JP4695472B2 - Image processing apparatus, image forming apparatus, image processing method, program, and storage medium - Google Patents

Description

  The present invention relates to an image processing apparatus, an image forming apparatus, an image processing method, a program, and a storage medium used in a color digital copying machine, a distribution scanner, a color printer, a facsimile, and the like, and more specifically, image data read from a document. The present invention relates to an image processing apparatus, an image forming apparatus, an image processing method, a program, and a storage medium that determine whether a document is a color document or a monochrome document based on the above.

  In recent years, image forming apparatuses used in color digital copying machines, distribution scanners, color printers, facsimiles, and the like have been further required to have higher functions and higher quality. In these image forming apparatuses, image data is read by pre-scanning a document, and the document is a monochrome image including only achromatic information from the read image data, or a color document including chromatic color information. Some have a document type discriminating mechanism for automatically discriminating whether or not.

  The document type discrimination mechanism stores the read image data in the memory, detects the component ratio of C (cyan), M (magenta), and Y (yellow) for each pixel of the stored image data, and the detection result The type of the document is determined based on the above. If it is determined that the document is a monochrome document including only achromatic pixels, black and white copy is executed using only Bk (black) toner. If it is determined that the document is a document including chromatic pixels, C, M, Y And color copying with four color toners of Bk and Bk. Switching between modes is very important because the amount and cost of toner used differ greatly between the monochrome mode and the full color mode, and the output result of the image transferred to the transfer paper is also greatly different. In switching modes, as described above, a technique for automatically identifying whether a document is a chromatic document or an achromatic document and automatically switching the operation mode of the copier according to the identification result is known. (For example, refer to Patent Document 1).

  However, when detecting chromatic (color) pixels and achromatic (black) pixels in the read image data, mechanical sampling such as digital sampling by a 3-line CCD (Charge Coupled Device) sensor or ADF (Auto Document Feeder) is used. It is necessary to pay attention to image reading deviation caused by accuracy. An ADF is an automatic document feeder that eliminates the hassle of moving documents one by one on a contact glass by moving the document while fixing the optical system when reading a document by a copying machine or a facsimile machine. For example, in a general 3-line CCD sensor, the R, G, and B components of the original cannot be read at the same time, and reading deviation may occur due to sequential reading. Further, in an image forming apparatus that changes the read image by changing the scanning speed of reading, there may be a case where a reading shift occurs at the time of zooming with a high scanning speed. In such a case, an image having a color line of about one line at the edge of a black character is recognized as a read image. For example, although it is a black and white original, it is based on C, M, Y, and Bk. There is a problem that full-color image formation is performed and the amount of toner to be used increases.

  On the other hand, if the sensitivity of detecting a chromatic original is reduced to avoid erroneous determination that the achromatic original is a chromatic original due to such a shock jitter, a chromatic original with low saturation will be achromatic. There is a problem that it is determined that the document is a document and a chromatic document is imaged in the Bk version.

  In addition, in an image forming apparatus that determines whether a predetermined area of read image data is a character area, a pattern area, a chromatic area, or an achromatic area, it is particularly important to have an accuracy of determining a black character among characters. Become. This is because minute misregistration at the time of output by a plotter or the like significantly reduces the legibility of characters. For the output of black characters, an output process using Bk single color (hereinafter referred to as “black character processing”) is generally used based on a signal corresponding to luminance. Even when black character processing is not used, processing for improving the readability of black characters by increasing the black amount of the black character portion is used.

  Thus, it is extremely important to accurately determine the type of pixel in order to correct reading deviation or to appropriately perform output processing.

As a technique for determining the type of pixel, for example, after classifying a scanned original into a 3-bit signal consisting of eight C, M, Y, R, G, B, Bk, and W (white) in units of pixels. A technique is known in which the signal is allocated to three bit planes, values in a predetermined area of each bit plane are counted, and the pixel is determined to be an achromatic pixel when the count result meets a predetermined condition. (For example, see Patent Document 2).
JP 63-107274 A JP 2000-125139 A

  However, the image forming apparatus described in Patent Document 2 has a problem that it is difficult to appropriately determine a chromatic original having a fine color line and an achromatic original having a fine color line caused by reading deviation. is there.

  In view of the above-described problems, the present invention provides an image processing apparatus, an image forming apparatus, an image processing method, a program, and an image processing apparatus that can appropriately determine a chromatic original having a fine color line and an achromatic original having a fine color line caused by reading deviation. An object is to provide a storage medium.

  In order to achieve the above object, an image processing apparatus according to a first aspect of the present invention includes a pixel classification unit that classifies pixels of a read image read from a document into white pixels, black pixels, and non-monochrome pixels, and a predetermined number of non-continuous pixels. A plurality of identification patterns in which white pixels are arranged on both sides of the black and white pixels, and an area extracting means for extracting from the read image an area including the target pixel in the read image and having a number of vertical and horizontal pixels equal to or greater than the predetermined number; One of the identification patterns and a pattern matching unit that collates whether or not the arrangement of the white pixel and the non-monochrome pixel in the region extracted by the region extracting unit matches, and the matching result of the pattern matching unit And chromatic pixel determining means for determining whether or not the pixel of interest is a chromatic pixel.

  A second invention is an image processing apparatus according to the first invention, comprising first counting means for counting the number of the black pixels and the non-monochrome pixels in the region, and the chromatic pixel determination. The means determines whether or not the pixel of interest is a chromatic pixel based on the counting result of the first counting means and the matching result of the pattern matching means.

  A third invention is an image processing apparatus according to the first invention, wherein C (cyan), M (magenta), Y (yellow), R (red), G from each pixel of a read image read from a document. (Green), Bk (Black), W (White) representing a 3-bit signal, and further, bit plane forming means for forming three bit planes from these 3-bit signals, and values in each bit plane in the region A chromatic pixel determination unit, wherein the pixel of interest is a chromatic pixel based on a counting result of the second counting unit and a matching result of the pattern matching unit. It is characterized by determining whether or not there is.

  A fourth invention is an image processing apparatus according to the first to third inventions, wherein it is determined whether or not the read image is a chromatic image based on a determination result of the chromatic pixel determining means. It has a chromatic image determination means.

  A fifth invention is an image forming apparatus having the image processing apparatus according to the first to fourth inventions.

  An image processing method according to a sixth aspect of the present invention is an image processing method having a plurality of identification patterns in which white pixels are arranged on both sides of a predetermined number of non-monochrome pixels, a document reading step for reading a document, A pixel classification step for classifying pixels of the read image acquired in the document reading step into white pixels, black pixels, and non-monochrome pixels, and an area in which the number of vertical and horizontal pixels including the target pixel in the read image is equal to or greater than the predetermined number A region extracting step for extracting from the read image; and a pattern matching step for verifying whether one of the identification patterns matches the arrangement of the white pixel and the non-monochrome pixel in the region extracted by the region extracting means. And a chromatic pixel determining step for determining whether or not the target pixel is a chromatic pixel based on the matching result in the pattern matching step. And wherein the Rukoto.

