheral 100. The digital color multifunction peripheral 100 is roughly divided into an engine unit 101 and a printer controller unit 102.

  First, with reference to FIG. 1, the operation of each unit of the digital color multifunction peripheral 100 will be described along the flow of image data during copying.

  The entire engine unit 101 is controlled by an engine controller 110. In this engine unit 101, a reading unit 111 is an image reading unit that reads an image of a document, and the image of the document is read as image data (reflectance linear) color-separated into R, G, and B, and a scanner correction unit. 112. The scanner correction unit 112 performs color conversion from the RGB signal unique to the device read by the reading unit 111 to the RGB signal in the standard color space. Here, the conversion to the standard color space is performed in order to reuse the image data.

  As shown in FIG. 2, in the scanner correction unit 112, RGB image data is subjected to image area separation processing by the image area separation unit 201, scanner γ correction processing by the scanner γ unit 202, filter processing by the filter processing unit 203, and original document. A document type determination process is performed by the type determination unit 204.

  An image area separation unit 201, which is a character edge area separation unit and a color area separation unit, classifies an image area (image area) of a document into areas having different characteristics (areas such as characters, line drawings, and photographs) (image area separation). ) In the present embodiment, a black character edge region, a color character edge region, and the other (photo region) are separated by a method disclosed in Japanese Patent Laid-Open No. 2003-259115. By performing image area separation in this way, an image area separation signal (character edge area, color area) is given to the image data for each pixel. Then, based on such an image area separation signal, the image area (image area) of the original is a black character edge area (character edge area and not a color area), color character edge area (character edge area and color area). Classified as a photographic area (other than the above). Here, FIG. 3 is an explanatory view showing a character edge region into which image areas are separated. As shown in FIG. 3, the inside of the character edge region, that is, the character line width, is a character medium region to be described later.

  A scanner γ unit 202 is an 8-bit input and 8-bit output LUT (Look Up Table) for each RGB channel, and converts image data from reflectance linear to density linear data.

  A filter processing unit 203 serving as a filter processing unit switches the filter processing according to an image area separation signal. In the character edge region (black character edge region and color character edge region), sharpening processing is performed with emphasis on legibility. In the photograph area, a sharp density change in the image data is used as an edge amount, and smoothing processing or sharpening processing is performed according to the edge amount. The sharp edges are sharpened to make the characters in the picture easier to read. As described above, the image quality of the output image can be greatly improved by performing various image processing on the image data according to the image area separation result as to which region the pixel of interest belongs to.

  The document type determination unit 204 uses a document determination block disclosed in Japanese Patent Laid-Open No. 2000-324338. Specifically, it is determined whether the document is a text document, a chromatic document, a photographic paper photograph, or a printed photograph, and it is determined whether or not only a character document is a color document by using these four feature amounts. Here, a text-only document is a document in which only characters are present in the document. Under the above-described determination conditions, a document with characters (present), a photographic paper document (none), and a printed photograph document (none) Is the time. The color original is a chromatic original (present). Note that a pattern such as a copy original or an ink jet original is subjected to gradation processing, and is classified as either a photographic paper photograph or a printed photograph original. This document type determination result is recorded as bibliographic information when image data is stored in a hard disk (HDD) 118 serving as a storage unit.

  The RGB 8-bit image data, character edge region signal (1 bit), and color region signal (1 bit) processed by the scanner correction unit 112 are compressed by the compression processing unit 113. The compressed image data is sent to the printer controller 115 via the general-purpose bus 114. Note that if the bandwidth of the general-purpose bus 114 is sufficiently wide and the capacity of the stored hard disk (HDD) 118 is large, data may be handled in an uncompressed state.

  The printer controller 115 includes a semiconductor memory 116 that stores image data. The semiconductor memory 116 stores the transmitted image data under the control of the main controller 117. Also, the hard disk (HDD) 118 serving as a storage unit stores the image data stored in the semiconductor memory 116 and the document size determined by the image size and document type determination unit 204. This is for avoiding rereading the original again even when the paper at the time of printing out by the digital color multifunction peripheral 100, that is, when printing is not normally completed, and for electronic sorting. In recent years, not only this, but also a function has been added to store scanned originals and re-output them when necessary. That is, the image data is once developed in the semiconductor memory 116 and stored in the hard disk 118 (image storage means).

