JP4063480B2 - Image processing device - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention provides an image processing apparatus for converting input image data such as R, G, and G image data into output image data such as c, m, y, and black bk image data. An image reading apparatus in combination with a color scanner to be applied, an image forming apparatus in which a printer is combined with the image processing apparatus, a color copying apparatus in which a color scanner and a color printer are combined in the image processing apparatus, and a personal computer etc. in the color copying apparatus A color composite copying apparatus combined with a printer controller that prints out image information using the color printer in response to image information and a print instruction given from an external device, and more particularly, a character image represented by input image data and Make line drawings (these binary images are simply called characters) and their backgrounds into high-quality images. It relates to an image data processing of the eye.
[0002]
[Prior art]
Japanese Laid-Open Patent Publication No. 2-294484 discloses image area separation for discriminating character areas based on the lowest level of color component image data, and Japanese Laid-Open Patent Publication No. 2-295357 discloses the lowest level of color component image data. Japanese Patent Laid-Open No. 2-295358 discloses image area separation for determining a halftone dot area based on the halftone area, and JP-A-2-295358 determines a halftone area based on the lowest level of color component image data. Japanese Patent Application Laid-Open No. 10-23251 discloses an image processing apparatus that ternizes image data to extract white and black areas and applies line matching to these areas to extract line drawing edges. Japanese Patent Laid-Open No. 10-108012 discloses image area separation that detects whether input image data is an edge area, a halftone dot area, or a white background area, and determines whether it is a character area or a picture area from the result of each area detection. An apparatus is disclosed.
[0003]
Japanese Patent Laid-Open No. 3-64251 discloses a main scanning direction density change detection slice level T1, a sub-scanning direction density change detection slice level T2, an oblique density change detection slice level T3, and a halftone determination slice level T4. Is controlled by an SEG signal operated by an operator to adjust character / picture determination, and as a result, control for adjusting character priority / photo priority of image processing is disclosed.
[0004]
In JP-A-5-292212, halftone dot pixels are detected, the number of distributions of the detected halftone dot pixels on a small area is counted, and the count value is compared with a threshold value. A halftone dot region separation device for determining whether a halftone dot region is present is disclosed. Japanese Patent Laid-Open No. 9-247481 discloses halftone dot detection in which halftone dot determination is performed after each of C, M, and Y image data. Japanese Patent No. 2856867 discloses a color image processing apparatus in which a picture area surrounded by a black character edge area is used as a black character area and a single black color is assigned thereto. Japanese Patent Application Laid-Open No. 7-95397 discloses that in monochromatic image processing, an edge and a high density region are detected and an edge within a predetermined distance is detected in order to prevent whitening inside a thick line of a high density thick character and to prevent a lowercase letter blur. A document reading apparatus is disclosed in which a sandwiched high density area is identified as a character area, and other high density areas are identified as non-character areas, and image processing corresponding to each area is performed.
[0005]
[Problems to be solved by the invention]
In conventional image area separation, a character area around a character edge may be determined as a white area in light-colored characters or newspapers. The cause is that the edge enhancement filter processing is performed on the image data in order to restore the character blur. If the background color is colored, the level of the background around the character is lowered to a white background level. When the white area is determined, the periphery of the character edge is processed as a white background level, so the background color around the character may be determined as the white area. If this is continuous, it will not be very noticeable, but when there is unevenness due to show-through, etc., white / color background judgment will be mixed around the characters, and the white background will be scattered or scattered in the light color background, which will be annoying Sometimes. If a matching pattern for detecting a white area that does not determine white is created, if the lines are dense, the white background of the interline area cannot be determined as a white area.
[0006]
When image data with high sensitivity to black density, such as high / low density, luminance, and G (green) signal, is used to detect a character edge, the signal has no correlation with the color, so light colors, particularly Y (yellow: yellow) ) Was difficult to detect. In the prior art, feature values are extracted by taking the minimum values of R (red), G (green), and B (blue) color component signals generated by a color scanner. If it is used, it is affected by misalignment at the time of reading. Therefore, the bright and dark parts of the document are slightly emphasized because the reading position is misaligned. In particular, since there is a halftone screen angle of printed matter, the influence is great. Further, at the time of edge extraction, edge enhancement filter processing is performed to restore the original blur of image data when read, but since the blur characteristics are different for each color, it is better to perform the processing filter for each color.
[0007]
The first object of the present invention is to improve the image quality of characters and surroundings. Specifically, as a result of performing edge emphasis processing on image data, the second object is to reduce the possibility of erroneously processing the area around the edge of a character as a white area in light-colored characters or newspapers. The third objective is to increase the accuracy of character edge detection and improve the reliability of reproduction, and to ensure character edge / pattern judgment closer to characters / pictures (photos) according to the background density of the original. The fourth object is to make it possible to switch or adjust the characteristics. A fifth object is to perform non-character edge processing (pattern processing) on characters on a color ground where the sensitivity of image data used for edge detection is low, such as yellow ground, and non-character edge processing is performed on halftone dots on the color ground. The sixth object is to perform (pattern processing).
[0008]
[Means for Solving the Problems]
(1) In image data, Below threshold concentration Painting Element With white pixels White data detection means for detecting;
Color ground detection means for detecting color pixels in the image data;
The multi-value white background information representing the degree of white of the pixel one line before is the white background information of the pixel one pixel previous on the same line. If it is larger, the white background information of the pixel before one line is set as the temporary white background information of the target pixel; otherwise, the white background information of the pixel one pixel before is set as the temporary white background information of the target pixel, and the target pixel is the color pixel. If the pixel of interest is not the white pixel, the temporary white background information is updated to be small, and if the pixel of interest is not the color pixel and the white pixel, the temporary white background information is updated to a large amount. Information, and if the target pixel is a white background in which all of the R, G, and B image data are smaller than the threshold value, the highest setting value of the white background information is used as the white background information of the target pixel. White judging means;
The target pixel is not the color pixel but the white pixel, and the The white background information generated by the white judging means If the pixel of interest is above the threshold, the pixel of interest is temporarily determined as a white pixel, and pattern matching is used to determine whether there is a series of white pixels centered on the pixel of interest. Pattern matching means for judging;
When there is a continuation of the white pixels, a block composed of a plurality of pixels including the target pixel and adjacent pixels is changed to a white block in which all pixels in the block are white pixels. White area detecting means for performing; and
The white area detecting means Pixels of interest that are not judged as white blocks Non-character edge When Size Set A non-character edge determination means.
[0009]
According to this, misidentification of detecting a non-white area as a white area is reduced, and the reliability of white area detection is high. The possibility that a light color with low sensitivity of the image data (G), for example, a character on a yellow ground, becomes a character edge is reduced. In other words, it is highly reliable that a character on a light color ground is a non-character edge.
[0010]
DETAILED DESCRIPTION OF THE INVENTION
(2) In image data, Below threshold concentration Painting Element With white pixels White data detection means for detecting;
Color ground detection means for detecting color pixels in the image data;
The multi-value white background information representing the degree of white of the pixel one line before is the white background information of the pixel one pixel previous on the same line. If it is larger, the white background information of the pixel before one line is set as the temporary white background information of the target pixel; otherwise, the white background information of the pixel one pixel before is set as the temporary white background information of the target pixel, and the target pixel is the color pixel. If the pixel of interest is not the white pixel, the temporary white background information is updated to be small, and if the pixel of interest is not the color pixel and the white pixel, the temporary white background information is updated to a large amount. Information, and if the target pixel is a white background in which all of the R, G, and B image data are smaller than the threshold value, the highest setting value of the white background information is used as the white background information of the target pixel. White judging means;
The target pixel is not the color pixel but the white pixel, and the The white background information generated by the white judging means If the pixel of interest is above the threshold, the pixel of interest is temporarily determined as a white pixel, and pattern matching is used to determine whether there is a series of white pixels centered on the pixel of interest. Pattern matching means for judging;
When there is a continuation of the white pixels, a block composed of a plurality of pixels including the target pixel and adjacent pixels is changed to a white block in which all pixels in the block are white pixels. White area detecting means for performing;
Halftone dot detecting means for detecting halftone dots in the image data; and
The white area detecting means A pixel of interest that is not determined to be a white block and a pixel of interest for which the halftone dot detection means has detected a halftone dot Non-character edge When Size Set A non-character edge determination means.
[0011]
According to this, in addition to the above (1), it is possible to further improve the reliability of the non-character edge determination by setting the area detected by the halftone detection means (324) as a halftone dot as the non-character edge area.
[0012]
(3) In image data, Below threshold concentration Painting Element With white pixels White data detection means for detecting;
Color ground detection means for detecting color pixels in the image data;
The multi-value white background information representing the degree of white of the pixel one line before is the white background information of the pixel one pixel previous on the same line. If it is larger, the white background information of the pixel before one line is set as the temporary white background information of the target pixel; otherwise, the white background information of the pixel one pixel before is set as the temporary white background information of the target pixel, and the target pixel is the color pixel. If the pixel of interest is not the white pixel, the temporary white background information is updated to be small, and if the pixel of interest is not the color pixel and the white pixel, the temporary white background information is updated to a large amount. Information, and if the target pixel is a white background in which all of the R, G, and B image data are smaller than the threshold value, the highest setting value of the white background information is used as the white background information of the target pixel. White judging means;
The target pixel is not the color pixel but the white pixel, and the The white background information generated by the white judging means If the pixel of interest is above the threshold, the pixel of interest is temporarily determined as a white pixel, and pattern matching is used to determine whether there is a series of white pixels centered on the pixel of interest. Pattern matching means for judging;
When there is a continuation of the white pixels, a block composed of a plurality of pixels including the target pixel and adjacent pixels is changed to a white block in which all pixels in the block are white pixels. White area detecting means for
Edge detection means for detecting edges in the image data; and
The Edge detection means But Edge When Detecting and detecting said white area The pixel of interest detected by Character edge When Size Set An image processing apparatus comprising: a character edge determination unit.
[0013]
According to this, both the non-character edge detection and the character edge detection are highly reliable, and output image data that is a high-quality image in both areas can be obtained.
[0014]
(4) In image data, Below threshold concentration Painting Element With white pixels White data detection means for detecting;
Color ground detection means for detecting color pixels in the image data;
Multi-value white background information representing the degree of white of the pixel one line before is white background information of the pixel one pixel previous on the same line. If it is larger, the white background information of the pixel before one line is set as the temporary white background information of the target pixel; otherwise, the white background information of the pixel one pixel before is set as the temporary white background information of the target pixel, and the target pixel is the color pixel. If the pixel of interest is not the white pixel, the temporary white background information is updated to be small, and if the pixel of interest is not the color pixel and the white pixel, the temporary white background information is updated to a large amount. Information, and if the target pixel is a white background in which all of the R, G, and B image data are smaller than the threshold value, the highest setting value of the white background information is used as the white background information of the target pixel. White judging means;
The target pixel is not the color pixel but the white pixel, and the The white background information generated by the white judging means If the pixel of interest is above the threshold, the pixel of interest is temporarily determined as a white pixel, and pattern matching is used to determine whether there is a series of white pixels centered on the pixel of interest. Pattern matching means for judging;
When there is a continuation of the white pixels, a block composed of a plurality of pixels including the target pixel and adjacent pixels is changed to a white block in which all pixels in the block are white pixels. White area detecting means for
Halftone dot detecting means for detecting halftone dots in the image data;
Edge detection means for detecting edges in the image data; and
The Edge detection means But Edge When Detecting the halftone dot Is not detected as a halftone dot, and The white area detecting means The pixel of interest detected by Character edge When Size Set An image processing apparatus comprising: a character edge determination unit.
[0015]
(5) The white determination means (323c) sets the white background information (MS) to a high level when the image level is white (white background / binarized white) based on the image data (steps 3 and 4 in FIG. 5). -7-10), when a color background having a color component level difference is detected, the white background information (MS) is lowered (step 6-13 in FIG. 5); described in any one of (1) to (4) above Image processing apparatus (IPU300).
[0016]
According to this, there is a high probability that an area read as white is detected as a white area including a character edge (character) by the white area detection means (323), and an area read as non-white is detected as a non-white area. Thus, there is a high probability that the non-character edge determination means (326a) will detect it as a non-character edge region (a picture region including a photograph). If a color background with a color component level difference is detected, the white background information (MS) is lowered, so that the misunderstanding that the color background is detected as a white area is reduced, and the probability that a color background outside the character is misidentified as a white area (character edge). Therefore, the possibility of erroneously processing the area around the edge of a character as a white area in light-colored characters or newspapers is reduced, and the reproduced image quality around the character is improved.
[0017]
(6) The white determination means (FIG. 5) lowers the white background information (MS) when the color background detection means detects the color background (step 6-13 in FIG. 5), and does not detect the color background, but white data. When the detection means (323a) detects a white pixel, the white background information (MS) is increased (steps 6 to 10 in FIG. 5), and the image processing apparatus according to any one of (1) to (5) above.
[0018]
According to this, when any level of the color component image data (R, G, B) is white (white background) smaller than the first threshold (thwss), high level white background information (MS) is generated, and this white background When the color background is switched to, the white background information (MS) is lowered. However, when the background is not a white background or a color background, the white background information (MS) is increased.
[0019]
Thereby, the white background information (MS) is binaryly switched between white / non-white depending on whether each of the color component image data (R, G, B) is white smaller than the first threshold (thwss). Even if there is uneven background density such as show-through in the document, the possibility of detecting mixed white areas (character areas) / non-white areas (design areas) is reduced, and the background color is light. Occasionally, fine white spots appear to be scattered or scattered in conjunction with fine unevenness of the original.
[0020]
(7) The halftone dot detection means (324) is a first halftone peak detection means (324a) for detecting a halftone peak of the image represented by the first image data (G) sensitive to the black density of the color image, Second halftone peak detecting means (324) for detecting a halftone dot peak of an image represented by the second image data (B) that is sensitive to a color component (Y) having low sensitivity of one image data (G); (2) or (2) including means (324c) for determining whether or not a halftone dot area by counting the number of halftone dots detected by the first and second halftone peak detecting means (324a, 324b) for each small area (4) The image processing apparatus.