  A seventh invention is a program for causing a computer to execute the image processing method according to the sixth invention.

  The eighth invention is a computer-readable storage medium storing the program according to the seventh invention.

  According to the present invention, there are provided an image processing apparatus, an image forming apparatus, an image processing method, a program, and a storage medium capable of appropriately determining a chromatic original having a fine color line and an achromatic original having a fine color line caused by reading deviation. It becomes possible.

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

  FIG. 1 is a block diagram illustrating a schematic configuration of a digital full-color image forming apparatus according to the first embodiment. 1 includes a scanner 1, a scanner correction unit 2, a compression processing unit 3, a controller 4, an HDD (Hard Disk Drive) 5, a NIC (Network Interface Card) 6, an expansion processing unit 7, and a printer correction unit. 8 and a plotter 9 and a general-purpose bus 10. A scanner 1 serving as a document reading unit reads image data color-separated into R, G, and B from a document 11 and converts the image data (analog signal) into digital data. The scanner correction unit 2 performs scanner γ correction processing for performing γ correction on the RGB image data (digital data) read by the scanner 1, image region separation processing for classifying the image region into characters, line drawings, patterns, or the like. Image processing such as filter processing for emphasizing the character portion or smoothing the pattern portion is performed. The compression processing unit 3 compresses the multivalued image data after scanner correction, and sends the data to the controller 4 via the general-purpose bus 10. The controller 4 has a semiconductor memory (not shown) and the like, and performs control such as temporarily storing the image data sent from the compression processing unit 3 in the memory. Further, the controller 4 executes a format process of the image data, and performs conversion into a general-purpose image format such as JPEG (Joint Photographic Experts Group), TIFF (Tag Image File Format), or BMP (Bit MaP). The HDD 5 stores image data temporarily stored in the semiconductor memory as needed. This enables electronic sorting to be performed without reading the document again even when the output is not completed normally, such as when paper is jammed at the time of printout, or to rearrange the image data of multiple documents. This is because the image data of the already read original is accumulated so that it can be re-output when necessary. Although the compression processing unit 3 compresses the image data, if the bandwidth of the general-purpose bus 10 is sufficiently wide and the capacity of the HDD 5 that stores the image data is sufficiently large, the image data is handled in an uncompressed state. Also good. Further, the controller 4 sends the image data in the HDD 5 to the decompression processing unit 7 via the general-purpose bus 10. The NIC 6 distributes the image data to the external PC terminal 12. The NIC 6 is used when the image forming apparatus 100 operates as a distribution scanner that distributes image data to the external PC terminal 12 via a network. The decompression processing unit 7 decompresses the compressed image data to the original multi-value image data and sends it to the printer correction unit 8. The printer correction unit 8 is a printer γ correction process, a gradation process, a light / dark characteristic correction process of the plotter 9, and an image data obtained by an error diffusion process and a dither process according to the gradation characteristic of the plotter 9 and the image area separation result. Quantize. The plotter 9 is a transfer paper printing unit using a laser beam writing process. The plotter 9 draws image data as a latent image on a photoconductor, and forms a copy image 13 on the transfer paper after image formation and transfer processing with toner.

  FIG. 2 is a diagram illustrating a configuration example of the scanner correction unit 2. The scanner correction unit 2 includes a scanner γ correction unit 20, an image area separation unit 21, a filter processing unit 22, a color correction unit 23, and a scaling processing unit 24. The scanner γ correction unit 20 converts the digital value of the RGB image data from the scanner 1 into a digital value proportional to the brightness. The image area separation unit 21 determines whether the image area (image area) of the document 11 is a character area, a halftone character area, a design area, or the like. The filter processing unit 21 performs a sharpening process or a smoothing process on the image data based on the image area separation result. The color correction unit 23 converts the image data color-separated into RGB into color image data including recording color information of C, M, Y, and Bk that are different color spaces. The scaling processing unit 24 enlarges or reduces the size of the input image data in the main scanning direction and outputs the image data. Further, the image area separation unit 21 outputs a binary signal yusai which is a determination result of whether or not the document 11 is a chromatic document. The yusai signal is transmitted to the controller 4 in FIG. 1. When the value of yusai is “1”, the controller 4 instructs the plotter 9 to perform image formation with four color plates of CMYBk, and the value of yusai Is “0”, the controller 4 instructs the plotter 9 to perform image formation using only the Bk version.

  FIG. 3 is a diagram illustrating a configuration example of the printer correction unit 8. The printer correction unit 8 includes a printer γ correction unit 30 and a gradation processing unit 31. The printer γ correction unit 30 performs γ correction corresponding to the frequency characteristics of the plotter 9 on the CMYBk image data that has passed through the expansion processing unit 7. The gradation processing unit 31 performs quantization such as dither processing and error diffusion processing. The printer correction unit 8 outputs signals C ″, M ″, Y ″, and Bk ″ obtained by correcting C, M, Y, and Bk to the plotter 9.

  FIG. 4 is a diagram illustrating a configuration example of the image area processing unit 21 which is an image processing apparatus. The image area processing unit 21 includes a filter unit 40, a color determination unit 41, a white region extraction unit 42, an edge extraction unit 43, a halftone separation unit 44, and an overall determination unit 45.

  The filter unit 40 corrects G image data generated by the scanner 1 mainly for character edge extraction. Here, since the image data read by the scanner 1 may not be clear depending on the performance of the lens or the like, an edge enhancement filter is applied. However, here, it is necessary to emphasize only the edges on the document and not to emphasize the line pattern for gradation expression that is widely used in copying machines. This is because if the line pattern is emphasized, a picture (a gradation expression area by the line pattern) is extracted as an edge, and may eventually be erroneously determined as a character edge. 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. In this case, the white block width is widened and the black block width is narrowed. As the density becomes higher, the white block width becomes narrower and the black block width becomes wider.

  In this embodiment, the pixel matrix of the filter unit 40 is a 7 × 5 pixel matrix having 7 pixels in the main scanning direction x and 5 pixels in the sub-scanning direction y (the mechanical document scanning direction of the scanner 1). 4, two sets of coefficient groups (coefficient matrix) addressing the respective weighting coefficients a1 to a7, b1 to b7, c1 to c7, d1 to d7, and e1 to e7 are addressed to each pixel. ) There are A and B. The next coefficient group A is a coefficient for filter processing that emphasizes the edge of the character while suppressing the enhancement of the 600 dpi line pattern A in FIG. 8, and the coefficient group B is the 400 dpi line pattern in FIG. This is a filter processing coefficient that emphasizes the edge of a character while suppressing the emphasis of B.

  The filter process is a process of adding the value of the pixel of interest by dividing the calculation result of the coefficient group A or B by 16. Thereby, the image data is emphasized. Coefficient group A is

And coefficient group B is

It is.