  When outputting image data, the image data in the hard disk 118 serving as a storage unit is once developed in the semiconductor memory 116 of the printer controller 115 and then sent to the engine unit 101 via the general-purpose bus 114. Then, the color / monochrome multi-value data fixed length expander 119 of the engine unit 101 expands the transmitted image data into original RGB 8-bit data, a character edge region signal (1 bit), and a color region signal (1 bit), The data is sent to the printer correction unit 120. In FIG. 1, the color / monochrome multi-value data fixed length compressor 113 and the color / monochrome multi-value data fixed length decompressor 119 are shown, but general-purpose compressors and decompressors may be used instead of the fixed length. As described above, the image data stored in the hard disk 118 is once developed in the semiconductor memory 116 before being output to the engine unit 101. The writing speed and the reading speed of the hard disk 118 are not constant and irregular. Because. The RGB image data read from the hard disk 118 is converted into a YMCBk color signal corresponding to the writing control unit 121 and the image forming unit 122 by the printer correction unit 120, and a portion that is a character edge region signal and not a color region signal is It is replaced with Bk monochrome data as black characters.

  As shown in FIG. 4, the printer correction unit 120 includes a color correction processing unit 401 that converts RGB 8-bit data into YMCBk color signals, and a printer that performs γ correction according to the γ characteristics of the image forming unit 122. a gamma unit 402, a halftone processing unit 403 that performs gradation correction by performing quantization such as dither processing and error diffusion processing, an amount detection unit 404 that detects a sharp density change in image data as an edge amount, It has.

  The color correction processing unit 401 converts R, G, and B data into C, M, and Y data by a primary density masking method or the like except for the black character edge region. In order to improve the color reproduction of the image data, the common portion of the C, M, Y data is subjected to UCR (additional color removal) processing to generate Bk data, and the C, M, Y, Bk data is output. Here, since the black character edge area is not legible if the black character of the original is colored due to the RGB reading position deviation of the reading unit 111 or the overlapping position deviation in the YMCBk printer of the image forming unit 122 is not legible, only the black character area has luminance. Are output as Bk single color data (C, M, and Y are unprinted data).

  The printer γ unit 402 processes each color of YMCBk according to the frequency characteristic of γ.

  The halftone processing unit 403 performs quantization such as dither processing according to the gradation characteristics and edge amount of the image forming unit 122. When performing the quantization process, it is also possible to emphasize the controller character of the black character by performing a black character signal (a black character extraction process described later). This improves the legibility of characters.

  The image forming unit 122 serving as an image forming unit is a transfer paper printing unit using a laser beam writing process. The image forming unit 122 draws 2-bit image data as a latent image on a photosensitive member, and after image forming / transfer processing with toner, Form a copy image. As the printing method of the image forming unit 122, various methods such as an ink jet method, a sublimation type thermal transfer method, a silver salt photography method, a direct thermal recording method, and a melt type thermal transfer method can be used in addition to the electrophotographic method.

  In the above description, the case where image data compressed in the RGB color space subjected to image processing for copying is stored in the hard disk 118 has been described. Here, the image data stored in the hard disk 118 is image data of a certain color space system read as a copy image by the digital color multifunction peripheral 100 or the like. The certain color space may be a device-dependent (depending on device type (device characteristic)) color space (Yuv, CMY), or a device independent (device type (device characteristic)). It may be an independent color space (sRGB). When these certain color space signals are transmitted to other devices via the network, they are corrected to the same color space that can be used as is with other devices. A certain color space is, for example, a standard sRGB space or Lab space, or a dedicated color space system that can be shared between different devices.

  Next, the operation of each unit of the digital color multifunction peripheral 100 when operating as a distribution scanner that distributes data stored in the hard disk 118 to the external PC 126 via the network will be described.

  The network interface controller (NIC) 124 is an interface for connecting the digital color multifunction peripheral 100 to a network such as a LAN to which the external PC 126 is connected.

  As described above, the hard disk 118 stores RGB image data that has been subjected to scanner correction, that is, that has been subjected to image processing for copying, and the document size determined by the image size and document type determination unit 204. Has been.

  The image data stored in the hard disk 118 is sent to the printer controller 115 and developed in the semiconductor memory 116, where gradation conversion processing, formatting processing, and the like are performed. 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 126 via the NIC 124.

  Here, FIG. 5 is a block diagram showing the configuration of the printer controller 115. As shown in FIG. 5, the printer controller 115 includes a semiconductor memory 116, a compression / decompression processing unit 501, an output format conversion unit 502, an input format conversion unit 503, and a data I / F 504. The operation of each unit will be described along the flow of data for distributing the image data expanded in the semiconductor memory 116 to the external PC 126. The compression / decompression processing unit 501 expands the compressed image data expanded in the semiconductor memory 116 to the original 8-bit data for each color, and outputs the data to the output format conversion unit 502. The output format conversion unit 502 performs color conversion of RGB data to sRGB data, which is a standard color space, and simultaneously performs general-purpose image format conversion to JPEG or TIFF format. The data I / F 504 outputs data from the output format conversion unit 502 to the NIC 124. The printer controller 115 performs appropriate image format processing for distribution in this way, and distributes it to the external PC 126 through the NIC 124.