[0021]
Since the first image data (G) indicating the dark and light density and the second image data (B) sensitive to the color (Y) having low sensitivity are used, the first image data (G) is used. It was also possible to detect halftone dots of a color that could not be detected in the past. Only the halftone dot detection is separate from the first image data (G) and the second image data (B), and the processing after the halftone peak detection is one pass, so the hardware amount is not so much.
[0022]
(8) The image processing apparatus (IPU 300) according to any one of the above (1) to (7) and a color scanner (color separation of the original image, reading the image to generate image data, and supplying the image data to the image processing apparatus (IPU 300)) 200), and an image reading apparatus (200 + IPU 300). This image reading apparatus outputs image data in which character reproduction is clear. Specifically, the effects described in the above (1) to (7) are exhibited.
[0023]
(9) An image forming apparatus (400 + IPU 300) comprising the image processing apparatus (IPU 300) of any one of (1) to (7) and a color printer (400) that prints output image data on paper. This image forming apparatus reproduces characters clearly. Specifically, the effects described in the above (1) to (7) are exhibited.
[0024]
(10) The image processing apparatus (IPU 300) according to any one of (1) to (7) above, and a color scanner (color separation of the original image, reading the image to generate image data, and supplying the image data to the image processing apparatus (IPU 300)) 200), and a color copying apparatus (200 + IPU300 + 400) including a color printer (400) for printing out output image data of the image processing apparatus (IPU300) on paper. This color copying apparatus copies characters clearly. Specifically, the effects described in the above (1) to (7) are exhibited.
[0025]
(11) The color copying apparatus (200 + 16 + IPU300 + 400) according to (19), further comprising a printer controller (16) for analyzing an external print instruction command and printing out image information from the outside by the printer (400). This color copying apparatus prints out image information given from outside such as a personal computer with clear characters. Specifically, the effects described in the above (1) to (16) are exhibited.
[0026]
(12) In the above (1) to (11), the image processing apparatus (IPU 300) includes a black background detecting means (323e, f) for detecting a high density area based on image data, and a low density area and a high density area area. [5. ) Black block correction], detecting the boundary area as a white area [6. A white correction means (323g).
[0027]
According to this, the boundary between the low density area (white area) and the high density area (black area) is detected as a white area where a character edge may exist, and the white area is not detected as a non-character area. Since it is determined as an edge area (picture area or character area), the possibility of erroneously determining the character edge area as a non-character edge area is reduced, and the character edge can be detected correctly regardless of the line width of the character. It becomes possible. As a result, it is possible to improve the character reproduction image quality, in other words, to reproduce characters clearly.
[0028]
(13) In the above (12), the white correction means (323g) further detects a region surrounded by the low density region, and also detects the region as a white region [4. ) White block correction].
[0029]
According to this, the white area, that is, the area surrounded by the low density area is also detected as a white area, and the area where the lines are dense can be determined as the white area. By determining the white area, it can be detected as a character edge. Other objects and features of the present invention will become apparent from the following description of embodiments with reference to the drawings.
[0030]
【Example】
An outline of the mechanism of one embodiment of the present invention is shown in FIG. This embodiment is a digital full-color copying machine. A color image reading apparatus (hereinafter referred to as a scanner) 200 forms an image of a document 180 on a contact glass 202 on a color sensor 207 through an illumination lamp 205, mirror groups 204A, 204B, 204C, and a lens 206. The color image information of the original is read for each color separation light of, for example, blue (hereinafter referred to as “B”), green (hereinafter referred to as “G”), and red (hereinafter referred to as “R”), and converted into an electrical image signal. In this example, the color sensor 207 includes a 3-line CCD sensor, and reads B, G, and R images for each color. Based on the color separation image signal intensity levels of B, G, and R obtained by the scanner 200, color conversion processing is performed by an image processing unit (not shown) to obtain black (hereinafter referred to as Bk), cyan (hereinafter referred to as “black”). C), magenta (hereinafter referred to as “M”), and yellow (hereinafter referred to as “Y”) color image data including recording color information is obtained.
[0031]
Using this color image data, Bk, C, M, and Y images are formed on an intermediate transfer belt by a color image recording apparatus (hereinafter referred to as a color printer) 400 described below, and transferred onto transfer paper. The scanner 200 receives a scanner start signal based on the operation and timing of the color printer 400, and the illumination / mirror optical system including the illumination lamp 205 and the mirror groups 204A, 204B, and 204C scans the document in the left arrow direction. One color image data is obtained for each scanning. Each time, the color printer 400 sequentially visualizes the images and superimposes them on the intermediate transfer belt to form a full-color image of four colors.
[0032]
A writing optical unit 401 as an exposure unit of the color printer 400 converts color image data from the scanner 200 into an optical signal, performs optical writing corresponding to the original image, and forms an electrostatic latent image on the photosensitive drum 414. Form. The optical writing optical unit 401 includes a laser light emitter 441, a light emission drive control unit (not shown) that drives the light emission, a polygon mirror 443, a rotation motor 444 that rotationally drives it, an fθ lens 442, a reflection mirror 446, and the like. Has been. The photoconductive drum 414 rotates counterclockwise as indicated by an arrow, and around the photoconductive drum cleaning unit 421, the charge eliminating lamp 414M, the charger 419, and the latent image potential on the photoconductive drum are detected. A potential sensor 414D, a selected developing device of the revolver developing device 420, a developing density pattern detector 414P, an intermediate transfer belt 415, and the like are arranged.
[0033]
The revolver developing device 420 includes a BK developing unit 420K, a C developing unit 420C, an M developing unit 420M, a Y developing unit 420Y, and a revolver rotation driving unit (not shown) that rotates each developing unit in a counterclockwise direction as indicated by an arrow. (Omitted). Each of these developing units assembles a developing sleeve 420KS, 420CS, 420MS, 420YS, which rotates by bringing the ears of the developer into contact with the surface of the photosensitive drum 414 in order to visualize the electrostatic latent image. -It consists of a development paddle that rotates to stir. In the standby state, the revolver developing device 420 is set at a position where development is performed by the BK developing device 420. When the copying operation is started, the scanner 200 starts reading BK image data from a predetermined timing. Based on the data, laser writing and latent image formation are started. Hereinafter, an electrostatic latent image based on Bk image data is referred to as a Bk latent image. The same applies to C, M, and Y image data. In order to enable development from the leading edge of the Bk latent image, before the leading edge of the latent image reaches the developing position of the Bk developing device 420K, the developing sleeve 420KS starts to rotate, and the Bk latent image is developed with Bk toner. . Thereafter, the developing operation of the Bk latent image area is continued. However, when the trailing edge of the latent image passes the Bk latent image position, the developing operation of the next color from the developing position by the Bk developing unit 420K is promptly performed. The revolver developing device 420 is driven and rotated to the position. This rotation operation is completed at least before the leading edge of the latent image by the next image data arrives.
[0034]
When the image forming cycle is started, the photosensitive drum 414 is rotated counterclockwise as indicated by an arrow, and the intermediate transfer belt 415 is rotated clockwise by a drive motor (not shown). As the intermediate transfer belt 415 rotates, BK toner image formation, C toner image formation, M toner image formation, and Y toner image formation are sequentially performed. Finally, intermediate transfer is performed in the order of BK, C, M, and Y. A toner image is formed over the belt 415. The BK image is formed as follows. That is, the charger 419 uniformly charges the photosensitive drum 414 to about −700 V with a negative charge by corona discharge. Subsequently, the laser diode 441 performs raster exposure based on the Bk signal. When the raster image is exposed in this way, the charge proportional to the exposure light amount disappears in the exposed portion of the uniformly charged photosensitive drum 414, and an electrostatic latent image is formed. The toner in the revolver developing device 420 is negatively charged by stirring with the ferrite carrier, and the BK developing sleeve 420KS of the developing device is connected to the metal base layer of the photosensitive drum 414 by a power supply circuit (not shown). It is biased to a potential in which a negative DC potential and an AC are superimposed. As a result, toner does not adhere to the portion where the charge of the photosensitive drum 414 remains, and Bk toner is adsorbed to the portion without charge, that is, the exposed portion, and Bk visible similar to the latent image. An image is formed. The intermediate transfer belt 415 is stretched around a drive roller 415D, a transfer counter roller 415T, a cleaning counter roller 415C, and a driven roller group, and is rotated by a drive motor (not shown). Now, the Bk toner image formed on the photosensitive drum 414 is applied to a belt transfer corona discharger (hereinafter referred to as a belt transfer unit) 416 on the surface of an intermediate transfer belt 415 that is driven at a constant speed in contact with the photosensitive member. Is transcribed by. Hereinafter, toner image transfer from the photosensitive drum 414 to the intermediate transfer belt 415 is referred to as belt transfer. Some untransferred residual toner on the photoconductor drum 414 is cleaned by the photoconductor cleaning unit 421 in preparation for reuse of the photoconductor drum 414. The toner collected here is stored in a waste toner tank (not shown) via a collection pipe.
[0035]
The intermediate transfer belt 415 sequentially aligns the Bk, C, M, and Y toner images formed on the photosensitive drum 414 on the same surface to form a four-color superimposed belt transfer image. Thereafter, batch transfer is performed on the transfer paper with a corona discharge transfer device. By the way, on the photosensitive drum 414 side, the process proceeds to the C image forming process after the BK image forming process. At a predetermined timing, reading of the C image data by the scanner 200 starts, and laser light writing by the image data is performed. Then, a C latent image is formed. The C developing device 420C rotates the revolver developing device after the rear end of the previous Bk latent image has passed with respect to the developing position and before the front end of the C latent image has arrived. Develop the image with C toner. Thereafter, the development of the C latent image area is continued. When the trailing edge of the latent image passes, the revolver developing device 420 is driven in the same manner as in the case of the previous Bk developing device, and the C developing device 420C is sent out. The M developing device 420M is positioned at the developing position. This operation is also performed before the leading edge of the next M latent image reaches the developing unit. It should be noted that the image forming process for each of the M and Y images will not be described because the image data reading, latent image forming, and developing operations are in accordance with the Bk image and C image processes described above.
[0036]
The belt cleaning device 415U includes an inlet seal, a rubber blade, a discharge coil, and a contact / separation mechanism for the inlet seal and the rubber blade. After transferring the first color Bk image to the belt, while transferring the second, third, and fourth color images to the belt, the blade seal mechanism separates the inlet seal, rubber blade, etc. from the intermediate transfer belt surface. deep.
[0037]
A paper transfer corona discharger (hereinafter referred to as a paper transfer unit) 417 is a corona discharge method for transferring the superimposed toner image on the intermediate transfer belt 415 to the transfer paper. This is applied to the transfer belt.
[0038]
The transfer paper cassette 482 in the paper supply bank stores transfer paper of various sizes, and is fed in the direction of the registration roller pair 418R by the paper supply roller 483 from the cassette storing the paper of the specified size.・ Conveyed. Reference numeral 412B2 denotes a paper feed tray for manually feeding OHP paper, cardboard, or the like. At the time when the image formation is started, the transfer paper is fed from one of the paper feed trays and stands by at the nip portion of the registration roller pair 418R. When the leading edge of the toner image on the intermediate transfer belt 415 approaches the paper transfer unit 417, the registration roller pair 418R is driven so that the leading edge of the transfer paper coincides with the leading edge of the image, and the paper and the image are transferred. Matching is done. In this way, the transfer paper is superimposed on the color superposition image on the intermediate transfer belt and passes over the paper transfer device 417 connected to a positive potential. At this time, the transfer paper is charged with a positive charge by the corona discharge current, and most of the toner image is transferred onto the transfer paper. Subsequently, when the paper passes through a separation static eliminator (not shown) disposed on the left side of the paper transfer unit 417, the transfer paper is neutralized, separated from the intermediate transfer belt 415, and transferred to the paper conveyance belt 422. The transfer paper onto which the four-color superimposed toner images have been transferred from the intermediate transfer belt surface is conveyed to the fixing device 423 by the paper conveying belt 422, and the toner is transferred to the nip portion between the fixing roller 423A and the pressure roller 423B controlled to a predetermined temperature. The image is melted and fixed, sent out of the main body by a pair of discharge rollers 424, and stacked face up on a copy tray (not shown).
[0039]
The surface of the photosensitive drum 414 after the belt transfer is cleaned by a photosensitive member cleaning unit 421 including a brush roller, a rubber blade, and the like, and is uniformly discharged by a discharging lamp 414M. The intermediate transfer belt 415 after transferring the toner image to the transfer paper again cleans the surface by pressing the blade with the blade contact / separation mechanism of the cleaning unit 415U. In the case of repeat copying, the operation of the scanner and the image formation on the photosensitive member are continued to the fourth color image process for the first sheet, and then proceed to the first color image process for the second sheet at a predetermined timing. In the intermediate transfer belt 415, the second Bk toner image is belt-transferred to the area where the surface is cleaned by a belt cleaning device following the batch transfer process of the first four-color superimposed image to the transfer paper. So that After that, the operation is the same as the first sheet.
[0040]
The color copier shown in FIG. 1 can print out (image output) with a color printer 400 when print data is given from a host such as a personal computer through a LAN or parallel I / F. This is a color copier with a combined function capable of transmitting image data read by the scanner 200 to a remote facsimile machine and printing out received image data. This copier is connected to a public telephone network via a private branch exchange PBX, and can communicate with a facsimile server or a service center management server via the public telephone network.
[0041]
FIG. 2 shows an outline of the electric system of the copying machine shown in FIG. FIG. 2 illustrates the control device of the copying machine with the main controller 10 as the center. The main controller 10 controls the entire copying machine. The main controller 10 includes a display for an operator, an operation / display board OPB for performing function setting input control from the operator, an editor 15, a scanner 200, and optional ADF control, control for writing a document image in an image memory, and image In the scanner controller 12, the printer controller 16, the image processing unit (IPU) 40, and the color printer 400 for performing control to perform image formation from the memory, and charging, exposure, development, paper feeding, transfer, fixing, and the like A distributed control device such as an engine controller 13 for controlling the image forming engine for carrying the transfer paper is connected. Each distributed control device and the main controller 10 exchange machine states and operation commands as necessary. A main motor and various clutches necessary for paper conveyance and the like are also connected to a driver (not shown) in the main controller 10.