  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 filter unit 40 in FIG. “20” is the coefficient of the pixel in the center of the third row c1 to c7 of the coefficient matrix of the block of the filter unit 40, 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 unit 40 are given to the edge extraction unit 43 and the white area extraction unit 42. Here, the target pixel is a pixel to be processed at present, and is sequentially updated while moving in the x direction and the y direction.

  In the coefficient group A, a negative coefficient (small value coefficient) is assigned to a part corresponding to the line pitch of the 600 dpi line pattern A shown in FIG. 8, and 0 (a slightly large value coefficient) is present between them. 20 (very large coefficient) is assigned to the pixel of interest for edge enhancement. Thereby, when the image data (pixel of interest) is a black / white edge of the line pattern A region, the derived weighted average value (product sum value) is a character edge that is not the line pattern A. Compared to a very low value.

  In the coefficient group B, a negative coefficient (small value coefficient) is assigned to a portion corresponding to the line pitch of the 400 dpi line pattern B shown in FIG. 8, and 0 (a slightly large value coefficient) is present between them. 20 (very large coefficient) is assigned to the pixel of interest for edge enhancement. As a result, when the image data (pixel of interest) is the black / white edge of the line pattern B region, the derived weighted average value (product sum value) is the character edge that is not the line pattern B. Compared to a very low value.

  The filter unit 40 performs the filtering process 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 is 400 dpi in FIG. If not, filter processing by coefficient group A is performed. Condition 1 [a condition for determining a thin portion of the 400 dpi line pattern B (white section in FIG. 8)] is (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])) and condition 2 [400 dpi The condition for determining the dark part of the system line pattern B (black section in FIG. 8) is (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 image data of a pixel at a position of x = i, y = j on a 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 unit 40 in FIG. 4 is addressed. “&” Means “logical product: AND”, and “ABS” means an absolute value operator. The target pixel is D [4] [3].

  When the condition 1 or 2 is satisfied, the pixel of interest at that time is assumed to be in the 400 dpi line pattern B region at the time of 600 dpi reading shown in FIG. I do. If neither of the conditions 1 and 2 is satisfied, the character edge emphasis filter process is performed using the coefficient group A that avoids emphasizing the 600 dpi line pattern A at the time of 600 dpi reading shown in FIG. That is, the image period (pitch) is detected so that the image pattern of a specific period is not emphasized. Thereby, it is possible to emphasize the edge of the character without enhancing 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 density can be applied.

  The edge extraction unit 43 is means for detecting a character edge, and includes a ternarization unit 431, a black pixel continuous detection unit 432, a white pixel continuous detection unit 433, a neighboring pixel detection unit 434, and an isolated point removal unit 435. . In the character edge portion, there are many high-level density pixels and low-level density pixels (hereinafter referred to as “black pixels” and “white pixels”, respectively), and these black pixels and white pixels are continuous. The edge extraction unit 43 detects a character edge based on the continuity of each of such black pixels and white pixels.

  The ternarization unit 431 ternarizes the G image data (input data of the edge extraction unit 43) that has been subjected to the filter processing for character edge enhancement by the filter unit 40 using the two types 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. The ternary unit 431 converts the input data into ternary data representing white pixels when input data <TH1, and the input data into ternary data representing halftone pixels when TH1 ≦ input data <TH2. When TH2 ≦ input data, the input data is converted into ternary data representing black pixels.

  The black pixel continuation detection unit 432 and the white pixel continuation detection unit 433 detect a portion where the black pixels are continuous and a portion where the white pixels are continuous based on the ternary data by pattern matching. 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. These patterns are stored in a storage device such as the HDD 5 of the image forming apparatus 100, a RAM (Random Access Memory) (not shown), an NVRAM (Non-Volatile RAM), a ROM (Read Only Memory), or the like. The same applies to other patterns described later. 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 of the circles are black pixels, halftone pixels, white pixels It shows that it is what does not ask. The pixel at the center of the 3 × 3 pixel matrix is the target 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. 9, the black pixel continuous detection unit 432 represents the target pixel at that time as “black continuous pixels”. Data is given to the pixel of interest. Similarly, when the white pixel continuous detection unit 433 matches 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. .

  For the detection results of the black pixel continuous detection unit 432 and the white pixel continuous detection unit 433, the neighboring pixel detection unit 434 determines whether there are black continuous pixels or white continuous pixels in the vicinity of the target pixel in the neighboring pixel detection unit 434. By examining, 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 at least one continuous black pixel and one continuous white pixel, the block is determined to be an edge region. If not, the block is determined as a non-edge region.

  The isolated point removing unit 435 corrects the isolated edge into a non-edge region. This is because character edges exist continuously. Then, the isolated point removal unit 435 outputs an edge signal “1” (edge region) to the pixel determined as the edge region, and “0” (non-edge region) to the pixel determined as the non-edge region. The edge signal is output.

  As shown in FIG. 21, the white area extraction unit 42 includes a binarization unit 4201, an RGB white extraction unit 4202, a white determination unit 4203, a white pattern matching unit 4204, a white pattern correction unit 4205, a white expansion unit 4206, and a white contraction unit. 4207, a white correction unit 4208, a gray pattern matching unit 4209, a gray expansion unit 4210, and a determination unit 4211. 4 corresponds to the white area extraction unit 42 in FIG.

  The binarization unit 4201 binarizes the edge enhancement output of the image density data (G image data) of the filter unit 40 with a threshold value thwsb. The edge emphasis output is 256 gradations from 0 to 255 in this embodiment, 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 it is smaller, the binarization unit 4201 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.

  The RGB white extraction unit 4202 includes a gray pixel detection unit 4212, a color background detection unit 4213, and an RGB white background detection unit 4214. The RGB white extraction unit 4202 determines whether the image data is a white area or a gray area (medium density area).

  The RGB white background detection unit 4213 activates the white background separation operation by detecting a white background region from the R, G, and 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. The white area is determined and the white background determination signal is set to active “1”. This is to detect whether or not there is a white pixel area having a certain extent. 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, threshold thwss <thwsb, and thwss is 40, for example. Yes, if all of the R, G, B image data is smaller 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.

  The color background detection unit 4213 detects the color background by the following pattern matching A to D in order not to determine a light color as a white background.

  A. First, if the sign of each pixel of the 5 × 5 pixel matrix centered on the target pixel is shown in the pattern MPp in FIG. 11, the RGB of the center pixel c3 (the X mark pixels of MCa to MCd) serving as the target pixel When the 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 when the difference is less than the threshold value thc “0” (monochrome pixel).

  B. When the R, G, and 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 are 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 20, for example.