  When the image processing apparatus 100 operates as a printer that prints out from the external PC 126 via the network, when data is input from the network interface controller (NIC) 124 via the data I / F 504, input format conversion is performed. The unit 503 analyzes the image and the command for instructing the print from the input data, and decompresses the bitmap so that it can be printed as image data. The compression / decompression processing unit 501 compresses the decompressed data and stores the data in the semiconductor memory 116. To accumulate. Data stored in the semiconductor memory 116 is written to a large-capacity hard disk 118 as needed. The input image data is a natural image in a general-purpose image format such as JPEG or TIFF format.

  Note that the flow of image data is not particularly shown for FAX, but the FAX controller 123 controls the FAX function of the image processing apparatus 100 to transmit and receive image data to and from a predetermined network such as a telephone line. The monochrome binary variable length lossless compression data decompressor 123a compresses and decompresses data to be transmitted and received.

  As described above, the digital color multifunction peripheral 100 stores the RGB image data of the scanned image in the hard disk 118, and converts the image format for the stored data when printing or distributing the stored data. Yes. That is, in the digital color multifunction peripheral 100 of the present embodiment, the image data accumulated in color can be output as it is in color, or converted into monochrome and output.

  For example, when image data accumulated in color is converted into monochrome and printed out, the color correction processing unit 401 of the printer correction unit 120 shown in FIG. 4 performs conversion from color to monochrome. Here, since paper output is intended, RGB → Bk (black) conversion is performed. In the case of distribution, the luminance Y is obtained from the original RGB value, and this is reflected in the converted RGB.

  Here, the output format conversion unit 502 of the printer controller 115 will be described. FIG. 6 is a block diagram illustrating a configuration of the output format conversion unit 502. As shown in FIG. 6, the output format conversion unit 502 includes a color conversion unit 601, a resolution conversion unit 602, a TIFF format generation unit 603, a JPEG format generation unit 604, a compression format generation unit 605, a data I / O F606.

  The color conversion unit 601 performs data conversion from RGB data to sRGB data. The resolution conversion unit 602 performs pixel density conversion such as 300 dpi and 200 dpi on the data converted into sRGB by the color conversion unit 601. In this embodiment, the pixel density when converted at 300 dpi will be described. Each format generation unit (TIFF format generation unit 603, JPEG format generation unit 604, compression format generation unit 605) converts the image whose resolution has been converted by the resolution conversion unit 602 into each format. The data I / F 606 outputs a format to be output to the NIC 124.

  Here, the compression format generation unit 605 will be described. The compression format generation unit 605 includes a binarization unit 607, a black image generation unit 608, a binary image generation unit 609, a first resolution conversion unit 610, a second resolution conversion unit 611, and a background image generation unit 612. And a character image generation unit 613 and an image file composition unit 614.

  The binarization unit 607 outputs binary data and black character data of the character area and the non-character area based on the lightness and darkness of the image density. The binary image generation unit 609 performs MMR compression that is reversible conversion on the binary data output from the binarization unit 607. The black image generation unit 608 performs MMR compression that is reversible conversion on the black character data output from the binarization unit 607. The first resolution conversion unit 610 and the second resolution conversion unit 611 perform resolution conversion on the image data to reduce the resolution (150 dpi). In the background image generation unit 612, JPEG compression is performed on the image data in the region that has become the character region in the binarization unit 607 by rewriting lossless compression of image data having a constant value corresponding to white. The character image generation unit 613 performs JPEG compression of image data of a region that has become a sentence background region by rewriting lossless compression of image data of a certain value. The reason why the character portion is set to a constant value for the background image is that the compression is improved by setting the constant value. Also for the character image, the background image is set to a constant value in order to improve compression.

  Note that the resolution of the resolution conversion in the first resolution conversion unit 610 and the second resolution conversion unit 611 may be about 75 dpi because the character image does not require as much resolution as the background image. If the bibliographic information is a document containing only characters, a JPEG file is created with a resolution of 75 dpi for both the background image and the character image. The resolution of characters is reduced because the resolution of the characters is guaranteed by the MMR resolution, so even if the dpi of the JPEG image is dropped, gradation degradation does not matter. The file size can be reduced by reducing the resolution. In the present embodiment, the file size is reduced by reducing the image resolution. However, the file size may be reduced by reducing the image quality such as the number of gradations other than the resolution of the image. Since there is a description that only text is included in the stored data as bibliographic information, it is possible to increase the compression ratio of the text-only document relative to the image data after the stored data.

  The image file composition unit 614 outputs the binary image generation unit 609 (MMR), the black image generation unit 608 (MMR), the background image generation unit 612 (JPEG), and the character image generation unit 613 (JPEG). 4) is converted into one file. As the file format at this time, a general-purpose format (such as a PDF file) may be used.