[0042]
The color printer 400 includes an electric circuit and a control circuit for driving a mechanism element that performs feeding of a photoconductor 414, image exposure by a laser writing unit, development, transfer, fixing, and paper discharge as well as feeding from a paper feed tray. And various sensors.
[0043]
The printer controller 16 analyzes an image from the outside such as a personal computer and a command for instructing printing, develops a bitmap as image data into a printable state, and drives the printer 400 via the main controller 10 to print the image data. Out. There is a LAN control 19 and a parallel I / F 18 for receiving and operating images and commands via the LAN and parallel I / F.
[0044]
When there is a facsimile transmission instruction, the FAX controller 17 drives the scanner 200 and the IPU 300 via the main controller 10 to read the image of the document, and sends the image data to the facsimile communication line via the communication control 20 and the PBX. Send it out. When a facsimile call is received from the communication line and image data is received, the printer 400 is driven via the main controller 10 to print out the image data.
[0045]
FIG. 3 shows the configuration of an image processing unit (IPU) 300. R, G, B image data generated by the scanner 200 is given to the IPU 300 via the interface 351. Note that when the BR unit 355 instructs B or R monochrome recording, R, G, and B image data are selected and assembled, but the description of the image recording processing in this mode is omitted. The R, G, B image data given to the IPU 300 is converted from reflectance data (R, G, B data) to density data (R, G, B data) by RGBγ correction 310.
[0046]
Based on the density R, G, B data, the document recognition 320 determines whether the image area to which the data is addressed is a character area (character or line drawing area) or a picture area (photo or picture area & not a character area). And the C / P signal and the B / C signal are supplied to the main controller 10 via the RGB filter 330 and the interface 353;
C / P signal: 2-bit signal, 2 bits “11” meaning 3
2 bits "01" indicating the character edge area, meaning 1
2 bits “00”, which indicates an area within a character and means 0
Indicates the pattern area;
B / C signal: 1-bit signal, H (“1”) indicates an achromatic region,
L (“0”) indicates a chromatic area.
[0047]
-Document recognition 320 (FIG. 4)-
FIG. 4 shows the function of the document recognition 320 in block sections. The original recognition 320 performs character edge detection, character detection, pattern detection, and chromatic / achromatic detection to detect a C / P signal and a chromatic region / achromatic region representing a character edge region, character region, or pattern region. A B / C signal representing Here, “character” means inside the character edge, that is, within the character line width.
[0048]
The document recognition 320 is roughly divided into a filter 321, edge extraction 322, white area extraction 323, halftone dot extraction 324, color determination 325, and general determination 326. Here, a case where the reading density of the scanner 200 is about 600 dpi will be described as an example.
[0049]
-Filter 321-
The filter 321 corrects the G image data generated by the scanner 200 mainly for extracting the edge of the character. Here, since the data read by the scanner 200 may be blurred due to the performance of a lens or the like, an edge enhancement filter is applied. However, here, it is necessary to simply emphasize the image edge on the original and not to emphasize the line pattern for gradation expression, which is widely used in copying machines. If the line pattern is emphasized, it is necessary to extract the picture (gradation expression area by the line pattern) as an edge and eventually misidentify it as a character edge. is there. Also, as shown in FIG. 8, the 600 dpi line pattern A and the 400 dpi line pattern B have different repetition periods, so it is difficult to avoid enhancement with the same filter coefficient. Therefore, the cycle of the image pattern is detected and the filter coefficient is switched. In FIG. 8, the sum of the width of one white block in the main scanning direction x and the width of one black block adjacent thereto is a line pitch (constant width: a predetermined number of pixels), that is, a line cycle, and a low density halftone. Sometimes the white block width increases and the black block width decreases. As the density becomes higher, the white block width becomes narrower and the black block width becomes wider.
[0050]
In this embodiment, the pixel matrix of the filter processing 321 is set to 7 pixels in the main scanning direction x × 5 pixels in the sub-scanning direction y (mechanical document scanning direction of the scanner 200). As shown in the block, there are two sets of coefficient groups (coefficient matrices) A and B addressed to each pixel, each weighted coefficient a1 to a7, b1 to b7, c1 to c7, d1 to d7, and e1 to e7. The next coefficient group A is a coefficient for filtering that suppresses emphasis of the 600 dpi line pattern A in FIG. 8 and emphasizes the edge of the character, and the coefficient group B is a 400 dpi line pattern B in FIG. Is a coefficient for filtering that suppresses the emphasis and emphasizes the edge of the character.
[0051]
Coefficient group A
0 -1 0 -2 0 -1 0
0 -1 0 -2 0 -1 0
0 -1 -1 20 -1 -1 0
0 -1 0 -2 0 -1 0
0 -1 0 -2 0 -1 0.
[0052]
Coefficient group B
-1 0 0 -2 0 0 -1
-1 0 0 -2 0 0 -1
-1 0 -1 20 -1 0 -1
-1 0 0 -2 0 0 -1
-1 0 0 -2 0 0 -1.
[0053]
Note that the horizontal direction is the alignment in the main scanning direction x, and the vertical direction is the alignment in the sub-scanning direction y. The coefficients in the first row of the coefficient groups A and B are the coefficients a1 to a7 in the first row of the coefficient matrix of the block of the filter 321 in FIG. The center “20” is the coefficient of the center pixel in the third row c1 to c7 of the coefficient matrix of the filter 321 block, that is, the coefficient c4 of the target pixel. The sum (product sum value) of products (total 7 × 5 = 35) obtained by multiplying each coefficient of the coefficient matrix by the value represented by the image data of the pixel addressed to the coefficient is the pixel of interest (pixel addressed to c4). The image data values processed by the filter 321 are given to the edge extraction 322 and the white area extraction 323. Here, the pixel of interest is a pixel that is currently processed, and it is updated to pixels that are sequentially different in the x direction and in the y direction.
[0054]
In the coefficient group A, a negative coefficient (small value coefficient) is distributed at the line pitch of the 600 dpi line pattern A shown in FIG. 8, and 0 (slightly large coefficient) is distributed between them, and the edge For emphasis, 20 (very large coefficient) is assigned to the target pixel. As a result, when the image data (target pixel) is the black / white edge of the line pattern A region, the weighted average value (product sum value) derived therefrom is the character edge that is not the line pattern A. Compared to a certain time, the value is considerably lower.
[0055]
In the coefficient group B, negative coefficients (coefficients having a small value) are distributed at the line pitch of the line pattern B of 400 dpi shown in FIG. For emphasis, 20 (very large coefficient) is assigned to the target pixel. As a result, when the image data (target pixel) is the black / white edge of the line pattern B region, the weighted average value (product sum value) derived to that is the character edge that is not the line pattern B. Compared to a certain time, the value is considerably lower.
[0056]
Note that the filter 321 performs the filter processing by the coefficient group B when one of the following conditions 1 and 2 is satisfied, that is, when there is a high possibility that the line pattern B of 400 dpi in FIG. Filter by coefficient group A:
-Condition 1- [Thin line pattern B of 400 dpi type is thin
(Conditions to see if the white section in Figure 8)]
(D [3] [1] <D [3] [2]) &
(D [3] [7] <D [3] [6]) &
(ABS (D [3] [2]-D [3] [4])> ABS (D [3] [4]-D [3] [1])) &
(ABS (D [3] [6]-D [3] [4])> ABS (D [3] [4]-D [3] [7]))
-Condition 2 [Deep part of line pattern B of 400 dpi system
(Conditions to see if the black section in Fig. 8)
(D [3] [1]> D [3] [2]) &
(D [3] [7]> D [3] [6]) &
(ABS (D [3] [2]-D [3] [4])> ABS (D [3] [4]-D [3] [1])) &
(ABS (D [3] [6]-D [3] [4])> ABS (D [3] [4]-D [3] [7]))
Note that D [i] [j] means a value represented by the image data of the pixel at the position of x = i, y = j on the pixel matrix of x, y distribution. For example, D [3] [1 ] Is a value represented by image data of a pixel to which the coefficient a3 of the coefficient matrix shown in the block of the filter 321 in FIG. 4 is addressed. “&” Means “logical product: AND”, and “ABS” means an absolute value operator. The target pixel is D [4] [3].
[0057]
When the above condition 1 or 2 is satisfied, it is assumed that the pixel of interest at that time is in the 400 dpi line pattern B region at the time of 600 dpi reading shown in FIG. Perform emphasis filtering. If neither of the conditions 1 and 2 is satisfied, the filter processing for character edge emphasis is performed using the coefficient group A shown in FIG. 8 that avoids emphasizing the 600 dpi line pattern A at the time of 600 dpi reading. That is, the image period (pitch) is detected so that the image pattern of a specific period is not emphasized. It is possible to emphasize the edge of a character without emphasizing the line pattern. FIG. 4 shows an aspect in which G image data is referred to for edge processing, but it is not limited to G image data, and may be luminance data. Any signal expressing dark and light can be applied.
[0058]
-Edge extraction 322-
In the character region, there are 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 in the edge portion. The edge extraction 322 detects a character edge based on the continuity of each of such black pixels and white pixels.
[0059]
-3 value 322a-
First, in the ternarization 322a, the G image data (input data of the edge extraction 322) subjected to the filter processing for character edge enhancement by the filter 321 is ternarized using two kinds of threshold values TH1 and TH2. For example, when the image data represents 256 gradations (0 = white) from 0 to 255, the thresholds TH1 and TH2 are set to TH1 = 20 and TH2 = 80, for example. In the ternarization 322a, when input data <TH1, the pixel to which the data is addressed is a white pixel, when TH1 ≦ input data <TH2, a halftone pixel, and when TH2 ≦ input data, a black pixel, The input data is converted into the ternary data to be represented.
[0060]
-Black pixel continuous detection 322b, white pixel continuous detection 322c-
The black pixel continuous detection 322b and the white pixel continuous detection 322c detect a location where the black pixels are continuous and a location where the white pixels are continuous by pattern matching based on the ternary data. In this embodiment, the pattern matching uses the patterns BPa to BPd and WPa to WPd of the 3 × 3 pixel matrix shown in FIG. In the pattern shown in FIG. 9, black circles indicate the above-described black pixels, white circles indicate the above-described white pixels, and blank pixels without any circles are black pixels, halftone pixels, and white pixels. It does not matter whether it is any of the above. The pixel at the center of the 3 × 3 pixel matrix is the target pixel.
[0061]
The black pixel continuous detection 322b is data indicating that the target pixel at that time is “black continuous pixel” when the distribution of the content of the ternary data matches any of the black pixel distribution patterns BPa to BPd shown in FIG. Is given to the target pixel. Similarly, when the white pixel continuous detection 322c is matched with any of the white pixel distribution patterns WPa to WPd shown in FIG. 9, the target pixel at that time is regarded as a “white continuous pixel” and data representing it is given to the target pixel.
[0062]
-Neighboring pixel detection 322d-
The next neighboring pixel detection 322d checks whether there are black continuous pixels or white continuous pixels in the vicinity of the target pixel in the neighboring pixel detection 322d with respect to the detection results of the black pixel continuous detection 322b and the white pixel continuous detection 322c. Thus, it is determined whether the target pixel is in the edge region or the non-edge region. More specifically, in this embodiment, when a block of a 5 × 5 pixel matrix includes one or more continuous black pixels and one continuous white pixel, the block is defined as an edge region. If not, the block is determined as a non-edge region.
[0063]
-Isolated point removal 322e-
Furthermore, since the character edges exist continuously, the isolated edges are corrected to the non-edge regions by the isolated point removal 322e. Then, an edge signal “1” (edge region) is output to a pixel determined to be an edge region, and an edge signal “0” (non-edge region) is output to a pixel determined to be a non-edge region.
[0064]
-White area extraction 323-
The white area extraction 323 includes binarization 323a, RGB white extraction 323b, white determination 323c, white pattern matching 323d, black determination 323e, black pattern matching 323f, and white correction 323g.
[0065]
-Binarization 323a-
The binarization 323a binarizes the edge emphasis output of the image density data (G image data) of the filter 321 with the threshold value thwsb, and the white data referred to by the preprocessing (step 7 in FIG. 5) of the white pattern matching 323d. A binary white decision signal for generating In this embodiment, the edge emphasis output is 256 gradations from 0 to 255, 0 is white without density, an example of the threshold value thwsb is 50, and the value of the edge emphasis output is thwsb = 50. If smaller, the binarization 323a determines “binarized white” and generates a binarized white determination signal “1”. When the value of the edge emphasis output is thwsb = 50 or more, a binarized white determination signal “0” is generated.
[0066]
-RGB white extraction 323b-
RGB white extraction 323b is: ) RGB white background detection, 2. 2.) Color ground detection and ) Perform valley white pixel detection to determine if the image data is a white area:
1. ) RGB white background detection
In the RGB white background detection, the white background separation operation is activated by detecting the white background area from the R, G, B image data. That is, the white background separation process is started. Specifically, as shown in the pattern WBP of FIG. 10, if all of the R, G, B image data of the 3 × 3 pixel matrix is smaller than the threshold thwss, the target pixel (the central pixel of the 3 × 3 pixel matrix) is determined. It is determined as a white area, and the white background determination signal referred to by the preprocessing (step 3 in FIG. 5) of the white pattern matching 323d is activated (“1”). This is to detect whether there is a white pixel region of a certain extent. Note that each of the R, G, and B image data has 256 gradations from 0 to 255 in this embodiment, 0 is a base level without density, a threshold thwss <thwsb, and an example of thwss is as follows: If all of the R, G, B image data are less than thwss = 40, it is determined as “white background” and a white background determination signal “1” is generated. When any of the R, G, and B image data is thwss = 40 or more, a white background determination signal “0” is generated.