  C. When 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 are all equal to or less than the threshold thwc, the other side white determination signal c is “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. 11, when aAND (bXNORc) = “1” is satisfied, that is, a is “1” (the target pixel is a color pixel), and b and c match (attention) When both pixels are white pixels or both sides are non-white pixels), the color gamut determination signal d addressed to the pixel of interest is set to “1” (color gamut).

  The above-described pattern matching A to D is performed in order to prevent a black character from being recognized as a color even when it is slightly colored due to the RGB reading position shift. At a colored position around the black character, bXNORc (exclusive OR of b and c) is “0” (one pixel on both sides of the target pixel is a white pixel and the other is a non-white pixel). The ground determination signal d is “0” (non-colored ground). 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 is “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, even if it is originally white, it is not read as completely white. When the RGB difference is small, it is not determined that the pixel is a color pixel. Therefore, the threshold thwc is set more strictly than the white background for which the density is to be viewed (for example, thwsc = 20 for thwss = 40 and thwsb = 50). Through the processing of D to D, it is strictly checked whether or not the background is a white background so that a light color pixel can be accurately detected as a color background.

  It should be noted that valley white pixel detection may be performed when detecting the color background. The valley white pixel detection detects valley white pixels in a small white area that cannot be detected by the RGB white background detection unit 4214 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]). 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 derived. Also, pixels with white circles in the 5 × 5 pixel matrix distribution RDPa shown in FIG. 10 according to maxy = max (G [3] [2], G [3] [3], G [3] [4]). The highest density maxy in the group is derived. Next, mint = min (G [2] [1], G [3] [1], G [4] [1], G [2] [5], G [3] [5], G [4 ] [5]), the lowest density mint in the pixel group with the black circles in the other 5 × 5 pixel matrix distribution RDPb shown in FIG. 10 is derived. Then, pixels with white circles in the 5 × 5 pixel matrix distribution RDPb shown in FIG. 10 according to maxt = max (G [2] [3], G [3] [3], G [4] [3]). The highest density maxt in the group is derived. Here, min () is a function for detecting the minimum value, and max () is a function for detecting the maximum value. Next, according to OUT = ((miny-maxy)> 0) # ((mint-maxt)> 0), the larger value of (miny-maxy) and (mint-maxt) is a positive value. Is detected as a valley detection value OUT, and when the value of OUT is equal to or greater than a certain threshold, the pixel of interest (the center pixel of RDPa or RDPb) is detected as a valley white pixel. In this way, the valley state of the image is detected, and the RGB white background detection unit 4214 compensates for the difficulty of detection. In addition, # means a logical sum (OR: or).

  The white determination unit 4203 updates the state variables MS and SS [I] used for white determination. The contents are shown in the flowchart of 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 shown in the flowchart 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 representing it, the stronger the white. At the start of the copying operation, the state variables MS and SS [I] are both initialized to 0.

  In the processing of FIG. 5, first, the state variable of the target pixel that is the processing target one line before, 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 S1). If the white background information SS [I] one line before is larger, it is set as the temporary white background information MS of the target pixel (step S2). 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 is selected from the white background information of the peripheral pixels.

  When a white area, that is, a white background is detected by the RGB white background detection unit 4214 after the copying operation is started (white background determination signal = “1” output from the RGB white background detection unit 4214), the white background of the pixel one line before the target pixel The information SS [I] is updated to 15 (steps S3 and S4), and the value of the white background information MS of the target pixel is also set to 15 (step S5). 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) of the line memory LMP shown in FIG. Information SS [I] is written into the main scanning position (F) of the target pixel in the line memory for the previous one line of the line memory LMP shown in FIG. 12 (steps S3, 4, 5). Next, the white background information SS [I] addressed to the previous pixel is propagated to the previous pixel as follows (steps S14 to S17). [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).

  If SS [I-1] <SS [I] -1, SS [I-1] = SS [I] -1 is set in the line memory (steps S14 and S15). That is, in the line one line before the target pixel, in the main scanning direction, the position (F) of the target pixel is higher than the white background information SS [I-1] one pixel before (E) from the target pixel position (F). When the value “SS [I] −1” obtained by subtracting 1 from the white background information SS [I] is larger (the white degree 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 the pixel (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.

  Next, when SS [I-2] <SS [I] -2, SS [I-2] = SS [I] -2 is set in the line memory (steps S16, 17-14, 15). Next, when SS [I-3] <SS [I] -3, SS [I-3] = SS [I] -3 is set in the line memory (steps S16, 17-14, 15).

  In the same manner, finally, if SS [I-15] <SS [I] -15, SS [I-15] = SS [I] -15 is set in the line memory (steps S16, 17-14). 15). The lower limit value MIN of the value of the white background information SS [I] is 0, and is 0 when it is less than 0. The same applies to step S13 described later.

  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 the white background information MS of the target pixel, and then the position of one pixel in the main scanning direction x. 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 by 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, when the pixel of the previous line is detected by the RGB white background detection unit 4214 to be a white background (white area), the white background information is 15 and is the highest value, so rewriting is not performed.

  When the pixel of interest is updated and becomes a non-white background (white background determination signal = “0” output from the RGB white background detection unit 4214), the process proceeds from step S3 to step S6 and subsequent steps, and the pixel of interest changes to the color background [color background]. Instead of the color gamut determination signal d = “1” output from the detection unit 4213 (non-color gamut), binarized white [binary white determination signal output from the binarization unit 4201 = “1” In addition, 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), 1 is added to the white background information MS addressed to the pixel of interest ( Steps S6 to 10). That is, the white level is updated by 1 to a strong value. The maximum value of the white background information MS is set to 15, and when it exceeds 15, it is set to 15 (steps S9 and S10). Even when the route has been advanced, the above-described steps S5 and S14 to S17 are executed. That is, white propagation processing is performed.

  When the pixel of interest is a non-color background and binarized white, but the white background information MS is less than thw1 (for example, 7), thw2 (for example, 1) or more, and is a valley white pixel, the state variable MS is set to The value is held as it is (steps S8, 11, 12). Even when the route has been advanced, the above-described steps S5 and S14 to S17 are executed. That is, white propagation processing is performed.

  If none of the above conditions is met, that is, if the target pixel is a color background or non-binary white, 1 is subtracted from the white background information MS of the target pixel (step S13). That is, it is updated to white background information whose white level is weak by one. The minimum value of the white background information MS is 0, and is 0 when it is less than 0. Even when the route has been advanced, the above-described steps S5 and S14 to S17 are executed. That is, white propagation processing is performed.

  As described above, by generating the white background information MS, it is possible to propagate the white information 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 in steps S3 to S4 in FIG. 5 based on the RGB white background determination signal representing a white background when the color data (all of the R, G, and B image data) is smaller than the threshold thwss = 40. -Including generation of white background information MS corresponding to the colors of S5-S14 to S17, and when the edge enhancement output (output of the filter unit 321) of density data (G image data) is smaller than the threshold thwsb = 50, This includes the generation of white background information MS corresponding to the density of the system in steps S7 to S13-S5-S14 to S17 in FIG. 5 based on the white background determination and the binarized white determination signal.