  Here, the binarization unit 607 will be described in detail with reference to FIG. The binarization unit 607 performs binarization by extracting a plurality of feature amounts. The following processes are sequential processes. When one process is completed, the adjacent pixel is processed, and one line is processed from the beginning of the next line, and the process is continued at the end of the image. It is assumed that the RGB image data becomes black when the number increases and becomes white when the number decreases.

  As shown in FIG. 7, the binarization unit 607 includes a character resolution conversion unit 701, a binarization unit 702, a mask unit 703, a black extraction unit 704, and a character determination + character determination unit 705.

  The character resolution conversion unit 701 performs resolution conversion (300 dpi) at the same resolution as the character edge region and color region signal, which is the data expanded by the compression / decompression processing unit 501, and converts the image data and the pixel density. Make the same. The output here is character edges and colors.

  The binarization unit 702 includes an adaptive binarization unit 706 that binarizes by changing a threshold value for each line, and a first isolated point removal unit 707 that removes isolated points from the output of adaptive binarization. The adaptive binarization unit 706 detects the color of the edge and changes the threshold value for each line in order to extract the color ground character and the white ground character. As shown in FIG. 708 and a binarization unit 709.

As shown in FIG. 9, when the following condition is satisfied with the reference pixels ▽ Δ of two pixels on the left and right with respect to the main scanning direction of the target pixel ○, it is determined as a binarization threshold target pixel.
(○-▽)> th2 or (○-△)> th2
Note that th2 is a fixed value determined by the input characteristics of the image. The threshold value calculation unit 708 obtains an average of the binarization target pixels independently for RGB in one line, and uses the averaged value as a threshold value. In addition, when there is no binarization target pixel in one line, the threshold calculation unit 708 sets a predetermined value as the threshold. The binarization unit 709 determines black (on) and not black (on) if at least one RGB value of the input image exceeds the threshold with respect to the threshold obtained by the threshold calculation unit 708. Time is output as white (off). Note that the line memory 710 in FIG. 8 is that the processing is shifted by one line when attempting to binarize based on the result calculated by the threshold calculation unit 708. Therefore, one line memory is delayed by one line so as not to shift. Yes. In this way, by changing the threshold value for each line, it is possible to satisfactorily extract characters on the color ground and white ground without depending on the background color or background color.

  The first isolated point removing unit 707 removes the isolated point because there are many isolated points in the result of the adaptive binarization. More specifically, when the pattern matches the pattern of FIG. 10, the isolated point is removed by inverting the target pixel.

  Next, the mask unit 703 that is an intermediate density region detection unit will be described. As shown in FIG. 7, the mask unit 703 includes an N-value conversion unit 711, a first halftone dot detection unit 712, a second halftone dot detection unit 713, a first gray detection unit 714, a second gray detection unit 715, and a background detection. Part 716.

The N-value conversion unit 711 commonly uses a halftone dot detection feature and a gray detection feature, which will be described later, as N value values. Data with a small RGB difference (bk) is a black character when the value is larger than thabk, and data with a large RGB difference is divided into six colors of YMCBGR and the thresholds (thay, tham, thac, thab, thag) for each hue. , Thar) is divided and binarization processing is performed, and binarization processing is performed with a dark color as an active pixel (character). The method of dividing the hue may be simply based on the magnitude relationship of RGB or may be determined by the ratio of RGB colors. This is determined by the characteristics of the input image. However, the output result is held for each hue. Here, it is defined as follows. In addition, () shows a bit display.
Dtah = 0 (000): Not applicable
Dtah = 1 (001): Yellow
Dtah = 2 (010): Magenta
Dtah = 3 (011): Red
Dtah = 4 (100): Cyan
Dtah = 5 (101): Green
Dtah = 6 (110): Blue
Dtah = 7 (111): Black Further, the N-value conversion unit 711 also binarizes the white level. Data with a small RGB difference (bk) is a white pixel when the value is smaller than thbbk, and data with a large RGB difference is divided into six hues of YMCBGR, and threshold values (thby, thbm, thbc, thbb, The binarization process is performed separately for thbg and thbr), and the binarization process is performed with a light color as an active pixel (white pixel). Moreover, what is contained in black and further extracted from a black (dark) color is made dark black and used when extracting black. Further, the N-value conversion unit 711 performs background extraction. The background is the same as the white level, but the threshold is an intermediate value between the white level and the character threshold. The relationship between the base area, the gray area, and the character area is as shown in FIG. There is a density range that spans two areas, the darker of the background area and the thinner gray area. The reason is that both the background area and the gray area are determined by pattern matching unless there is an area of a certain size, so if there is no overlap, the background area and the density area of the uniform image near the gray determination This is also to prevent any of the background area and the gray area from being lost when the background area and the gray area are straddled.