[0067]
2. ) Color ground detection
To prevent a light color from being identified as a white background, detect the color background:
A. Here, first, assuming that the sign of each pixel of the 5 × 5 pixel matrix centered on the target pixel is shown in the pattern MPp of FIG. 11, the center pixel c3 (the X mark pixels of MCa to MCd) serving as the target pixel. When the RGB difference (difference between the maximum value and the minimum value of R, G, B image data addressed to one pixel) is larger than the threshold value thc, the color pixel determination signal a is set to “1” (color pixel), and is equal to or less than the threshold value thc. Is “0” (monochrome pixel);
B. When the R, G, B image data of any pixel in the peripheral pixel group Δ (in MCa to MCd in FIG. 11) on one side of the target pixel is all equal to or less than the threshold thwc, the one-side white determination signal b is set to “1”. (White pixel), and “0” (non-white pixel) when the threshold value thwc is exceeded. The threshold thwc is, for example, 20;
C. If the R, G, B image data of any pixel in the peripheral pixel group □ (in MCa to MCd in FIG. 11) on the other side of the target pixel is all equal to or less than the threshold thwc, the other side white determination signal c is set to “1”. ”(White pixel), and“ 0 ”(non-white pixel) when the threshold value thwc is exceeded;
D. In any of the patterns MCa to MCd in FIG.
a AND (exclusive NOR of b and c) = "1"
That is, when a = “1” (the pixel of interest is a color pixel) and b and c match (a white pixel on both sides of the pixel of interest or a non-white pixel on both sides), The color ground determination signal d is “1” (color ground). This color ground determination signal d is referred to in the pre-processing (step 6 in FIG. 5) of the white pattern matching 323d.
[0068]
Pattern matching as described above ~ D. The reason for this is that when the area around the black character becomes slightly colored due to the RGB reading position shift, it is not picked up as a color. At a colored position around the black character, (exclusive NOR of b and c) or “0” (one pixel on both sides of the target pixel is a white pixel and the other is a non-white pixel). In this case, the color gamut determination signal d = “0” (non-colored background). In addition, when the pixel of interest is a color pixel whose periphery is surrounded by a white background, the color background determination signal d = “1” (color background), and even when the line is intricate, a light color pixel is detected as the color background. be able to. That is, when the line is intricate, the originally white portion is not completely read in white. If the RGB difference is small, the pixel is not determined as a color pixel. Therefore, the threshold thwc is set to be stricter than the white background for which the density is to be viewed (for example, thws = 20 for thwss = 40 and thwsb = 50). ~ D. In this process, it is possible to accurately check whether the background is a white background and accurately detect a light color pixel as a color background.
[0069]
3. ) Valley white pixel detection
Next, in the valley white pixel detection, valley white pixels in a small white region that cannot be detected by the above-described RGB white background detection are detected based on the 5 × 5 pixel matrix distributions RDPa and RDPb of the G image data shown in FIG. Specifically, based on the 5 × 5 pixel matrix distribution RDPa,
miny = min (G [1] [2], G [1] [3], G [1] [4], G [5] [2], G [5] [3], G [5] [4 ]) Is calculated. That is, the minimum density miny in the pixel group with black circles in the 5 × 5 pixel matrix distribution RDPa shown in FIG. 10 is extracted. And
maxy = max (G [3] [2], G [3] [3], G [3] [4])
Is calculated. That is, the highest density maxy in the pixel group with white circles in the 5 × 5 pixel matrix distribution RDPa shown in FIG. 10 is extracted. next,
mint = min (G [2] [1], G [3] [1], G [4] [1], G [2] [5], G [3] [5], G [4] [5 ]) Is calculated. That is, the lowest density mint in the pixel group with a black circle in another 5 × 5 pixel matrix distribution RDPb shown in FIG. 10 is extracted. And
maxt = max (G [2] [3], G [3] [3], G [4] [3]) is calculated. That is, the highest density maxt in the pixel group with white circles in the 5 × 5 pixel matrix distribution RDPb shown in FIG. 10 is extracted. Here, min () is a function for detecting the minimum value. max () is a function for detecting the maximum value. next,
OUT = ((miny-maxy)> 0) # ((mint-maxt)> 0)
Is calculated. That is, of (miny-maxy) and (mint-maxt), the larger positive value is defined as a valley detection value OUT, and if the value of OUT is equal to or greater than a certain threshold, the target pixel (RDPa or RDPb Are detected as valley white pixels. In this way, the valley state of the image is detected. ) RGB white background detection compensates for difficult detection.
[0070]
-White determination 323c-
Here, the state variables MS and SS [I] used for white determination are updated. The contents are shown in FIG. Here, the state variable MS is addressed to the pixel of the processing target line (target line), and the state variable SS [I] is addressed to the pixel one line before the processing target line (processed line). This is 4-bit white background information representing the degree of white, and is generated by the processing of FIG. The maximum value represented by the state variables MS and SS [I] is set to 15, which means the whitest degree, and the minimum value is 0. That is, the state variables MS and SS [I] are data indicating the degree of white, and the larger the value represented, the stronger the white. At the start of the copying operation, the state variables MS and SS [I] are both initialized to 0.
[0071]
In the process of FIG. 5, first, the state variable of the target pixel one line before the processing target, that is, the white background information SS [I] and the pixel one pixel before the target pixel on the same line (previous pixel: processed pixel). The state variable, that is, the white background information MS is compared (step 1). If the white background information SS [I] one line before is larger, this is used as the temporary white background information MS of the target pixel (step 2). Otherwise, the state variable MS of the preceding pixel is set as the temporary white background information MS of the target pixel. This means that information closer to white of the white background information of the peripheral pixels is selected.
[0072]
After starting the copying operation, the above 1. ) When a white area, that is, a white background is detected by RGB white background detection [1. ) White background determination signal = “1” which is an output of RGB white background detection], white background information SS [I] of the pixel one line before the target pixel is updated to 15 (steps 3 and 4), and white background information MS of the target pixel Is also set to 15 (step 5). The white background information MS of the target pixel is written in the main scanning position (F) of the target pixel in the line memory for the current line (target line) in the line memory LMP shown in FIG. Information SS [I] is written in the main scanning position (F) of the target pixel in the line memory for the previous one line in the line memory LMP shown in FIG. 12 (steps 3, 4, and 5). Next, the white background information SS [I] addressed to the pixel one line before is propagated to the pixel one line before as follows (steps 14 to 17). [I] means the main scanning position of the target pixel, and [I-1] means the position of the pixel one pixel before (in the main scanning direction x) (the pixel immediately before the target pixel).
[0073]
When SS [I-1] <SS [I] -1, SS [I-1] = SS [I] -1 is set in the line memory (steps 14 and 15). That is, in the line one line before the target pixel, the white background at the position (F) of the target pixel from the white background information SS [I-1] one pixel before (E) from the position (F) of the target pixel in the main scanning direction. If the value “SS [I] −1” obtained by subtracting 1 from the information SS [I] is larger (whiteness is stronger), the pixel one pixel before the position (F) of the target pixel on the line one line before The white background information SS [I-1] addressed to (E) is updated to a value obtained by lowering the white intensity by 1 from the white background information SS [I] at the position (F) of the target pixel.
[0074]
Next, when SS [I-2] <SS [I] -2, SS [I-2] = SS [I] -2 is set in the line memory (steps 16, 17-14, 15);
Next, when SS [I-3] <SS [I] -3, SS [I-3] = SS [I] -3 is set in the line memory (steps 16, 17-14, 15).
[0075]
In the same manner, finally, when SS [I-15] <SS [I] -15, SS [I-15] = SS [I] -15 is set in the line memory (steps 16 and 17-14). , 15). The lower limit value MIN of the value of the white background information SS [I] is 0, and when it is less than 0, it is kept at 0. The same applies to step 13 described later.
[0076]
By the processing of these steps 14 to 17, the white background information SS one line before and before the main scanning position of the target pixel is changed to one for the positional deviation of one pixel in the main scanning direction x from the white background information MS of the target pixel. The white background information of the target pixel is propagated to the rear of the main scanning in the main scanning direction x one line before at the reduction rate (white propagation processing). However, this is a case where the white background information one line before is a smaller value. For example, if the pixel one line before is the above 1. ) When a white background (white area) is detected by RGB white background detection, the white background information is 15 and is the highest value, so rewriting is not performed.
[0077]
When the pixel of interest is updated and it becomes a non-white background [1. ) RGB white background detection output white background determination signal = “0”], the process proceeds from step 3 to step 6 and subsequent steps. ) Not the color gamut determination signal d = “1”, which is the output of the color gamut detection (non-color gamut), binarized white [binary white determination signal = “binarized 323a output =“ 1 ”], and when the state variable of the pixel of interest temporarily determined in Steps 1 and 2, that is, the white background information MS is equal to or greater than a threshold thw1 (for example, 13), the white background information MS addressed to the pixel of interest is incremented by 1 (Step 1). 6-10). That is, the white level is updated to a strong value by 1. The maximum value max of the white background information MS is set to 15, and when it exceeds 15, it is limited to 15 (steps 9 and 10). Even when the route has been reached, steps 5 and 14 to 17 described above are executed. That is, white propagation processing is performed.
[0078]
If the target pixel is non-colored and binary white, but the white background information MS is less than thw1 (for example, 13), thw2 (for example, 1) or more, and is a valley white pixel, the state variable MS is set to the value as it is. Hold (steps 8, 11, 12). Even when the route has been reached, steps 5 and 14 to 17 described above are executed. That is, white propagation processing is performed.
[0079]
If none of the above conditions is met, that is, if the pixel of interest is a color background or non-binary white, the white background information MS of the pixel of interest is decremented by 1 (step 13). That is, it is updated to white background information whose white level is weak by one. The minimum value MIN of the white background information MS is 0, and is kept at 0 when it is less than 0. Even when the route has been reached, steps 5 and 14 to 17 described above are executed. That is, white propagation processing is performed.
[0080]
By generating the white background information MS as described above, the white information can be propagated to the peripheral pixels via the state variable (white background information) MS on the line memory LMP. As described above, the white background information MS is generated based on the RGB white background determination signal that represents the white background when the color data (all of the R, G, and B image data) is smaller than the threshold thwss = 40. When generation of color-corresponding white background information MS of the system of 4-5-14 to 17 is included, and the edge enhancement output (output of the filter 321) of the density data (G image data) is smaller than the threshold thwsb = 50 This includes the generation of density-corresponding white background information MS for the system in steps 7 to 13-5-14 to 17 in FIG. 5 based on the white background and the binarized white determination signal.
[0081]
The white determination 323c is performed by first selecting 1. of the RGB white extraction 323b. ) RGB white background detection until a white area is detected, i.e. ) Until the RGB white background detection generates the white background determination signal “1” and the generation of the color-corresponding white background information MS (steps 3-4-5-14 to 17) starts correspondingly, the operation (step 4) Do not execute. This is to prevent an area that cannot be determined as a white area from being erroneously determined as a white pixel (white block) in white pattern matching (to be described later) of the G image data after edge enhancement processing by the filter 321.
[0082]
When the edge emphasis filter 321 is applied to a light color ground character, the data around the character becomes a value (white) having a lower level than the original image data (color ground). Therefore, the data after the edge emphasis processing of the filter 321 is used. When white pattern matching is performed, that is, when white area determination is performed based only on the generation of density-corresponding white background information MS (steps 7-13-5-14 to 17), it is easy to mistakenly determine the character ground around the color ground as a white background. A white pattern for determining a white pixel (white block), which will be described later, in an area that can be determined as a white area by generating the color-corresponding white background information MS (steps 3-4-5-14 to 17). If the white background information MS is set to the highest value so that matching is applied, and the white background is not white in step 3, the white background condition is checked in detail in step 6 and subsequent steps. Since the white background information MS, which is one parameter for determining whether to apply, is adjusted, a white pixel (white block) is erroneously determined by white pattern matching described later of the G image data after the edge enhancement processing of the filter 321. It prevents that.
[0083]
For example, when the possibility of a color pixel is high, the white background information MS is lowered (step 13), and when there is a suspicion of a color pixel, the white background information MS is held (no change) (steps 11 to 13), and a white pattern to be described later By preventing matching from being erroneously determined as a white pixel (white block), data around the character is prevented from having a lower level (white) than the original image data (color background).
[0084]
When the character is dense, the white background information MS is updated and propagated by the above-described processing (steps 3 to 5, 6 to 10, and 14 to 17), so that the possibility that the dense character region is erroneously determined as a pattern is reduced. . Also, characters such as complicated characters (for example, “call”) ) In some cases, white detection cannot be performed by RGB white background detection. ) White is detected by the valley white pixel detection, and the white background information MS is held in the path in which the YES output of step 12 goes straight to step 5 and stays on the white background tendency. The possibility of being judged is reduced.
[0085]
As described above, when the pixel of interest is a color pixel surrounded by a white background, 2. ) Color gamut detection signal d = “1” (color gamut), which is an output of color gamut detection, can detect a thin color pixel as a color gamut even where a line is intricate, and determine whether the periphery of the target pixel is white. Since the threshold value thwc for viewing is set low (thwc = 20), it is possible to detect a thin color pixel as a color background by strictly checking whether or not the periphery of a light color pixel (target pixel) is a white background. It is possible to further reduce the possibility that the character is erroneously determined as a picture.
[0086]
As described above, since a light color pixel can be detected more precisely as a color background, the process proceeds from step 6 to step 13 in FIG. 5 when the color background is detected, and the state variable MS is lowered to determine the color background as white. In addition to being able to reduce the possibility, the threshold value for generating the binarized white determination signal to be referred to in step 7 with respect to the threshold value thwss (for example, 40) for generating the white background determination signal to be referred to in step 3 If thwsb (for example, 50) is set to a large value and the color ground is not determined (step 6: NO), the probability that the binarization 323a regards it as white is increased, and steps 7 to 10 in FIG. 5 are performed. The possibility that the state variable MS is advanced and the white area is determined is increased.
[0087]
That is, the above 1. ) RGB white background detection with a threshold thwss = 40, and a strict white determination with a low probability of determining white is performed. If the white background is determined there, the state variable MS is increased by the processing from step 3 to step 4 in FIG. The possibility that the background is determined to be white is increased. If the strict white determination does not determine a white background, conversely, it is a strict color background determination with high reliability for detecting a light color pixel as a color gamut, that is, a color background. ) Refer to the result of color gamut detection, and if it is not determined to be a color gamut, again, a sweet white determination with a threshold thwsb = 50 that has a high probability of determining white is performed, that is, the binarization 323a. If it is determined that it is white, the state variable MS is increased to increase the possibility that the character background is determined to be white (steps 7 to 10). Because of this processing (steps 6 to 10), when the background density unevenness is thinner than the color background and the light color pixel detected, for example, when there is unevenness in the background of the original such as show-through, the fine background unevenness of the original As a result, it is possible to prevent the state variable MS from changing significantly in binary, and to prevent the next white pattern matching 323d from determining whether it is a white pixel or not in the scanning direction. As a result, when the background is a light color background, fine color loss (white background) does not appear in conjunction with the fine background unevenness of the document such as show-through.