  The white determination unit 4203 first generates a white background determination signal “1” until the RGB white background detection unit 4214 of the RGB white extraction unit 4202 detects a white region, that is, a color corresponding to this is generated. The operation (execution of step S4) is not performed until the generation of the corresponding white background information MS (steps S3-S4-S5-S14 to S17) is started. This is to prevent an area that cannot be determined to be a white area from being erroneously determined to be a white pixel (white block) in the white pattern matching unit 4204 described later.

  When an edge emphasis filter is applied to a light color character, the data around the character becomes a lower value (white) than the original image data (color background). Therefore, when white pattern matching is performed on the data after the edge enhancement processing of the filter unit 40, that is, when white region determination is performed based only on generation of density-corresponding white background information MS (steps S7 to S13-S5-S14 to S17). It is easy to erroneously determine that the character ground around the color is white. Therefore, a white pixel (white block), which will be described later, is determined in an area that can be determined to be a white area by generating the white background information MS corresponding to the color (steps S3-S4-S5-S14 to S17). If the white background information MS is set to the highest value so that the white pattern matching is applied and the white background is not white in step S3, the white background condition is checked in detail in step S6 and subsequent steps to determine whether to apply the white pattern matching. By adjusting the white background information MS that is one parameter, it is possible to prevent the G image data after the edge enhancement processing of the filter unit 40 from being erroneously determined as a white pixel (white block) in the white pattern matching unit 4204 described later. .

  For example, when the possibility of a color pixel is high, the white background information MS is lowered (step S13), and when there is a suspicion of a color pixel, the white background information MS is held (no change) (steps S11 to S13). Pattern matching prevents erroneous determination that the pixel is a white pixel (white block), and prevents data around the character from having a lower level (white) than the original image data (color background).

  When the character is dense, the white background information MS is updated and propagated by the above-described processing (steps S3 to S5, S6 to S10, and S14 to S17), so that the possibility that the dense character region is erroneously determined as a pattern is reduced. . In addition, white characters may not be detected by the RGB white background detection unit 4214 in characters such as complicated characters (for example, “call”). In this case, white is detected by valley white pixel detection. Since the information MS is held by the route in which the YES output of step S12 goes straight to step S5 and remains in a white background tendency, the possibility that a complicated character is erroneously determined as a design is reduced.

  Further, as described above, when the target pixel is a color pixel surrounded by a white background, the color background determination signal d that is the output of the color background detection unit 4213 is “1” (color background), and the line is Even in a complicated area, a thin color pixel can be detected as a color background, and a threshold value thwc for determining whether or not the periphery of the target pixel is white is set low (thwc = 20). Since it is possible to detect light color pixels as a color background by strictly checking whether or not the surrounding is a white background, it is possible to further reduce the possibility that a complicated character is erroneously determined as a picture.

  As described above, since a light color pixel can be detected more precisely as a color background, when the color background is detected, the process proceeds from step S6 to step S13 in FIG. In addition to the threshold thwss (eg, 40) used when generating the white background determination signal referred to in step S3, the binarized white determination signal referred to in step S7 is generated. If the threshold value thwsb (for example, 50) is set to a large value and the color background is not determined (step S6: NO), the binarization unit 4201 increases the probability of considering it as white, and step S7 in FIG. From step S10, the state variable MS is increased to increase the possibility of determining a white area.

  That is, the RGB white background detection unit 4214 performs a strict white determination with a low probability of determining white with the threshold thwss = 40, and when the white background is determined there, the state variable MS is increased by the processing from step S3 to S4 in FIG. This increases the possibility of judging the character background as white. If the above-mentioned strict white determination does not determine a white background, conversely, a strict color determination with high reliability is performed to detect a light color pixel that may be a color background as a color background. If the result of the unit 4213 is referred to and it is not determined to be a color background, a sweet white determination with a threshold thwsb = 50 having a high probability of determining white is performed again, that is, refer to the binarization unit 4201 If the determination is white, the state variable MS is increased to increase the possibility that the character background is determined to be white (steps S7 to S10). Since there is this processing (steps S6 to S10), when the background density unevenness is lighter than the color background and the detected light color pixel, for example, when there is unevenness in the background of the document such as show-through, the fine background unevenness of the document As a result, it is possible to prevent the state variable MS from significantly changing in binary, and to prevent the next white pattern matching unit 4204 from determining whether or not the pixel is a white pixel 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.

  The white pattern matching unit 4204 determines whether or not the background is white based on whether or not there is a continuous white pixel in a 5 × 5 pixel unit block centered on the target pixel. Therefore, regarding 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. The conditional expression is (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) It is. Here, the target pixel for checking whether or not this conditional expression is satisfied has been subjected to the white propagation processing in steps S5 and S14 to S17 in FIG. “White background information MS” is the white background information MS [I] of the pixel of interest for which the above-described check after the white propagation processing is performed. However, MS [I] is the white background information after the white propagation processing, and I is the position in the main scanning direction x of the target pixel to be checked, and the white determination unit 4203 described above has the state variable. This is different from the position in the main scanning direction x of the target pixel for calculating MS.

  In the conditional expression, “non-color pixel” indicates that the color background determination signal d output from the color background detection unit 4213 is “0”, and “binary white” indicates the binary value of the binarization unit 4201. The whitening determination signal is “1” (binarized white), and “valley white pixel” means that the detection result of valley white pixel detection is a valley white pixel, and # is logic. It means sum (or: or). The white pattern matching is to check whether the output (whether or not it is a white pixel) determined by the 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.

  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, it is determined that the target pixel is a white pattern pixel.

  The gray pixel detection unit 4212 performs hue division of R, G, B, Y, M, C, and Bk, and detects a pixel having a low density for each hue. Hue division is the same as color determination described later. Here, if the filtered G data is compared with thgr and satisfies either the larger than the G data or the color pixel in the RGB white extraction color pixel detection, the following (1) to (6) are satisfied. ) And if any of the following conditions (7) to (13) is satisfied, the pixel is determined as a gray pixel. Here, the threshold is changed for each color because the maximum density of each ink is different.

The conditions are (1) RY hue region boundary (ry): R-2 * G + B> 0,
(2) Y-G 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,
(7) Y pixel determination (gry): (color pixel) & (ry == 1) & (yg == 0) & (maximum RGB value <thmaxy),
(8) G pixel determination (grg): (color pixel) & (yg == 1) & (gc == 0) & (maximum RGB value <thmaxg),
(9) C pixel determination (grc): (color pixel) & (gc == 1) & (cb == 0) & (maximum RGB value <thmaxc),
(10) B pixel determination (grb): (color pixel) & (cb == 1) & (bm == 0) & (maximum RGB value <thmaxb),
(11) M pixel determination (grm): (color pixel) & (bm == 1) & (mr == 0) & RGB maximum value <thmaxm),
(12) R pixel determination (grr): (color pixel) & (mr == 1) & (ry == 0) & (maximum RGB value <thmaxr), and
(13) Determination when not a color pixel (grbk): (RGB maximum value <thmaxbk). Note that “==” is a notation representing “equal” in the C language.