  In the first halftone dot detection unit 712, the halftone dot shape is eliminated by the smoothing process in the fine dot in the scanner correction unit 112, but the rough halftone dot such as a newspaper photograph is sufficiently smoothed. The dot shape of the halftone dot remains, and the object is to detect this rough halftone dot. Here, halftone dot pattern matching is performed. Here, when Dtah ≠ 0, a black pixel is set, and an N-valued white pixel is set as a white pixel. The halftone dot detection process in the first halftone dot detection unit 712 will be described with reference to the flowchart of FIG. As shown in FIG. 12, first, MS which is the processing result of one pixel and is a halftone dot count value is compared with SS [i] which is the processing result of one line before (step S1). If SS [i] is also large (Y in step S1), MS is replaced with SS [I] (step S2), and the process proceeds to step S3. On the other hand, when SS [i] is not larger than MS (N in step S1), the process proceeds to step S3 as it is. That is, the larger value of the result of the previous line and the processing result of the previous pixel is obtained.

  In the subsequent step S3, it is determined whether or not the pattern is a white pattern by pattern matching of white pixels shown in FIG. If the white pixel matches the pattern (Y in step S3), MS is set to 0, S [i] = 0, and it is used in the next line of S [i] (step S4), and the non-halftone dot A pixel is set (step S8). On the other hand, if the patterns do not match (N in step S3), the process proceeds to step S5.

  In step S5, it is determined whether or not the pattern is a halftone dot pattern by the halftone dot pattern matching shown in FIG. In FIG. 14, ● is a black pixel, and ◯ is a non-black pixel. If it matches the halftone dot pattern (Y in step S5), MS is incremented by 1 (step S6), and the process proceeds to step S7. On the other hand, if it does not match the halftone dot pattern (N in step S5), the process proceeds to step S7 as it is. In order to improve halftone dot detection accuracy, the accuracy may be increased by increasing the condition of including several white pixels in non-black pixels.

  In step S7, it is determined whether the pixel is a halftone pixel. Specifically, S [i] = MS is used, and S [i] is used in the next line to determine whether MS> 5. If MS> 5 (Y in step S7), a halftone dot pixel is set (step S9). If MS> 5 is not satisfied (N in step S7), a non-halftone dot pixel is set (step S8).

  Finally, the halftone dot count value MS is set to the processing result SS [j] one line before (step S10), and the processing is terminated.

  Next, the second halftone dot detection unit 713 will be briefly described. The first halftone dot detection unit 712 processes image data in the forward direction, but the second halftone dot detection unit 713 performs processing in the reverse direction. In the first halftone dot detection unit 712, the tip of the halftone dot is reversely read so that the halftone dot becomes a halftone dot.

  In this way, in the halftone dot detection in the first halftone dot detection unit 712 and the second halftone dot detection unit 713, if there is a halftone dot pattern between a white pattern and a white pattern, a halftone dot is detected. This is because characters are generally white ground characters, and white ground characters are rarely erroneously detected because the halftone dot pattern is only near the edges of the characters. The same processing (first halftone dot detection unit 712 and second halftone dot detection unit 713) is performed using color data having a Y component (yellow, green, red, black) as black pixels. Further, color data having M component (red, magenta, blue, black) and color data having C component (cyan, blue, green, black) are similarly subjected to Y component. The reason why the Y, M, and C components are developed is that the ink dot reproduction is accurately extracted because the ink component for printing is YMC.

  The first gray detection unit 714 uses the fact that the character area is dark and the area around the character is thin, and performs gray determination with a density that is lighter than the character area and darker than the character area. The white background used in the gray determination is an N-valued white pixel. The gray detection processing in the first gray detection unit 714 will be described with reference to the flowchart of FIG. As shown in FIG. 15, first, MS which is the processing result of the previous pixel and is the count value of the white pixel is compared with SS [i] which is the processing result of the previous line (step S11). If SS [i] is also large (Y in step S11), MS is replaced with SS [I] (step S12), and the process proceeds to step S13. On the other hand, if SS [i] is not larger than MS (N in step S11), the process proceeds to step S13 as it is. That is, the larger value of the result of the previous line and the processing result of the previous pixel is obtained.

  In a succeeding step S13, it is determined whether or not the pattern is a gray pattern by pattern matching shown in FIG. If the medium density matches the gray pattern (Y in step S13), MS is set to 5 and S [i] = 0, and it is used in the next line of S [i] (step S14), and the gray pixel is used. (Step S19). On the other hand, if the patterns do not match (N in step S13), the process proceeds to step S15. Here, the medium density is N-value conversion, Dtah = 0, and a non-white pixel.