[0088]
-White pattern matching 323d-
Whether the background is white is determined by whether or not there is a continuous white pixel in a 5 × 5 pixel unit block centered on the target pixel. Therefore, for the target pixel, when the following expression is satisfied, the target pixel is temporarily determined as a white pixel and white pattern matching is performed:
(Non-color pixel & (white background information MS ≧ thw1 (13)) & binarized white) #
(Non-color pixel & (white background information MS ≧ thw2 (1)) & valley white pixel & binarized white)
Here, the target pixel for checking whether or not this conditional expression is satisfied has been subjected to the white propagation processing in Steps 5 and 14 to 17 in FIG. “White background information MS” is the white background information MS [I] of the target pixel to be checked after the white propagation process. However, MS [I] is the white background information after the white propagation processing, and I is the position of the pixel of interest to be checked in the main scanning direction x, and the state variable MS is set in the white determination 323c. The position of the target pixel to be calculated is different from the position in the main scanning direction x.
[0089]
In the above conditional expression, “non-color pixel” is the same as that in 2. ) The color gamut determination signal d, which is the output of the color gamut detection, is “0”, “binarized white” is the binarized white determination signal of the binarized 323a is “1” (binary white) And “Tanihira Pixel” are described in 3. above. ) Means that the detection result of valley white pixel detection is a valley white pixel, and # means a logical sum (OR: or). The white pattern matching is to check whether the output (whether it is a white pixel) determined by the above conditional expression corresponds to one of the vertical and horizontal diagonal continuity patterns PMPa to PMPd in FIG. White circles attached to the patterns PMPa to PMPd mean white pixels. It does not matter whether the other blank pixels are white pixels.
[0090]
If the white pixel distribution of the 5 × 5 pixel matrix centered on the target pixel corresponds to the pattern PMPa, PMPb, PMPc or PMPd in FIG. 12, the target pixel is determined to be a white pattern pixel, and the result of this white pattern matching is determined. 4 × 4 pixels are divided into blocks. That is, when one or more white pattern pixels exist in 4 × 4 pixels, the block is a white block. That is, all the pixels of 4 × 4 pixels are white pixels.
[0091]
-Black judgment 323e-
A pixel whose G image data exceeds the threshold thbk is determined as a black pixel. Pixels less than thbk are white pixels.
[0092]
-Black pattern matching 323f-
Black pattern matching is performed using the black / white pixel determination result of each pixel in the black determination 323e. If all the pixels of the 3 × 3 pixel matrix centered on the target pixel that is the current processing target are all black pixels as shown in the pattern BBP of FIG. 10, the target pixel is determined to be a black pattern pixel. Then, the black pattern matching result is divided into blocks of 4 × 4 pixels as one block unit. That is, when one or more black pattern pixels exist in 4 × 4 pixels, the block is a black block. That is, all the 4 × 4 pixels are black pixels.
[0093]
-White correction 323g-
Here, 4. ) White block correction, 5. ) Black block correction and 6. ) Extract a white area by white area determination. FIG. 12 shows a block pattern BCP. One square of the pattern BCP is one block, and one block is 4 × 4 pixels.
[0094]
4). ) White block correction
In white block correction, in a 15 × 11 block centered on a target block marked with × of the block pattern BCP, when one or more white candidate blocks exist in each of the 6 × 4 block areas at the four corners, the target block Is given white block correction data. As a result, a region surrounded by a white background is set as a white region.
[0095]
5. ) Black block correction
In the black block correction, if there is one or more white blocks in the 3 × 3 block matrix centered on the target block, and one or more black blocks exist in the 5 × 5 block matrix centered on the target block, Black block correction data is given to the target block. Thus, the boundary between the white block and the black block is set as a white area.
[0096]
6). ) White area judgment
Next, in the white area determination, if black block correction data or white block correction data exists, the white area is determined.
[0097]
In FIG. 13, the black protrusions surrounded by the circles Bp1 to Bp4 have one or more white candidate blocks in each of the 6 × 4 block regions at the four corners in the 15 × 11 block centered on the block of interest described above. The white block is replaced by white block correction that gives white block correction data to the target block. Making a black area surrounded by a white background like the black protrusions surrounded by the circles Bp1 to Bp4 as a white area reduces the possibility of determining that it is a picture part. In the comprehensive determination 326 described later, the non-white area is determined to be a pattern, but the possibility of erroneously determining a black area surrounded by a white background such as a black protrusion surrounded by the circles Bp1 to Bp4 is reduced. Furthermore, 5. ) Black block correction and 6. ) In white area determination, the boundary between the black background and the white background is determined as a white area (character area), so the character edge is determined as a white background regardless of the thickness of the character. It becomes possible.
[0098]
-Adjustment of text / photo judgment level-
As described above, in the white area extraction 323, in the white determination 323c, the white background determination signal of the RGB white extraction 323b, the color background determination signal d and the valley white pixel determination signal, and the binarized white determination signal of the binarization 323a, The white background information MS, which is a state variable representing the degree of white, corresponding to. Then, the white pattern matching 323d temporarily determines whether the pixel of interest is a white pixel based on the color background determination signal d, the white background information MS, the binarized white determination signal, and the valley white pixel determination signal. Whether or not the pixel is a white pixel is determined by white pixel distribution pattern matching for the mat risk. Using this result and the results of the black determination 323e and the black pattern matching 323f, the white correction 323g determines whether the target pixel is the boundary between the black background and the white background (white region: character region).
[0099]
The white background determination signal (see step 3 in FIG. 5) of the RGB white extraction 323b is “1” (white background) when all of the R, G, B image data of the pixel of interest is smaller than the threshold thwss = 40. Increasing this threshold thwss increases the probability of determining a large value of the white background information MS, and increases the probability of extracting the “white region” (the boundary between the black background and the white background boundary: the character region) (ie, extracting the pattern region). Probability decreases). The reverse occurs when the threshold value thwss is decreased.
[0100]
The binarized white determination signal of the binarization 323a (refer to step 7 in FIG. 5) is “1” (binarized white) if the edge enhancement output of the G image data of the filter 321 is smaller than the threshold value thwsb = 50. It is. Increasing the threshold thwsb increases the probability of determining a large value of the white background information MS, and increases the probability of extracting the “white region” (that is, the probability of extracting the pattern region decreases). If the threshold value thwsb is reduced, the opposite is true.
[0101]
Since the image data for “white area” is subjected to image processing for clearly expressing the character image in a later step, when the threshold values thwss and thwsb are increased, image processing with high priority is performed on the characters. The image data in the non-white area, that is, the picture (picture) area, is subjected to image processing for faithfully representing the picture or picture in a later process. Therefore, if the threshold values thwss and thwsb are reduced, the priority is given to the picture (picture). High image processing is performed.
[0102]
By the way, when the color background determination signal d (refer to step 6 in FIG. 5) of the RGB white extraction 323b is “1” (color background), the white background information MS is lowered, and the probability of extracting the “white area” is low. (That is, the probability of extracting the pattern area increases). 2. B) Processing for generating a color gamut determination signal d by color gamut detection. , C.I. When the threshold thwc (for example, 20) used in the above is reduced, the probability of simultaneously detecting neighboring pixels (Δ and □ in FIG. 11) as color pixels, that is, the probability of (exclusive NOR of b and c) = “1” increases. The probability of obtaining the color background determination signal d = “1” (color background) increases, and the probability of extracting the “white area” decreases (that is, the probability of extracting the pattern area increases).
[0103]
Therefore, in the present embodiment, in the operation / display unit OPB of FIG. 2, the menu display of the input mode by key input and the operation of the key image (parameter designation key and up / down key) on the menu screen displayed on the liquid crystal display. The threshold values thwss, thwsb, and thwc are adjusted as follows by adjusting the “character / photo level” in the parameter adjustment to be adjusted by:
Parameter Text side adjustment value Standard Photo side adjustment value
6 5 4 3 2 1 0
thwss 46 44 42 40 38 36 34
thwsb 56 54 52 50 48 46 44
thwc 26 24 22 20 18 16 14
That is, the standard value (default) of the parameter “character / photo level” that is adjusted and set by the operator on the operation / display unit OPB is “3”, and the default value is the above-described character / photo level and threshold values thwss, thwsb. 3 is written in the ROM 358 shown in FIG. 3 together with a conversion table representing the relationship between the CPU 357 and the thwc. When the power is turned on to the IPU 300 shown in FIG. The default value of the level is read, and the corresponding threshold values thwss, thwsb, and thwc are read from the conversion table, written in the registers addressed to the respective threshold values in the RAM 356, and used for the above-described processing in the white area extraction 323. After that, the character / photo level is adjusted by input from the operation board OPB. When the adjusted value A is given from the main controller 10 to the CPU 357, the CPU 357 sets the parameters thwss, thwsb and thwc corresponding to the adjusted value A. Are read from the conversion table of the ROM 358 and written to the parameter register of the RAM 356.
[0104]
When the threshold values are set to the standard values thwss = 40, thwsb = 50, and thwc = 20, the operator uses the operation board OPB to increase the value of “character / photo level” by i (for example, 1) to “Up”. Then, the thresholds thwss, thwsb, and thwc are set to values that are changed in the character priority direction by 2i (2). Conversely, when the operator decreases the value of “character / photo level” by “Down” by i (for example, 1), the thresholds thwss, thwsb, and thwc are set to values that are changed in the photo priority direction by 2i (2).
[0105]
-Halftone dot extraction 324-
The first halftone dot peak detection 324a uses G image data, and forms pixels of halftone dots (referred to as halftone peak pixels) from pixel density information in a two-dimensional local region having a predetermined size. Is a circuit for detecting For a local region, the center pixel of the region is detected as a halftone peak pixel when the following two conditions are met simultaneously:
Condition 1: The density level of the central pixel is maximum (mountain peak) or minimum (valley peak) in the local region;
Condition 2: The absolute value of the difference between the average density level of the pixel pair and the density level of the central pixel is greater than or equal to the threshold Th for all pixel pairs that are in point symmetry with respect to the central pixel.
[0106]
With reference to FIG. 14, the detection process of the 1st halftone peak detection 324a is demonstrated concretely. In this example, a 5 × 5 pixel matrix (M × M pixel matrix when generalized) mask is used as the local region. If the sign of each pixel of the 5 × 5 pixel matrix is as shown in the pattern MPp of FIG. 11, the density Lc of the center pixel c3 serving as the target pixel is the maximum or minimum compared to the densities L1 to L8 of the surrounding pixels. And
abs (2Lc-L1-L8) ≧ Lth
And abs (2Lc-L2-L7) ≧ Lth
And abs (2Lc-L3-L6) ≧ Lth
And abs (2Lc-L4-L5) ≧ Lth
At this time, the center pixel (Lc) of the mask is detected as a halftone dot peak pixel. The abs function means taking an absolute value. Lth is a threshold value (fixed value).
[0107]
Specifically, the surrounding pixels are pixels to which a quadrangle of the surrounding pixel distribution pattern MPa or MPb shown in FIG. 14 is added. When either halftone dot peak pixel detection based on the surrounding pixel distribution patterns MPa and MPb detects a halftone peak pixel, a detection signal that represents a halftone dot pixel at the current pixel of interest (center pixel c3) give. The reason for using the two patterns is to deal with a wide range of halftone dot lines.
[0108]
The pattern MPa is: L1 = b2, L2 = b3, L3 = b4
L4 = c2, L5 = c4, L6 = d2,
L7 = d3, L8 = d4,
It is determined. Here, L1 = b2 means that the density of the pixel b2 is set to the value of L1 in the above-described halftone peak pixel detection calculation.
[0109]
The pattern MPb is: L1 = b2, L2 = a3, L3 = b4
L4 = c1, L5 = c5, L6 = d2,
L7 = e3, L8 = d4,
It is determined.
[0110]
In the case of copying, enlargement / reduction in the sub-scanning direction y is performed at low and high document scanning speeds of the scanner 200. Therefore, the scanner 200 provides image data with enlargement / reduction in the sub-scanning direction y. . Therefore, at the time of reduction, the patterns MPc and MPd shown in FIG. 14 are used instead of the above-described patterns MPa and MPb. When enlarging, patterns MPe and MPf shown in FIG. 14 are used. In addition, in the patterns MPe and MPf, a pixel given a triangle mark may be added to the above-mentioned “peripheral pixels”.
[0111]
The second halftone peak detection 324b detects halftone dots using the B data, and has the same function as the first halftone peak detection 324a. Since the first halftone peak detection 324a uses G image data and reacts to most colors, but does not react to Y, the second halftone peak detection 324c uses B image data, It is a supplementary object aimed at detecting the Y dot peak.
[0112]
The halftone dot region detection 324c is a two-dimensional small-sized pixel having a predetermined size, which is a peak and valley halftone dot pixel detected by either the first halftone dot peak pixel detection 324a or the second halftone dot peak pixel detection 324b. It counts for every area | region, and makes the sum total of the halftone dot peak pixel of a peak and a valley the count value P of a small area. When the count value P is larger than the threshold value Pth, all the pixels in the small area (or in the case of pixel unit processing, only the central pixel of the small area) are determined as halftone dot areas. The result of the determination is stored in the temporary memory 324d.
[0113]
The threshold value Pth is adaptively changed according to the halftone / non-halftone dot determination result (peripheral feature information) of the processed area in the vicinity of the small area of interest. In the present embodiment, two values TH1 and TH2 (where TH1> TH2) are prepared as the threshold value Pth, and one of the two values TH1 and TH2 is determined based on the determination result of the processed region near the target small region stored in the temporary memory 324d. Select a value. That is, if the neighboring area is determined to be a non-halftone dot area, there is a high possibility that the area is a line drawing area. Therefore, TH1 whose conditions are severer is selected as the threshold value Pth in order to reduce false detection. On the other hand, if it is determined that the neighboring region is a halftone dot region, since there is a high possibility that it is a halftone dot region, TH2 where the condition is relaxed is used as the threshold value Pth. Note that TH1 is selected as the initial value of the threshold value Pth.