  This processing is performed by the gray pixel detection unit 4212 in FIG. As described above, the RGB white extraction unit 4202 includes the gray pixel detection unit 4212, the color pixel detection unit 4213, and the RGB white background detection unit 4214, and R, G, and B image data are input to these units. The output of the gray pixel detection unit 4212 is input to the gray pattern matching unit 4209, and the pattern matching result of the gray pattern matching unit 4209 is input to the gray expansion unit 4210. After the expansion processing is performed, the output is determined by the determination unit. 4211 is input. The white determination unit 4203 receives the outputs of the color pixel detection unit 4213, the RGB white background detection unit 4214, and the binarization unit 4201, and the determination result of the white determination unit 4203 is input to the white pattern matching unit 4204. The pattern matching result is input to the white pattern correction unit 4205 and the white correction unit 4208. The correction result of the white pattern correction unit 4205 is further processed by the white expansion unit 4206 and the white contraction unit 4207, and then input to the determination unit 4211. The processing result of the white correction unit 4208 is input to the determination unit 4211 as it is. . It should be noted that the isolated points can be removed by performing the shrinking process before the gray expansion part 4210 performs the expansion process. The white pattern matching unit 4204, the white pattern correction unit 4205, the white expansion unit 4206, the white contraction unit 4207, and the white correction unit 4208 are configured to detect white and a non-white boundary region. The output indicates the line width, the output of the white contraction part 4207 indicates a white area, and the output of the gray expansion part 4210 indicates medium density. Therefore, the determination unit 4211 makes a determination by assigning priorities to these three outputs, and outputs the determination result to the subsequent stage. In this case, priority 1 is line width information from the white correction unit 4208, priority 2 is medium density information from the gray expansion unit 4210, and priority 3 is white area information from the white contraction unit 4207. is there.

  The gray pattern matching unit 4209 performs pattern matching with the pattern shown in FIG. Here, it is assumed that the black circle is a gray pixel and the white circle is darker than the gray pixel. Since the copy document has a thin line pattern of 200 lines and a line pattern of 300 lines, such a pattern is adopted so that the copy document is also detected in gray.

  Those that match the pattern of FIG. 22 are gray pixels. 22A shows a pattern for 200 lines, and FIG. 22B shows a pattern for 300 lines.

  The white pattern correction unit 4205 deactivates active pixels that are isolated (white pixels of 1 × 1, 1 × 2, 2 × 1, 2 × 2, 1 × 3, and 3 × 1) by white pixel pattern matching. To do. This removes isolated pixels.

  The white expansion unit 4206 performs 7 × 41 OR on the white pixel pattern matching correction result.

  The white contraction unit 4207 performs 1 × 33 AND on the white expansion result in the white expansion unit 4206. By performing white expansion and white contraction, inactive pixels existing in a small area with respect to the correction result in the white pattern matching unit 4204 are removed. The determination result includes a non-white background side boundary region with respect to the white background and the boundary portion. In other words, the area is larger than the white background.

  The white correction unit 4208 has at least one white candidate block in each of the 6 × 4 pixel regions at the four corners in the 15 × 11 pixel centered on the target pixel marked with “X” in the block pattern BCP of FIG. Sometimes white block correction data is given to the target block. As a result, a region surrounded by a white background is set as a white region.

  The gray expansion unit 4210 performs 11 × 11 OR processing on the result of gray pattern matching. This makes the area slightly larger than the gray area.

  The determination unit 4211 sets a white background when the result of the white correction unit 4208 is active, or when the result of the white contraction unit 4207 is active and the result of the gray expansion unit 4210 is inactive. Expressed as an expression, (white correction result) # ((white shrinkage result) &! (Gray expansion result)). Here, the (white correction result) reliably determines that the area surrounded by the white background is a white area, and the result of ((white shrinkage result) &! (Gray dilation result)) A white area is determined and a non-white area is defined as a low density area. “!” Represents negative.

  In FIG. 13, in the black protrusions surrounded by the circles Bp1 to Bp4, one or more white candidate blocks exist in each of the 6 × 4 pixel regions at the four corners in 15 × 11 pixels centering on the above-described target block. At this time, the white block is replaced by white block correction which gives white block correction data to the target block. Making a black region surrounded by a white background like the black protrusions surrounded by the circles Bp1 to Bp4 as a white region lowers the possibility of determining it as a picture portion. In the overall determination unit 45 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 circles Bp1 to Bp4, is reduced. . Furthermore, as a result of white shrinkage, the boundary between black and white is determined as a white area (character area) based on the result of gray expansion, so a dark character edge is determined as a white background regardless of the thickness of the character. It can be determined as an edge. A character edge is not determined in a portion having a low density.

  As described above, in the white area extraction unit 42, the white determination unit 4203 performs the white background determination signal of the RGB white extraction unit 4202, the color background determination signal d and the valley white pixel determination signal, and the binarized white of the binarization unit 4201. White background information MS, which is a state variable representing the degree of white corresponding to the determination signal, is generated. A white pattern matching unit 4204 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, and includes the pixel including the pixel of interest. 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 unit (not shown) and the black pattern matching unit (not shown), the white correction unit 4208 determines that the target pixel is the boundary between the black background and the white background (white region: Character area). The white region extraction unit 42 has the circuit configuration of FIG. 21 in the case of gray pixel determination, but the black and white determination is processed in the circuit configuration of FIG.

  The white background determination signal of the RGB white extraction unit 4202 is “1” (white background) when all of the R, G, and B image data of the target pixel are smaller than the threshold thwss = 40. Increasing this threshold thwss increases the probability of determining a large value of white background information MS, and increases the probability of extracting a “white area” (boundary between black background and white background: character area) (ie, extracting a picture area). Probability decreases). The reverse occurs when the threshold value thwss is decreased.

  The binarized white determination signal of the binarization unit 4201 is “1” (binarized white) if the edge enhancement output of the G image data of the filter unit 321 is smaller than the threshold value thwsb = 50. When this threshold value thwsb is increased, the probability of determining a large value of the white background information MS increases, and the probability of extracting the “white region” increases (that is, the probability of extracting the pattern region decreases). If the threshold value thwsb is reduced, the opposite is true.

  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 step. Therefore, if the threshold values thwss and thwsb are reduced, the priority is given to the picture (picture). High image processing is performed.