  In step S15, it is determined whether or not the pixel is a white pixel. Here, the white pixel is an N-valued white pixel. If it is a white pixel (Y in step S15), it is determined whether MS> 0 (step S16). If MS> 0 (Y in step S7), the MS is decremented by 1 (step S17), and the process proceeds to step S18. If MS> 0 is not satisfied (N in step S16), S [i] is used in the next line as S [i] = MS as a non-gray pixel (step S20). On the other hand, if it is not a white pixel (N in step S15), the process proceeds to step S18 as it is.

  In step S18, it is determined whether or not the pixel is a gray pixel. Specifically, S [i] = MS is used, and S [i] is used in the next line to determine whether MS> 0. If MS> 0 (Y in Step S18), the pixel is a gray pixel (Step S19), and if MS> 0 (N in Step S19), the pixel is a non-gray pixel (Step S20).

  Finally, MS, which is the count value of white pixels, is set as the processing result SS [j] of the previous line (step S21), and the processing ends.

  Next, the second gray detection unit 715 will be briefly described. The first gray detection unit 714 processes image data in the forward direction, but the second gray detection unit 715 performs processing in the reverse direction. By processing in the reverse direction, the portion where the tip of the gray area is not gray is gray.

  Next, the background detection unit 716 will be described. When the adaptive binarization unit 706 switches the threshold value for each line and character determination is performed even in a thin area, there is no problem if all the thin areas are character determinations. There are many black and white change points in the result of the value conversion unit, and the file size becomes large in the final image. Therefore, if the lower limit value (white side) of the simple gray determination area is set closer to white, the character on the color ground cannot be determined, so the background is detected here. Add 4 × 5 AND to the ground, then perform 2 × 3 OR. This reduces the background for input data. Thus, the background around the character is also the boundary between the character and the background, and since the background area is reduced, it is difficult to include the character in the background, so that the background can be detected satisfactorily.

  Next, the black extraction unit 704 which is a high density area detection unit will be described. The black extraction unit 704 extracts a (very) dark area for use in determining whether the character is in the subsequent stage. The black extraction unit 704 includes a second isolated point removal unit 717. The second isolated point removal unit 717 performs 2 × 3 AND and 2 × 3 OR to perform isolated point removal. This makes it possible to extract only a cluster of (very) dark areas.

  Next, the character determination + character determination unit 705 that is character determination means will be described.

  First, character determination will be described. It is a character region (output of the first isolated point removal unit 707), not a halftone region (outputs of the first halftone dot detection unit 712 and the second halftone dot detection unit 713), but a gray region (first gray detection unit 714). If it is not a background area (output of the background detection section 716), but a character (result of determination of whether it is a character to be described later), not a character. The reason why the character area is logically operated with the background area, the halftone dot area, and the gray area in this way is that the character determination result is originally a photo area that does not require resolution, and is corrected as a photo area. It is a thing. In particular, the photographic region contains a large number of isolated points, and by performing this correction, it is possible to improve the compression rate of the character image and to reduce image and character non-character mixing, and to improve image quality. The reason why the character determination result is excluded from the character determination result is that black characters are output in a single black color, so that the character image is set to a fixed value in order to improve the compression rate.

  Next, the character determination will be described. Since there is always a misjudgment in the determination of characters, dark black can be output for thick characters (line with thick line width) so that dark black is detected and does not affect the image. These are operated from an operation unit (not shown). As the output, one of the following two types is selected: (1) determination of character determination, and (2) dark black determination.

(1). Determining whether or not it is a character The determination of whether or not a character is made up of two mirrors: character determination, three-line OR, picture determination, black determination, extraction 1, and extraction 2, as shown in FIG.

(1.1). Character determination The logical operation of the character determination result and the color determination result, which is the output result of the image area separation in the previous stage, is taken, and if the character is not a color, it is output with a black character edge.

(1.2). 3 line OR
An OR of 3 lines × 1 pixel of the black character edge as a result of character determination is taken. Originally, instead of this three-line OR, it is necessary to perform a two-line delay after the extraction 1 to match the line delay with the extraction 2, but if a line delay is performed after the extraction unit 1, it is necessary to delay the image data. Therefore, the line delay is absorbed by ORing three lines here.

(1.3). Image determination If any one of the color determination result, the gray detection 1 result, the gray detection 2 result, the halftone detection 1 result, and the halftone detection 2 result, which is the output result of the previous image area separation, is on. If it is a pattern, it is determined.

(1.4). Picture determination If the color determination result, which is the output result of the image area separation in the previous stage, is non-colored and black (Bk or dark black) in N-value, it is black.