[0114]
AMP on FIG. 14 shows the distribution of the above-mentioned small regions. Each of S1 to S4 of the small area distribution pattern AMP is, for example, a small area (block) having a size of 4 × 4 pixels. S4 is a small area of interest, and S1, S2, and S3 are processed small areas. Suppose that When it is determined that all of S1, S2, and S3 are halftone areas, Th2 is used as the threshold value Pth for the determination of S4. If any one of S1, S2 and S3 is determined to be a non-halftone area, TH1 is selected as the threshold value Pth. A halftone dot region detection signal ht is output from the halftone dot extraction 324 when it is determined as a halftone dot region and is “1” when it is determined as a non-halftone dot region. However, this is only an example, and TH2 is selected when any one of S1, S2, and S3 is determined to be a halftone dot region, and TH1 is selected only when all are determined to be non-halftone regions. May be selected. Furthermore, the neighborhood area to be referred to may be only S1 or only S2.
[0115]
-Color determination 325-
When detecting color (chromatic) pixels and black (achromatic) pixels in a document, there is a relative reading shift of R, G, and B due to sampling of each color image data and mechanical accuracy. . This will be described with reference to FIG. FIG. 15A shows an image density signal. The black density signal is ideally black when the levels of the R, B, and G density signals coincide with each other. However, the actual image data is obtained by forming an image on the CCD with a lens and digitizing the image signal of the CCD. FIG. 15B shows an ideal high and low waveform. However, since a general scanner uses a three-line CCD sensor, the R, G, B line sensors are not read simultaneously in time, but the R, G, B line sensors are equal. Since they are arranged at intervals and cannot be read simultaneously in time, the reading position will inevitably shift. For example, the R, G, and B color density signals representing the level-change black shown in FIG. 15B are relatively shifted as shown in FIG. If this shift is large, a color shift appears at the periphery of the black area.
[0116]
-Hue division 325a-
The color determination 325 is for finding a chromatic color region. Input data R, G, and B are converted into signals of c, m, y, and color determination w (white) by hue division 325a. As an example of hue division, each color boundary is obtained, and the difference between the maximum value and the minimum value of R, G, and B image data in one pixel is defined as an RGB difference, and the following is performed. Here, the R, G, B image data becomes black (darkens) as the number increases:
1). RY hue region boundary (ry)
R-2 * G + B> 0
2). YG hue region boundary (yg)
11 * R-8 * G-3 * B> 0
3). GC hue region boundary (gc)
1 * R-5 * G + 4 * B <0
4). CB hue region boundary (cb)
8 * R-14 * G + 6 * B <0
5). BM hue region boundary (bm)
9 * R-2 * G-7 * B <0
6). MR hue region boundary (mr)
R + 5 * G-6 * B <0.
[0117]
7). Color determination w (white) pixel determination:
(R <thwa) & (G <thwa) & (B <thwa), y = m = c = 0. thwa is a threshold value.
[0118]
8). Y pixel determination:
If (ry == 1) & (yg == 0) & (RGB difference> thy), then y = 1 and m = c = 0. thy is a threshold value.
[0119]
9). G pixel determination:
If (yg == 1) & (gc == 0) & (RGB difference> thg), c = y = 1 and m = 0. thg is a threshold value.
[0120]
10). C pixel determination:
If (gc == 1) & (cb == 0) & (RGB difference> thc), c = 1 and m = y = 0. thc is a threshold value.
[0121]
11). B pixel determination:
If (cb == 1) & (bm == 0) & (RGB difference> thb), m = c = 1 and y = 0. thb is a threshold value.
[0122]
12). M pixel determination:
If (bm == 1) & (mr == 0) & (RGB difference> thm), then m = 1 and y = c = 0. thm is a threshold value.
[0123]
13). R pixel determination:
If (mr == 1) & (ry == 0) & (RGB difference> thr), y = m = 1 and c = 0. thr is a threshold value.
[0124]
14). BK pixel determination: 7). To 13). If not, y = m = c = 1.
[0125]
Further, the color determination w pixel is determined. The conditions are as follows:
(R <thw) & (G <thw) & (B If <thw), the color pixel is set to w pixel and output as w. thw is a threshold value. Here, the priority of 7) to 14) is given priority to the smaller number. The above-mentioned thresholds thwa, thy, thm, thc, thr, thg, thb are thresholds determined before copying (processing). The relationship between thw and thwa is thw> tha. The output signal is 3 bits of data of 1 bit for each of c, m, and y, and 1 bit of w for color pixel detection for color determination. Here, the threshold is changed for each hue because the threshold corresponding to the hue area is determined for each hue area when the chromatic range is different. This hue division is an example, and any formula may be used.
[0126]
The outputs c, m, y, and w of the hue division 325a are stored in the line memories 325b to 325e for 5 lines and input to the color pixel determination 325f.
[0127]
-Color pixel determination 325f-
FIG. 6 shows the contents of the color pixel determination 325f. The data of c, m, y, and w for 5 lines are input to pattern matching 325f5 to 325f7 and counts 325f1 to 325f. First, the pattern matching 325f6 in the flow for obtaining the B / C signal will be described.
[0128]
-Pattern matching 325f6-
When the color pixel w pixel exists, the pixel is corrected to c = m = y = 0. This correction increases the white level of the 5 × 5 pixel matrix centered on the pixel of interest. Next, the pixel of interest is a pixel (color) other than 1 (c = m = y = 1) or all 0 (c = m = y = 0) of the pixels determined by the hue division 325a. Is determined by checking whether the 5 × 5 pixel matrix matches the following pattern:
1). Color pixel pattern group
1-1). Pattern 1-1 (pm1)
D23 & D33 & D43
1-2). Pattern 1-2 (pm2)
D32 & D33 & D34
1-3). Pattern 1-3 (pm3)
D22 & D33 & D44
1-4). Pattern 1-4 (pm4)
D24 & D33 & D42
The center pixel (target pixel) is D33. FIG. 16 shows these patterns pm1 to pm4. White circles on these patterns indicate that at least one of c, m, and y is 1. Pattern matching is used to prevent picking up isolated points. On the other hand, when detecting a small area color such as a halftone dot, the central pixel is a pixel (color pixel) other than 1 (c = m = y = 1) or all 0 (c = m = y = 0). It may be determined whether or not.
[0129]
2). Color thin line pattern group
Detect a color line surrounded by white. The pattern used for this is shown in FIG. In FIG. 17, pixels with white circles are pixels in which c, m, and y are all 0. When the distribution of the data (c, m, y) of the 5 × 5 pixel matrix centered on the target pixel (center pixel) matches any of the patterns pw11a to pw14d in FIG. 17, the target pixel (center pixel) at that time ) Is considered a color line pixel:
2-1). Pattern 2-1 (pw11a-pw11d)
((D12 & D13 & D14) & (D42 & D43 & D44)) #
((D12 & D13 & D14) & (D52 & D53 & D54)) #
((D22 & D23 & D42) & (D42 & D43 & D44)) #
((D22 & D23 & D42) & (D52 & D53 & D54))
2-2). Pattern 2-2 (pw12a-pw12d)
((D21 & D31 & D41) & (D24 & D34 & D44)) #
((D21 & D31 & D41) & (D25 & D35 & D45)) #
((D22 & D23 & D24) & (D24 & D34 & D44)) #
((D22 & D23 & D24) & (D25 & D35 & D45))
2-3). Pattern 2-3 (pw13a-pw13d)
((D11 & D21 & D12) & (D35 & D44 & D53)) #
((D11 & D21 & D12) & (D45 & D44 & D55)) #
((D13 & D22 & D31) & (D35 & D44 & D53)) #
((D13 & D22 & D31) & (D45 & D44 & D55))
2-4). Pattern 2-4 (pw14a-pw14d)
((D13 & D24 & D35) & (D41 & D51 & D52)) #
((D14 & D15 & D25) & (D41 & D51 & D52)) #
((D13 & D24 & D35) & (D31 & D42 & D53)) #
((D14 & D15 & D25) & (D31 & D42 & D53)).
[0130]
3). White area pattern group
Pattern matching is performed where c, m, and y are all zero. The pattern used for this is shown in FIG. In FIG. 18, pixels with white circles are pixels in which c, m, and y are all 0. When the distribution of the data (c, m, y) of the 5 × 5 pixel matrix centered on the target pixel (center pixel) matches any of the patterns pw21a to pw24d in FIG. 18, the target pixel (center pixel) at that time ) As white area pixels:
3-1). Pattern 3-1 (pw21a-pw21d)
(D21 & D31 & D41) #
(D22 & D32 & D42) #
(D24 & D34 & D44) #
(D25 & D35 & D45)
3-2). Pattern 3-2 (pw22a to pw22d)
(D12 & D13 & D14) #
(D22 & D23 & D24) #
(D42 & D43 & D44) #
(D52 & D53 & D54)
3-3). Pattern 3-3 (pw23a-pw23d)
(D52 & D51 & D41) #
(D53 & D42 & D31) #
(D35 & D24 & D13) #
(D25 & D15 & D14)
3-4). Pattern 3-4 (pw24a-pw24d)
(D54 & D55 & D45) #
(D53 & D44 & D35) #
(D31 & D22 & D13) #
(D21 & D11 & D12).
[0131]
4). Determination of color pixel candidate 2
If the pattern matching result extracted above matches the following pattern, the target pixel is set as a color pixel candidate 2 for color determination:
((pm1 == 1) & ((pw11 == 1) # (pw21! = 1))) #
((pm2 == 1) & ((pw12 == 1) # (pw22! = 1))) #
((pm3 == 1) & ((pw13 == 1) # (pw23! = 1))) #
((pm4 == 1) & ((pw14 == 1) # (pw24! = 1))))
Here, (pm1 == 1) means that the data distribution centered on the pixel of interest matches the pattern pm1, and (pw11 == 1) means that it matches any of the patterns pw11a to pw11d. This means that (pw21! = 1) matches with any of the patterns pw21a to pw21d. & Means logical product, and # means logical sum. With this pattern matching, a color pixel surrounded by a white area is set as a color pixel candidate, and when there is a white area other than that, it is not set as a color pixel. Those matched by color pixel pattern matching without a white area are color pixel candidates.
[0132]
-Count 325f1-
When there are w pixels for color determination in the 5 × 5 pixel matrix centered on the target pixel, the c, m, y data determined by the hue division 325a of the pixel is corrected to c = m = y = 0. To do. This correction increases the white level of the pixel matrix. Then, the number of c, m, and y 1 (c = 1, m = 1, y = 1) of each pixel in the pixel matrix is counted. If the difference between the maximum value and the minimum value of the count values for c, m, and y is greater than or equal to thcnt and the minimum value is less than thmin, color pixel candidate 1 is determined. thcnt and thmin are threshold values set before copying (processing). The plane is expanded to y, m, and c, the number is counted for each plane in the N × N matrix, and the minimum value is assumed to be black. This makes it possible to correct even if black pixel reading fails. A chromatic pixel is determined based on the difference between the maximum value and the minimum value. This corrects a pixel from which a black pixel is not read, and extracts a chromatic pixel. If there is a chromatic pixel of a certain pixel in a 5 × 5 pixel matrix centered on the pixel of interest, the pixel of interest is a chromatic pixel.
[0133]
-Color pixel determination 325f8-
Based on the outputs of the pattern matching 325f6 and the count 325f1, a color pixel determination 325f8 determines whether the pixel is a color pixel. If the color pixel candidate 1 and the color pixel candidate 2, the color pixel 1 is assumed.
[0134]
-Blocking 325f9-
The output of the color pixel determination 325f8 is blocked at block 325f9. Blocking means that if there is one or more color pixels 1 in a 4 × 4 pixel matrix, the entire 4 × 4 pixel matrix is output as one color pixel block. In the processing after blocking 325f9, 4 × 4 pixels are regarded as one block and output is made in block units.
[0135]
-Isolated point removal 325f10-
Blocked data is removed as an isolated point in isolated point removal 325f10 if there is no color pixel block in the adjacent block of the target block.
[0136]
-Expansion 325f11-
In the expansion 325f11, the output of the isolated point removal 325f10 is expanded to 5 × 5 blocks when there is one color pixel block. The reason for expansion is to prevent black character processing around the color pixel. Here, the output B / C signal outputs L (chromatic) when the color pixel is one block, and outputs H (achromatic) at other times.
[0137]
-Count 325f2-
When the w determination pixel exists in the 5 × 5 pixel matrix centered on the target pixel, the c, m, and y data determined in the hue division 325a of the pixel are corrected to c = m = y = 0. . This correction increases the white level of the pixel matrix. Then, the number of c, m, and y of 1 (c = 1, m = 1, y = 1) of each pixel in the pixel matrix is counted. If the difference between the maximum value and the minimum value of the count values for c, m, and y is greater than or equal to thacnt and less than the minimum value, the pixel of interest is set as a color pixel candidate 1. thacnt and thamin are threshold values set before copying (processing).
[0138]
-Color pixel determination 325f12-
Based on the outputs of the pattern matching 325f6 and the count 325f2, the color pixel determination 325f12 determines whether or not the pixel is a color pixel. If it is the color pixel candidate 1 and the color pixel candidate 2, it is set as the color pixel 2.
[0139]
-Blocking 325f13-
The output of the color pixel determination 325f12 is blocked by a block 325f13. That is, if there is one or more color pixels 2 in a 4 × 4 pixel matrix, the entire 4 × 4 pixel matrix is output as a color pixel 2 block. In the processing after blocking 325f13, 4 × 4 pixels are regarded as one block and output is made in block units.
[0140]
-Density 325f14-
In order to remove an isolated block, if there are three or more active conditions (color pixel 2 blocks) in the 3 × 3 block and the target block is active (color pixel), the target block is defined as an active block (color pixel 2 block). ).