  By the way, when the color background determination signal d of the RGB white extraction unit 4202 is “1” (color background), the white background information MS is lowered, and the probability of extracting the “white area” becomes low (that is, the probability of extracting the pattern area). Becomes higher). B. Pattern matching for generating a color gamut determination signal d by color gamut detection And C.I. When the threshold thwc (for example, 20) used in the above is reduced, the probability of detecting neighboring pixels (Δ and □ in FIG. 11) as color pixels at the same time (probability that the exclusive OR of b and c is “1”) is increased. The probability of obtaining the color background determination signal d = “1” (color background) increases and the probability of extracting the “white region” decreases (that is, the probability of extracting the pattern region increases).

  Therefore, in the present embodiment, “character” in the parameter adjustment to be adjusted by operating the key image (parameter designation key and up / down key) on the menu screen displayed on the liquid crystal display and the input mode menu display by key input. The thresholds thwss, thwsb, and thwc are adjusted as follows by adjusting “/ photo level”.

That is, the standard value (default) of the parameter “character / photo level” that is adjusted and set by the operator on the operation board is “3”, and this default value is the character / photo level and the threshold values thwss, thwsb, and thwc. It is written in a ROM (not shown) together with a conversion table representing the relationship, an IPU (Instruction Processing Unit) (not shown) is powered on, and a CPU (not shown) initializes the IPU. The CPU reads the default value of the character / photo level from the ROM, reads the corresponding threshold values thwss, thwsb, and thwc from the conversion table, writes them to the registers addressed to the respective threshold values in the RAM, and the white area extraction unit 42 Used in the above-described processing. After that, when the character / photo level is adjusted by input from the operation board, and the adjusted value A is given from the main controller to the CPU, the CPU sets the parameters thwss, thwsb and thwc corresponding to the adjusted value A. Each value is read from the conversion table in the ROM and written to the register addressed to the RAM parameter.

  When the threshold value is set to the standard value thwss = 40, thwsb = 50, thwsc = 20, the operator increases the value of “character / photo level” by “i” (for example, 1) to “Up” using the operation board. , Thresholds thwss, thwsb, and thwc are set to values that are changed in the character priority direction by 2 × i (2). On the contrary, when the value of “character / photo level” is decreased by “i” (for example, 1) and “down”, the threshold values thwss, thwsb, and thwc are set to values that are changed to the photo priority direction by 2 × i (2). It is done.

  As shown in FIG. 23, the halftone dot extraction unit 44 includes a first halftone peak detection unit 4401, a second halftone peak detection unit 4402, a third halftone peak detection unit 4403, a first halftone dot region detection unit 4404, 3 halftone dot area detector 4405 and temporary storage means (temporary memory) 4406. G image data is input to the first halftone peak detector 4401 and the third halftone peak detector 4403, and B image data is input to the second halftone peak detector 4402. The first halftone dot region detector 4404 receives the detection results of the first halftone dot peak detector 4401 and the second halftone dot peak detector 4402, and the second halftone dot region detector 4405 receives the third halftone dot region detector 4405. The detection result of the peak detection unit 4403 is input. The temporary memory 4406 temporarily stores the detection results of the first and second halftone dot area detection units 4404 and 4405. Note that the halftone dot extraction unit 44 in FIG. 4 corresponds to the halftone dot extraction unit 44 in FIG.

  The first halftone dot detection unit 4401 uses G image data to generate pixels that form part of halftone dots (hereinafter, “halftone peak pixels” from pixel density information in a two-dimensional local region having a predetermined size. "). When the following two conditions are simultaneously satisfied for the local region, the central pixel of the region is detected as a halftone dot pixel.

  Condition 1 is that the density level of the central pixel is maximum (peak peak) or minimum (valley peak) in the local region. Condition 2 is that the absolute value of the difference between the average density level of the pixel pair and the density level of the central pixel is equal to or greater than the threshold value Th for all pixel pairs that are in point symmetry with respect to the central pixel.

  With reference to FIG. 14, the detection process of the 1st halftone peak detection part 4401 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 central pixel c3 that is the target pixel is the maximum or minimum compared to the densities L1 to L8 of the surrounding pixels. Abs (2Lc-L1-L8) ≧ Lth and abs (2Lc-L2-L7) ≧ Lth and abs (2Lc-L3-L6) ≧ Lth and abs (2Lc-L4-L5) ) ≧ Lth, the center pixel (Lc) of the mask is detected as a halftone dot pixel. The abs function means taking an absolute value. Lth is a threshold value (fixed value).

  Specifically, the surrounding pixels are pixels to which the surrounding pixel distribution pattern MPa or MPb quadrangle shown in FIG. 14 is added. When either halftone dot pixel detection described above based on the surrounding pixel distribution patterns MPa and MPb detects a halftone peak pixel, detection that represents a halftone dot pixel at the current pixel of interest (center pixel c3) Give a signal. The reason for using the two patterns is to deal with a wide range of halftone dot lines.

  The pattern MPa is defined as L1 = b2, L2 = b3, L3 = b4, L4 = c2, L5 = c4, L6 = d2, L7 = d3, and L8 = d4. 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. The pattern MPb is defined as L1 = b2, L2 = a3, L3 = b4, L4 = c1, L5 = c5, L6 = d2, L7 = e3, and L8 = d4.

  In the case of copying, since enlargement / reduction in the sub-scanning direction y is performed at high and low document scanning speeds of the scanner 1, the scanner 1 gives image data that has been enlarged / reduced 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 aforementioned patterns MPa and MPb. When enlarging, the 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 “surrounding pixels”.

  The second halftone peak detector 4402 detects a halftone peak using the B data, and has the same function as the first halftone peak detector 4401. Since the first halftone dot peak detection unit 4401 uses G image data, it reacts to most colors, but does not react to Y, so the second halftone peak detection unit 4402 uses B image data. Thus, the object is to detect a Y dot peak.

  The third halftone dot region detection unit 4403 has a predetermined size of peak and valley halftone dot pixels detected by either the first halftone dot peak pixel detection unit 4401 or the second halftone peak pixel detection unit 4402. Counting is performed for each two-dimensional small area, and the sum of halftone dot peak pixels of peaks and valleys is taken as a small area count value P. 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 determination result is stored in the temporary memory 4406.

  With reference to FIG. 24, the detection process of the 3rd halftone peak detection part 4403 is demonstrated concretely. The detection processing of the third halftone dot peak detection unit 4403 is intended to detect 100 lines or less and 65 lines (newspaper dot) or more. In this embodiment, a 7 × 7 pixel matrix (generalized as a local region) is used. In this example, an M × M pixel matrix mask is employed. The density Lc of the central pixel group serving as the target pixel is the maximum or the minimum compared to the density groups L1 to L8 of the surrounding pixels, and abs (2Lc−L1−L8) ≧ Lth and abs (2Lc−L2 −L7) ≧ Lth, and when abs (2Lc−L3−L6) ≧ Lth and abs (2Lc−L4−L5) ≧ Lth, the center pixel (Lc) of the mask is the halftone peak pixel (the extreme pixel) ) To detect. The abs function means taking an absolute value as described above. Lth is a threshold value (fixed value).