(1.5). Extraction 1
A flow for extracting characters is shown in FIG. In the following description, the output of the three lines OR is assumed to be a black character edge, the pattern determination result is a pattern, and the black determination result is black.
a). Attention pixel determination If it is a black character edge, it is set as an area within a character.
If the result of the pattern determination is a pattern, the pattern area is set.
Note that neither characters nor patterns are turned on in the image area separation algorithm.
b). High density determination If the target line is not black as a result of black pixel determination, it is determined as an intermediate region.
c). One line before (picture) determination If the determination result one line before after the line segment processing is a picture area (photograph area), it is determined as a picture area (photograph area).
d). Determination of one pixel before (pattern) If the determination result of one pixel before is a pattern area (photo area), the pattern area (photo area) is determined.
e). Judgment before one line (character) If the judgment result one line before after the line segment processing is an area that is not a character, an area is determined to be a character.
f). Determination of one pixel before (character) If the determination result one pixel before is a character or a region, the character is a region.
g). Other than above Intermediate area.
h). Line segment processing Finally, line segment processing is performed. Here, if the color determination result is not a color and 144 pixels or more of high-density pixels are continuous, this module (in the character) corrects it as an intermediate region. Data to be output to the next stage is not corrected (the result before the line segment processing is output to the next stage (determination unit)).

(1.6). Extraction 2 and mirror In extraction 2, a reverse image (mirror) image is determined to be a character. In order to realize the reverse image processing by pipeline processing, mirroring is performed before and after the extraction 2. The description is omitted because it is the same as the extraction unit 1.

(1.7). Determination unit If the output of the mirrors of extraction 1 and extraction 2 is both a character region and the output of the binarization unit is a character, it is assumed to be a black character.

(2). Dark Black Determination In the dark black determination, if the output of the binarization unit 702 is a character, the black result is determined as a black character.

  This completes the description of the character determination.

  As described above, by referring to the state of the image of the surrounding pixels, it is possible to determine whether the character is the character in the image region by determining whether the character is a character.

  The character edge area and the color area can be detected with high accuracy because colors and halftone dots are detected from the read image. In addition, since the data after filtering is used for the density information for detection of characters, the halftone dot area is small for a character composed of halftone dots, and the character edge area is not used. Instead, the data after filtering (smoothed because it is not a character edge region) is used to make only the dark portion in the character. A halftone dot with a low screen line number, such as a newspaper photo, will remain in the screen even if it is smoothed. Since the screen is smoothed and the halftone dot shape disappears, a halftone dot area ratio of about 30% to 60% is detected as gray in the gray determination. In particular, since the leading edge of the character is narrow, it is difficult to form a halftone dot (non-character area). For example, if the leading edge is a character edge area and the central part of the character is determined to be a halftone dot, the determination of whether the character is halfway, This is to avoid being unsightly.

  Finally, the input format conversion unit 503 of the printer controller 115 will be described. FIG. 19 is a block diagram illustrating a configuration of the input format conversion unit 503. As shown in FIG. 19, the input format conversion unit 503 includes a TIFF format expansion unit 801, a JPEG format expansion unit 802, a compression format expansion unit 803, and an output selection unit 804. The TIFF format expansion unit 801, the JPEG format expansion unit 802, and the compression format expansion unit 803 have a function of expanding each format into a bitmap, and the output selection unit selects one of the three formats. Simultaneously with the output, the RGB data is converted into YMCBk. If the input image data is in the TIFF format, the TIFF format expansion unit 801 expands it with bitmap data. In the case of the JPEG format, the JPEG format development unit 802 develops the bitmap data. Further, in the case of a compression format, the compression format expansion unit 803 expands the compressed format.

  Here, the compression format expansion unit 803 will be described. The compression format development unit 803 includes an image file development unit 805, a binary image development unit 806, a black image development unit 807, a background image development unit 808, a character image development unit 809, and an image file composition unit 810. It is configured.

  In the image file development unit 805, four files among the files generated by the compression format generation unit 605 in FIG. 6 are converted into a binary image development unit 806, a black image development unit 807, a background image development unit 808, and a character image. Image data corresponding to each of the development units 809 is output.

  The binary image expansion unit 806 expands the MMR and expands it into a bitmap. The black image expansion unit 807 expands the MMR into a bitmap. The background image expansion unit 808 converts the JPEG of the background image into a bitmap. A character image expansion unit 809 expands each JPEG of the character image into a bitmap. The four developed bitmap data are synthesized into one piece of bitmap data by the image file synthesis unit 810.

  In the image file development unit 805, if the output of the binary image development unit 806 is a character region, the image data output from the character image development unit 809 is output, and the output of the binary image development unit 806 is a non-character region. If there is, the image data that is output from the background image development unit 808 is output. Further, if the output of the black image development unit 807 is a black character, it is output in black. Thus, one image is generated. The resolution of characters and non-characters is the resolution of the binary image.

  Here, FIG. 20 is an explanatory diagram showing images of an input image, a file image, and an output image.

  As described above, according to the present embodiment, the character edge region and the color region are separated from the input image data, so that the character edge region and the color region can be accurately detected. By using the image data, it is possible to make only the dark part a character by using data after filtering (smoothed because it is not a character edge region) instead of halftone information. Therefore, it is possible to detect a character with high accuracy.