[0141]
-Count 325f3-
The number of c, m, y of 1 (c = 1, m = 1, y = 1) of each pixel in the 5 × 5 pixel matrix centered on the target pixel is counted. If the difference between the maximum value and the minimum value of c, m, and y for each of c, m, and y is equal to or greater than tha1cnt, and the counted minimum value of c, m, and y is less than tha1min, color pixel candidate 3 is determined. tha1cnt and tha1min are threshold values set before copying (processing).
[0142]
-Pattern matching 325f5-
Whether the pixel (c, m, y) determined by color pixel detection is a color pixel is determined by pattern matching using a 5 × 5 pixel matrix. The pattern is the same as that of pattern matching 325f6. The pixel matched by pattern matching is set as a color pixel candidate 4.
[0143]
-Color pixel determination 325f15-
If it is the color pixel candidate 3 and the color pixel candidate 4, it is set as the color pixel 3.
[0144]
-Blocking 325f16-
The output of the color pixel determination 325f15 is blocked at a block 325f16. That is, if there is one or more color pixels 3 in a 4 × 4 pixel matrix, the entire 4 × 4 pixel matrix is output as a color pixel 3 block. In the processing after blocking 325f16, 4 × 4 is regarded as one block and output in block units.
[0145]
-Density 325f17-
If there are three or more active conditions (color pixel 3 blocks) in the 3 × 3 block for removing the isolated block and the target block is active (color pixel 3), the target block is changed to the active block (color pixel 3). Block).
[0146]
-Count 325f4-
The number of 1 of c, m, and y (c = 1, m = 1, y = 1) determined by the hue division 325a of each pixel in the 5 × 5 pixel matrix centered on the target pixel is counted. If the minimum value of each count value of c, m, and y is greater than or equal to thabk, the pixel of interest is set as a black pixel candidate 1. Thabk is a threshold value set before copying (processing).
[0147]
-Pattern matching 325f7-
In a 5 × 5 pixel matrix centered on the pixel of interest, pattern matching is performed on pixels with c = m = y = 1.
[0148]
1-1). Pattern 1-1 (pm1)
D23 & D33 & D43
1-2). Pattern 1-2 (pm2)
D32 & D33 & d34
1-3). Pattern 1-3 (pm3)
D22 & D33 & D44
1-4). Pattern 1-4 (pm4)
D42 & D33 & D24
These patterns are shown in FIG. 16, and the pixels with circles in the figure are pixels with c = m = y = 1. When matching with any of these patterns, the target pixel is set as a black pixel candidate 2.
[0149]
-Achromatic determination 325f18-
If the pixel of interest is black pixel candidate 1 and black pixel candidate 2, it is determined as a black pixel.
[0150]
-Blocking 325f19-
Black pixel output is blocked at block 325f19. In this block formation, if there is one or more black pixels in a 4 × 4 pixel matrix, the entire 4 × 4 pixel matrix is output as a black pixel block. In the processing after blocking 325f19, 4 × 4 pixels are regarded as one block and output is made in block units.
[0151]
-Expansion 325f20-
If the target block is active (black pixel block) and its surrounding pixels are non-active (non-black pixel) in the 3 × 3 block matrix, the target block is made non-active (non-black pixel block).
[0152]
-Overall color pixel determination 325f21-
If the target block is determined to be active (color pixel 2) in the color pixel determination 325f12 and not determined to be active (black pixel) in the achromatic determination 325f18, the target block is determined to be a color (color block). The color is also determined when the color pixel determination 325f15 is active (color pixel).
[0153]
-Expansion 325f22-
In order to regard small characters as continuous for the block determined to be a color in the overall color pixel determination 325f21, if there is even one active block in the 9 × 9 block matrix centered on the target block, the target block is determined. The active block. Here, the reason for the large expansion is to fill the gap between the characters.
[0154]
-Continuous count 325f23-
In the continuous count 325f23, it is determined whether the original is a color original or a monochrome original by looking at the continuity of the color pixel blocks. By counting the number of continuous color pixels in the output data (color pixel block) of the expansion 325f22, it is determined whether the document is a color document.
[0155]
FIG. 7 shows the contents of this determination process. When the target pixel is in the color pixel block, the number of continuous color pixels of the target pixel is calculated with reference to the number of continuous color pixels of the upper left, upper, upper right and left pixels of the target pixel (steps 21 to 26). Here, if the target pixel is, for example, the c3 pixel of the 5 × 5 pixel distribution pattern MPp in FIG. 11, the upper left, upper, upper right, and left pixels are the pixels b2, b3, b4, and c2, respectively. If the pixel of interest is not in the color pixel block, it is given a continuous color pixel number of 0 (steps 21-27).
[0156]
When the target pixel is in the color pixel block, first, the number of continuous color pixels of the upper pixel (b3) of the target pixel (c3) is checked (step 22). A value obtained by adding 1 to the number of continuous color pixels of (b4) is given (step 24), and the number of continuous color pixels of the upper right pixel (b4) is added to the reference value A when the number of continuous color pixels of the upper pixel (b3) is 0. (Step 23). Next, a value obtained by adding 1 to the number of continuous color pixels of the upper left pixel (b2) is given to the reference value B, and a value obtained by adding 1 to the number of continuous color pixels of the upper pixel (b3) is given to the reference value B. Further, a value obtained by adding 1 to the number of continuous color pixels of the left pixel (c2) is given to the reference value D (step 25). Then, the highest value among the reference values A, B, C and D is set as the number of continuous color pixels of the target pixel (c3) (step 26).
[0157]
When the number of continuous color pixels is given to the target pixel (c3) as described above, it is checked whether the number of continuous color pixels is equal to or larger than the set value THACS (step 28). Is determined (step 29), and the processing of the continuous count 325f23 is ended there. If the number of continuous color pixels is less than the set value THACS, the target pixel is updated to the next pixel in the scanning directions x and y, and the above-described processing is repeated. As a result of performing the above-described processing on the entire surface of the original, if the number of continuous color pixels is less than the set value THACS until the end (steps 30 to 34), it is determined that the original is a monochrome image.
[0158]
The above-mentioned number of consecutive color pixels is the sum of almost a fresh colored line segment and a horizontal colored line segment. The number of consecutive color pixels in the upper right is different from others because it prevents double counting. Specific data on the number of continuous color pixels is shown in FIG. A small square including a number shown in FIG. 19 is a color pixel, and the number is a continuous number of color pixels given to the pixel. A block consisting of a series of small squares with numbers is a color pixel group, and even if one continuous color pixel in any color pixel group on the same document exceeds the set value THACS, it is a color document. , The determination of color or black and white is confirmed (steps 28 and 29).
[0159]
The reason why it is divided from the color pixel determinations 1 to 3 (325f8 to 325f15) is to increase the determination accuracy of whether it is a color document or a monochrome document. The color pixel determination for black character processing is local and not so noticeable even if an erroneous determination is made. However, the determination of whether the original is a color original or a monochrome original affects the entire original if an erroneous determination is made. Therefore, the counts 325f1-f4 are independent. Originally, it is better to make the hue division 325a independent. However, making the hue division 325a independent is not preferable because the memory of the pattern matching 325f5-f7 increases. By changing the color pixel parameter (color pixel 1-3) with the count 325f1-f4 parameter (color pixel candidate 1,3, black pixel candidate 1), an increase in the amount of memory is reduced. The reason why the color pixel determinations 2 and 3 (325f12, 325f15) are provided is to detect a low density color such as yellow of a fluorescent pen, and further, an achromatic determination (black pixel determination) 325f18 is provided. This is because correction is performed when erroneous detection is performed when the density is lowered. Light colors such as highlighters can be corrected with black data to a certain extent without any problem. When extracting multiple color pixels, the level of w (white) is only changed, so there is no need to have two memories for color pixel detection, and a capacity of one + 1 line is possible. is there.
[0160]
In the continuous count 325f23, the count value is counted by referring to the count data of the previous line and the count data of the current line. Therefore, it is possible to accurately count the continuity of the peripheral pixels, and thus count the continuity of the color pixels. It becomes possible. In this embodiment, the hue determination is performed on the R, G, B image data. However, the hue determination is not limited to the R, G, B image data, and the hue determination is performed on the luminance color difference (for example, Lab). It is easy.
[0161]
-Comprehensive judgment 326
The overall determination 326 includes a character determination 326a, an expansion process 326b, a character determination 326c, and a decode 326d.
[0162]
-Character determination 326a-
In the character determination 326a, if the result of the edge extraction 322 is an edge, the result of the halftone extraction 324 is no halftone, and the result of the white area extraction 323 is a white area, it is determined as a character edge. Otherwise, it is determined as a non-character edge (whether a pattern or a character).
[0163]
-Expansion treatment 326b-
In the expansion process 326b, the result of the character determination 326b is subjected to OR processing of 8 × 8 blocks, and then AND processing of 3 × 3 blocks is performed to perform expansion processing of 4 blocks. That is, if any block of the 8 × 8 block centered on the target block is a character edge, it is assumed that the target block is also a character edge block, and all 3 × 3 blocks centered on the target block are If it is a character edge, the target block is determined as the character edge, and the target block and three blocks adjacent to the target block are regarded as the character edge. The reason why the AND process is performed after the OR process, particularly in the case of a black character, when a small non-black character region exists around the black character region, a sense of incongruity may be felt due to a difference in processing. For example, black looks thin. In order to prevent this, the non-black character area is enlarged by OR processing. The AND process is performed to obtain a desired expansion amount.
[0164]
By the way, since a color copying machine scans four times to make one copy, the character determination result slightly differs for each scan. In particular, if non-black character determination is performed at the time of black image formation and black character determination is performed at times other than black image formation, this black character region becomes thin. Therefore, at bk, 8 × 8 block OR processing is performed, and then 3 When the AND processing of the × 3 block is performed and other than bk is formed, the OR processing of the 5 × 5 block is performed, and thereafter the AND processing of the 1 × 1 block is performed. Note that performing 1 × 1 AND processing is synonymous with performing no processing because the result is the same as before processing. The result of the expansion process is output to the decode 326d as a character edge signal.
[0165]
By performing the expansion process in this way, the separation result is different and the character area is not thinned. This expansion process may darken the middle part of the character, but there is no sense of incongruity because the character is lighter than the character edge and the density is saturated.
[0166]
FIG. 20 schematically shows an enlargement of the overlapping of the color colorants by color copying. FIG. 20D shows an ideal case where black characters are processed for all four colors. (E) of FIG. 20 shows a case where black characters are processed for all four colors, and only bk is not corrected, and correction other than bk is applied and lightened. FIG. 20 (f) shows a preferable case where only black characters are processed according to this embodiment, and FIG. 20 (g) shows that black characters are processed only for black characters according to this embodiment, and only bk is not corrected. , Bk is a preferable case where correction is applied.
[0167]
FIG. 20A shows an ideal case where the expansion amount is the same and black characters are processed. FIG. 20B shows the case where the expansion amount is the same and the print position is shifted after black character processing (out of white). FIG. 20C shows a case where the printing position is shifted by black character processing according to the present embodiment when the expansion amount of bk is large.
[0168]
-Character determination 326c-
The character determination 326c generates a signal indicating whether the character is in the character region using the results of the edge extraction 322, the white region extraction 323, the halftone dot extraction 324, the color determination 325, and the character determination 326a. The processing and signals used to generate a character signal are as follows.
[0169]
Character signal for character: The output signal representing the character edge / non-character edge of the character determination 326a is subjected to OR processing of 5 × 5 blocks. This output is called a character signal for character use;
White block black character signal A: The character signal for the character is active (character edge), the output of the white block correction 323g of the white area extraction 323 is white block correction data, and the result of the color determination 325 is inactive (achromatic: In the case of black pixel block), the white block black character signal A is made active. That is, “white block black character” is indicated. In this case (black characters surrounded by white background), the probability of being a character is very high;
High-density black region signal B: 3 × 3 block OR of white block extraction 323 is active (black), the result of color determination 325 is inactive (achromatic), and the result of halftone extraction 324 is When it is non-active (non-dot) and the character signal for characters is non-active (non-character edge), the high density black area signal B is activated. That is, “high density black region” is indicated. Among black characters, the density is high, so it is determined whether it is a character in combination with other conditions;
Black character signal C: When the character signal for character is active (character edge) and the result of the color determination 325 is non-active (achromatic), the black character signal C becomes active (black character). This active black character portion is likely to be an edge of the character, and there is a high possibility that there is a character around it.
[0170]
Here, the determination of candidates among characters will be described. Using the white block black character signal A, the high density black region signal B, and the black character signal C to express the candidate signal Q among characters, the following expression is obtained:
Q24 = (A21 & A22 & A23 & A24)
# ((Q13 # Q23 # Q14 # Q15) & (B24 # C24))
The positional relationship is shown in FIG. The upper number 2 of the two-digit number of the symbol indicates the current line y2, and 1 indicates the previous line y1. The lower digit indicates the pixel position x on the line. Briefly explaining the processing represented by the above formula, if the white block black character signal A exists continuously, that is, if all of A21 to A24 are active, it is assumed that the pixel of interest is a character or a candidate, The candidate confirmation process is started. That is, if there is a pixel (Q13, Q23, Q14, or Q15) that has been determined to be a candidate for a character in the vicinity of the high density black region signal B24 or the black character signal C24, the determination is made that the target pixel is also a candidate for a character. That is, when the white block character signal A (active) is continuously present, this condition is used as a trigger to start the determination of a character candidate.
[0171]
In the case of a black character surrounded by a white background (white block black character signal A is active), there is a very high probability that the character is a character, and white block black character signal A (active) is present almost continuously. Because. The black character signal A (active) is highly likely to be an edge of a character, and there is a high possibility that “character is” in the vicinity thereof, and therefore, as described above, a character character is a candidate (Q24: active). The result is output to the decode 326d as a character candidate. The decode 326d finally determines whether or not the character candidate is “character”.
[0172]
-Decode 326d-
Here, a character signal is generated from a character candidate (signal Q: active). If the character signal is not a character edge signal but a character or a candidate, it is determined that there is a character signal (character signal: active). The C / P signal finally output by the decode 326d is as shown in the following table:
C / P signal Character edge signal Character signal Signal area determination
0 None None Picture area
1 No Yes Characters in the area
2 − − −
3 Yes × Character edge area
There is no case of outputting C / P = 2.
[0173]
Next, FIG. 3 will be referred to again. The C / P signal and the B / C signal generated by the document recognition 320 are supplied to the RGB filter 330, the color correction 340, the magnification change 350, the interface 352, the UCR 360, the CMYBk filter 370, the CMYBkγ correction 380, and the gradation processing 390. Is given in cascade.
[0174]
The RGB filter 330 is a filter that performs MTF correction on RGB data, and includes a coefficient matrix corresponding to an N × N pixel matrix and logic that multiplies each coefficient by each image data to obtain a weighted average value. When the C / P signal represents 3 (character edge region), the coefficient matrix for sharpening processing is used, and when it represents 0 or 1 (character region or pattern region), it is used for smoothing processing. Using the coefficient matrix, a weighted average value is derived and output to the color correction 340. The color correction 340 converts R, G, B data into C, M, Y data by a primary masking process or the like. A scaling unit 350 performs enlargement / reduction in the main scanning direction x or equal magnification processing on the image data.
[0175]
The UCR 360 is for improving the color reproduction of the image data. The UCR (addition removal) process is performed on the common part of the C, M, and Y data input from the color correction 340 to generate Bk data. M, Y, Bk data is output. Here, when the C / P signal is other than 3 (character edge region) (when it is a character region or a picture region), skeleton black processing is performed. When the C / P signal is 3 (character edge region), full black processing is performed. Further, when the C / P signal is 3 (character edge region) and the B / C signal is H (achromatic region), the C, M, and Y data are erased. This is because black characters are expressed only by the black component.
[0176]
Further, the output image signal IMG of the UCR 360 is one color among C, M, Y, and Bk at a temporary point, and is a frame sequential one color output. That is, full-color (four-color) data is generated by reading the document four times. Further, in the case of black-and-white copying, since only one Bk image formation is required, one document reading is sufficient. If there is a mechanism for determining whether the original is a color document or a black and white document, the number of times of reading depends on the document. Therefore, it is not necessary for the operator to determine whether the document is a color document or a monochrome document according to the document. In this embodiment, the signal is referred to for determining whether the B / C signal is a color document or a monochrome document. When the B / C signal is H (achromatic region) on the entire surface of the document, the main controller 10 determines that the document is a monochrome document.
[0177]
The CMYBk filter 370 performs smoothing and sharpening processing using an N × N spatial filter according to the frequency characteristics of the color printer 400 and the C / P signal. The CMYBkγ correction 380 changes and processes the γ curve according to the frequency characteristics of the color printer 400 and the C / P signal. When the C / P signal is 0 (picture area) or 1 (character area), the γ curve is used to faithfully reproduce the image. When the C / P signal is 3 (character edge area), the γ curve is set up. Emphasize contrast.
[0178]
The gradation processing 390 performs quantization such as dither processing and error diffusion processing according to the gradation characteristics of the color printer 400 and the C / P signal. During Bk image formation, gradation-oriented processing is performed when the C / P signal is 0 (picture area), and resolution-oriented processing is performed otherwise. During image formation other than Bk, gradation-oriented processing is performed when the C / P signal is 0 (picture area) or 1 (character area), and resolution-oriented processing is performed otherwise. The image data subjected to the above processing is given from the video control 359 having a buffer memory to the color printer 400 in synchronization with the image data writing operation.
[0179]
The IPU 300 performs a smoothing process using the RGB filter 330 during the pattern processing (C / P signal = 0), performs a skeleton black process using the UCR 360, and emphasizes linearity (gradation) in the CMYBkγ correction 380. A curve is selected, and the CMYBk filter 370 and the gradation processing 390 perform processing that emphasizes gradation.
[0180]
On the other hand, for character processing (C / P signal = 3 and B / C signal = L), edge enhancement processing is performed by the RGB filter 330, full black processing is performed by the UCR 360, and contrast is emphasized by the CMYBkγ correction 380. And the CMYBk filter 370 and the gradation processing 390 perform processing focusing on resolution.
[0181]
In black character processing (C / P signal = 3 and B / C signal = H), C, M, and Y data are not printed during C, M, and Y image formation excluding Bk. This is to prevent the surroundings of black characters from being colored due to misalignment. In addition, the RGB filter 330 of the Bk data at this time may be made sharper by performing edge enhancement stronger than in the case of color characters.
[0182]
Further, during character processing (C / P signal = 1), smoothing processing is performed by the RGB filter 330, skeleton black processing is performed by the UCR 360, and linear (gradation) is emphasized by the CMYBkγ correction 380. And the CMYBk filter 370 performs processing that places importance on gradation.
[0183]
As described above, the IPU 300 performs four types of processing: a pattern, a character edge, a character on a pattern, and a character.
[Brief description of the drawings]
FIG. 1 is a longitudinal sectional view showing an outline of a mechanism of a color composite function copying apparatus according to an embodiment of the present invention.
2 is a block diagram showing a system configuration of an electric system of the copying apparatus shown in FIG.
3 is a block diagram showing a functional configuration of the IPU 300 shown in FIG. 2. FIG.
4 is a block diagram showing a functional configuration of document recognition 320 shown in FIG. 3. FIG.
FIG. 5 is a flowchart showing information processing for propagating white information to surrounding pixels in white determination 323C shown in FIG. 4;
6 is a block diagram showing a functional configuration of a color pixel determination 325f shown in FIG.
7 is a flowchart showing information processing for determining whether or not a document is color by the continuous count 325f23 shown in FIG.
FIG. 8 is an enlarged plan view showing a line pattern often used for halftone expression in a copying machine.
9 is an enlarged plan view of a 3 × 3 pixel matrix showing pixel distributions detected by the black pixel continuous detection 322b and the white pixel continuous detection 322c shown in FIG. 4;
10 is a diagram illustrating a 3 × 3 pixel matrix WBp / BBp referred to for white / black determination of a target pixel and RGB white extraction 323b shown in FIG. FIG. 6 is an enlarged plan view of a 5 × 5 pixel matrix RDPa, RDPb showing a pixel distribution detected by valley white pixel detection.
11 is an enlarged plan view of a 5 × 5 pixel matrix MPp, MCa to MCd showing pixels referred to by the RGB white extraction 323b shown in FIG. 4 for color background detection.
12 is a plan view showing a data writing position of a line memory used for propagation of white information, and PMPa to PMPd are 5 × 5 pixel matrix showing a pixel distribution detected by white pattern matching 323d shown in FIG. An enlarged plan view, BCP, is an enlarged plan view of a block matrix used for detecting whether the four corner directions are surrounded by white in the white correction 323g shown in FIG.
13 is an enlarged plan view of a black image showing black protrusion regions Bp1 to Bp4 that are definitely processed as black by the white correction 323g shown in FIG. 4; FIG.
14 is an enlarged plan view of a 5 × 5 pixel matrix MPa to MPf in which the first halftone peak detection 324a shown in FIG. 4 indicates pixels referred to halftone dot detection, and 4 × 4 pixels that count halftone dots. It is an enlarged plan view of a 2 × 2 block pattern AMP having a matrix as one block.
FIGS. 15A and 15B are graphs showing deviations between image data when a color image is read by a color scanner to obtain R, G, and B image data. FIG. 15A is a black region on a document, and FIG. Image data addressed to the black color material bk for recording and expressing it is schematically shown (c), and image data applied to the color materials c, m, and y.
16 is an enlarged view of a 5 × 5 pixel matrix showing a pixel distribution in which the target pixel is determined to be a color pixel in the pattern matching 325f6 shown in FIG.
17 is an enlarged view of a 5 × 5 pixel matrix showing a pixel distribution in which the target pixel is determined to be a color thin line pixel in the pattern matching 325f6 shown in FIG. 6;
18 is an enlarged view of a 5 × 5 pixel matrix showing a pixel distribution in which the target pixel is determined to be a white region pixel in the pattern matching 325f6 shown in FIG.
19 is a plan view specifically showing the value of the continuous number of color pixels by the continuous count 325f23 shown in FIG.
FIG. 20 is an enlarged vertical cross-sectional view schematically showing an enlargement of color color material overlapping by color copying.
FIG. 21 is a plan view showing a distribution of data to be referred to in determination 326c among the characters shown in FIG. 4;
[Explanation of symbols]
200: Scanner 300: Image processing apparatus
400: Printer

Claims (4)

In the image data, white data detecting means for a low concentration of the field containing the threshold for detecting a white pixel;
Color ground detection means for detecting color pixels in the image data;
If the multi-value white background information representing the degree of white of the pixel one line before is larger than the white background information of the pixel one pixel previous on the same line, the white background information of the pixel one line previous is used as the temporary white background information of the target pixel. Otherwise, the white background information of the pixel one pixel before is set as the temporary white background information of the target pixel, and if the target pixel is the color pixel or not the white pixel, the temporary white background information is updated to be small. If the target pixel is not the color pixel and the white pixel, the provisional white background information is greatly updated to be the white background information of the target pixel, and the target pixel is a white background in which all of the R, G, and B image data are smaller than the threshold value. If it is, the white determination means which uses the set maximum value of the white background information as the white background information of the target pixel ;
If the target pixel is not the color pixel but the white pixel and the white background information generated by the white determination means is greater than or equal to the threshold value, the target pixel is temporarily determined as a white pixel, and a series of white pixels centered on the target pixel Pattern matching means for determining whether there is a pattern by pattern matching;
A white region detecting means that, when there is a continuation of the white pixels, makes a block composed of a plurality of pixels including the target pixel and adjacent pixels a white block in which all pixels in the block are white pixels ; and
Non-character edge determination unit the pixel of interest to the white area detecting means determines that no white block Ru non-character edge and determine Teisu;
An image processing apparatus comprising: In the image data, white data detecting means for a low concentration of the field containing the threshold for detecting a white pixel;
Color ground detection means for detecting color pixels in the image data;
If the multi-value white background information representing the degree of white of the pixel one line before is larger than the white background information of the pixel one pixel previous on the same line, the white background information of the pixel one line previous is used as the temporary white background information of the target pixel. Otherwise, the white background information of the pixel one pixel before is set as the temporary white background information of the target pixel, and if the target pixel is the color pixel or not the white pixel, the temporary white background information is updated to be small. If the target pixel is not the color pixel and the white pixel, the provisional white background information is greatly updated to be the white background information of the target pixel, and the target pixel is a white background in which all of the R, G, and B image data are smaller than the threshold value. If it is, the white determination means which uses the set maximum value of the white background information as the white background information of the target pixel ;
If the target pixel is not the color pixel but the white pixel and the white background information generated by the white determination means is greater than or equal to the threshold value, the target pixel is temporarily determined as a white pixel, and a series of white pixels centered on the target pixel Pattern matching means for determining whether there is a pattern by pattern matching;
A white region detecting means that, when there is a continuation of the white pixels, makes a block composed of a plurality of pixels including the target pixel and adjacent pixels a white block in which all pixels in the block are white pixels ;
Halftone dot detecting means for detecting halftone dots in the image data; and
The white area detecting means pixel of interest and the dot detecting means does not determine that the white block is Ru non-character edge and determine Teisu the pixel of interest has been detected halftone non-character edge determining unit;
An image processing apparatus comprising: In the image data, white data detecting means for a low concentration of the field containing the threshold for detecting a white pixel;
Color ground detection means for detecting color pixels in the image data;
If the multi-value white background information representing the degree of white of the pixel one line before is larger than the white background information of the pixel one pixel previous on the same line, the white background information of the pixel one line previous is used as the temporary white background information of the target pixel. Otherwise, the white background information of the pixel one pixel before is set as the temporary white background information of the target pixel, and if the target pixel is the color pixel or not the white pixel, the temporary white background information is updated to be small. If the target pixel is not the color pixel and the white pixel, the provisional white background information is greatly updated to be the white background information of the target pixel, and the target pixel is a white background in which all of the R, G, and B image data are smaller than the threshold value. If it is, the white determination means which uses the set maximum value of the white background information as the white background information of the target pixel ;
If the target pixel is not the color pixel but the white pixel and the white background information generated by the white determination means is greater than or equal to the threshold value, the target pixel is temporarily determined as a white pixel, and a series of white pixels centered on the target pixel Pattern matching means for determining whether there is a pattern by pattern matching;
A white region detecting means that, when there is a continuation of the white pixels, makes a block composed of a plurality of pixels including the target pixel and adjacent pixels a white block in which all pixels in the block are white pixels ;
Edge detection means for detecting edges in the image data; and
The edge detecting means detects an edge, the white region detecting means Ru character edge and determine Teisu the pixel of interest is detected as an edge character edge determination means;
An image processing apparatus comprising: In the image data, white data detecting means for a low concentration of the field containing the threshold for detecting a white pixel;
Color ground detection means for detecting color pixels in the image data;
If the multi-value white background information representing the degree of white of the pixel one line before is larger than the white background information of the pixel one pixel previous on the same line, the white background information of the pixel one line previous is used as the temporary white background information of the target pixel. Otherwise, the white background information of the pixel one pixel before is set as the temporary white background information of the target pixel, and if the target pixel is the color pixel or not the white pixel, the temporary white background information is updated to be small. If the target pixel is not the color pixel and the white pixel, the provisional white background information is greatly updated to be the white background information of the target pixel, and the target pixel is a white background in which all of the R, G, and B image data are smaller than the threshold value. If it is, the white determination means which uses the set maximum value of the white background information as the white background information of the target pixel ;
If the target pixel is not the color pixel but the white pixel and the white background information generated by the white determination means is greater than or equal to the threshold value, the target pixel is temporarily determined as a white pixel, and a series of white pixels centered on the target pixel Pattern matching means for determining whether there is a pattern by pattern matching;
A white region detecting means that, when there is a continuation of the white pixels, makes a block composed of a plurality of pixels including the target pixel and adjacent pixels a white block in which all pixels in the block are white pixels ;
Halftone dot detecting means for detecting halftone dots in the image data;
Edge detection means for detecting edges in the image data; and
The edge detecting means detects an edge, the dot detecting means does not detect a dot, moreover the pixel of interest the white area detecting means detects an edge, the character edge and determine Teisu Ru character edge determination means;
An image processing apparatus comprising:

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