  In addition, by performing the character edge area and the color area first, and performing the processing unique to the distribution later, it is possible to perform the scanner copy simultaneous operation and the like. In addition, since the determination of characters required for distribution is performed after the image data is stored in the storage unit, it is not necessary to store the determination result of characters that are not necessary for copying or the like, so that the amount of stored image data is reduced.

  In the present embodiment, the image processing apparatus includes a copy function, a facsimile (FAX) function, a printer function, and a function for distributing an input image (read original image or image input by a printer or FAX function). Although a digital color copying machine which is a so-called composite machine is applied, the present invention is not limited to this, and a printer apparatus having only a printer function may be used.

  Further, in the digital color multifunction peripheral 100 of the present embodiment, an example in which various processes are executed by the printer controller unit 102 which is a hardware resource of a digital circuit configuration has been shown, but the present invention is not limited to this. Various processes may be executed by operating the CPU by a computer program installed in a hardware resource (for example, HD) of the digital color multifunction peripheral 100.

1 is a block diagram showing a system configuration of a digital color multifunction peripheral according to an embodiment of the present invention. It is a block diagram which shows the structure of a scanner correction | amendment part. It is explanatory drawing which shows the character edge area | region by which image area separation is carried out. It is a block diagram which shows the structure of a printer correction | amendment part. 2 is a block diagram illustrating a configuration of a printer controller. FIG. It is a block diagram which shows the structure of an output format conversion part. It is a block diagram which shows the structure of a binarization part. It is a block diagram which shows the structure of an adaptive binarization part. It is explanatory drawing which shows the reference pixel of the adaptive binarization in an adaptive binarization part. It is explanatory drawing which shows the pattern of the isolated point removal in a 1st isolated point removal part. It is explanatory drawing which shows the relationship between a base area | region, a gray area | region, and a character area. It is a flowchart which shows the flow of the halftone detection process in a 1st halftone detection part. It is explanatory drawing which shows the pattern used for the pattern matching of a white pixel. It is explanatory drawing which shows the pattern used for the pattern matching of a halftone dot. It is a flowchart which shows the flow of the gray detection process in a 1st gray detection part. It is explanatory drawing which shows the pattern used for gray pattern matching. It is a block diagram which shows character determination in a character determination + character determination part. It is a flowchart which shows the flow of the process which extracts a character. It is a block diagram which shows the structure of an input format conversion part. It is explanatory drawing which shows the image of an input image, a file image, and an output image.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Image processing apparatus 118 Storage part 122 Image formation means 201 Character edge area | region separation means, Color area separation means 203 Filter processing means 703 Intermediate density area detection means 704 High density area detection means 705 Character determination means

Claims (5)

A character edge region separating means for separating a character edge region from input image data;
Color region separation means for separating a color region from input image data;
Filter processing means for performing filter processing according to an image area separation result in the character edge area separation means and the color area separation means;
Image storage means for storing the image data filtered by the filter processing means and the image area separation result in a storage unit;
High density area detection means for detecting a high density area for the image data stored in the storage unit;
Intermediate density area detecting means for detecting an intermediate density area for the image data stored in the storage unit;
By referring to the image state of surrounding pixels according to the high density area detected by the high density area detection means and the intermediate density area detected by the intermediate density area detection means, the inside of the black character and the character edge, that is, the character line Character judging means for judging whether the character means within the width;
An image processing apparatus comprising: The high density area detection means, the intermediate density area detection means, and the character determination means are re-executed to deliver the image data stored in the storage unit to another network-connected terminal.
The image processing apparatus according to claim 1. An image forming unit configured to form and output an image formed on the transfer paper based on the image data stored in the storage unit;
The image processing apparatus according to claim 1, wherein the image processing apparatus is an image processing apparatus. A character edge region separation function for separating a character edge region from input image data,
A color region separation function for separating a color region from input image data;
A filter processing function for performing filter processing according to an image region separation result in the character edge region separation function and the color region separation function;
An image accumulating function for accumulating in the storage unit the image data that has undergone the filtering process by the filtering function and the image area separation result;
A high density area detection function for detecting a high density area for the image data stored in the storage unit;
An intermediate density area detection function for detecting an intermediate density area for the image data stored in the storage unit;
By referring to the image state of the surrounding pixels according to the high density area detected by the high density area detection function and the intermediate density area detected by the intermediate density area detection function, the inside of the black character and the character edge, that is, the character line A character determination function that determines whether a character means a width,
A program for causing a computer to execute. The high density area detection function, the intermediate density area detection function, and the character determination function are re-executed to deliver the image data stored in the storage unit to other terminals connected to the network.
The program according to claim 4, wherein:

Images