  Specifically, the surrounding pixels are assumed to be the surrounding pixel distribution pattern shown in FIG. FIG. 24C is a diagram illustrating coordinates of a 7 × 7 pixel matrix corresponding to FIG. When one of the first and second halftone peak detection units 4401 and 4402 based on the surrounding pixel distribution pattern detects a halftone peak pixel, the halftone dot peak is applied to the target pixel (center pixel d4) at that time. A detection signal representing a pixel is provided. The reason why the two patterns are used is to deal with a wide range of halftone dot area ratios.

  The density of the central pixel Lc is determined as Lc = Min (d4, d3, d5, c4, e4) with reference to the peripheral pixels. When Lc is the maximum value with respect to the surrounding pixels, the patterns are L1 = Max (a1, a2, b1), L2 = Max (a3, a4, a5), L3 = Max (a6, a7, c7), L4 = Max (c1, d1, e1), L5 = Max (c7, d7, e7), L6 = Max (f1, g1, g2), L7 = Max (g3, g4, g5), L8 = Max (g6, g7 F7). Here, L1 = Max (a1, a2, b1) means that the maximum density value of the pixels a1, a2, and b1 is set as the value of L1 in the above-described halftone peak pixel detection calculation. Lc = Min (d4, d3, d5, c4, e4) means that Lc is the smallest of d4, d3, d5, c4, e4.

  When the density of the central pixel Lc is Lc = Max (d4, d3, d5, c4, e4), and this Lc is the minimum value with respect to the surrounding pixels, the pattern is L1 = Min (a1, a2, b1) , L2 = Min (a3, a4, a5), L3 = Max (a6, a7, c7), L4 = Max (c1, d1, e1), L5 = Max (c7, d7, e7), L6 = Max (f1 , G1, g2), L7 = Max (g3, g4, g5), and L8 = Max (g6, g7, f7). Lc = Max (d4, d3, d5, c4, e4) means that Lc is the largest of d4, d3, d5, c4, e4.

  In the case of copying, since enlargement / reduction in the sub-scanning direction y is performed at high and low document scanning speeds of the scanner 1, the scanner 1 gives image data that has been enlarged / reduced in the sub-scanning direction y. . Therefore, at the time of reduction, the pattern shown in FIG. When enlarging, the pattern shown in FIG.

  The calculation formula of the third halftone dot peak detection unit 4403 does not calculate with the data of one pixel, but refers to the target pixel with a plurality of pixels (calculation of min and max). This is because a halftone dot with a low line number has a large shade period (the area becomes large), so it is not determined by one pixel, but by referring to surrounding pixels, the influence of noise (dust) is reduced. In addition, the arithmetic operation amount is reduced so that the arithmetic expression can be used in common in other blocks. This facilitates hardware implementation.

  The first halftone dot region detection unit 4404 counts the halftone dot peak pixels of the peaks and valleys detected by the first halftone dot peak detection unit 4401 for each two-dimensional small region of a predetermined size. The sum of halftone dot peak pixels with the valley is taken as a count value P for 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 determination result is stored in the temporary memory 4406.

  If either the first halftone dot area detection unit 4404 or the second halftone dot area detection unit 4405 detects a halftone dot area, the halftone dot / non-halftone dot determination of the processed area near the small area of interest is performed. The threshold value Pth is adaptively changed according to the result (peripheral feature information). In the present embodiment, two values TH1 and TH2 (where TH1> TH2) are prepared as the threshold value Pth, and one of the values is determined based on the determination result of the processed region near the target small region stored in the temporary memory 4406. Select a value. In other words, 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, and therefore TH1 whose conditions are stricter 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.

  The AMP on FIG. 14 shows the distribution of the small regions described above. Each of S1 to S4 of the small area distribution pattern AMP is a small area (block) having a size of, for example, 4 × 4 pixels. 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 of “1” is output from the halftone dot extraction unit 44 when it is determined as a halftone dot region, and “0” when it is determined as a non-halftone dot region. However, this is an example, and TH2 is selected when any one of S1, S2, and S3 is determined to be a halftone dot region, and only when all are determined to be non-halftone regions, TH1 is selected. May be selected. Furthermore, the neighborhood area to be referred to may be only S1 or only S2.

  When detecting color (chromatic) pixels and black (achromatic) pixels in a document, relative reading shifts of R, G, and B exist 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 ideally becomes ideal black when the three signal levels of the R, B, and G density signals coincide. 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, and B images of image data cannot be read simultaneously in time. Since the R, G, and B line sensors are arranged at equal intervals and cannot be read simultaneously in time, the reading position is inevitably displaced. For example, the R, G, 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.

The hue division unit 411 is an example of a pixel classification unit, and is a device for finding a chromatic color region. The input data R, G, and B are converted into signals of c, m, and y and color determination w (white) by the hue dividing unit 411. As an example of hue division, the boundary of each color 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 is as follows. Here, the R, G, and B image data become black (darker) as the number increases.
(1) RY hue region boundary (ry): R-2 * G + B> 0,
(2) Y-G 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,
(7) Color determination w (white) pixel determination: If (R <thwa) & (G <thwa) & (B <thwa), y = m = c = 0. Also,
(8) Y pixel determination: If (ry == 1) & (yg == 0) & (RGB difference> thy), then y = 1 and m = c = 0. Also,
(9) G pixel determination: If (yg == 1) & (gc == 0) & (RGB difference> thg), c = y = 1 and m = 0. Also,
(10) C pixel determination: If (gc == 1) & (cb == 0) & (RGB difference> thc), c = 1 and m = y = 0. Also,
(11) B pixel determination: If (cb == 1) & (bm == 0) & (RGB difference> thb), m = c = 1 and y = 0. Also,
(12) M pixel determination: If (bm == 1) & (mr == 0) & (RGB difference> thm), m = 1 and y = c = 0. Also,
(13) R pixel determination: If (mr == 1) & (ry == 0) & (RGB difference> thr), y = m = 1 and c = 0. Also,
(14) BK pixel determination: When not corresponding to (7) to (13), y = m = c = 1.

  Further, the hue division unit 411 determines the w pixel for color determination. If (R <thw) & (G <thw) & (B <thw), it is set as a w pixel for the color pixel and is output as w. Here, as for the priorities of (7) to (14), the smaller one is prioritized. The above-described threshold values thwa, thy, thm, thc, thr, thg, thb are threshold values determined before copying (processing). The relationship between thw and thwa is thw> tha. The reason why the threshold value is changed for each hue is that the chromatic range is different for each hue region. This hue division is an example, and any formula may be used. The hue division unit 411 outputs 1-bit 3-bit data for c, m, and y and 1-bit data for w for color pixel detection for color determination. The bit plane forming unit forms a 3-bit plane from 3-bit data of c, m, and y that are output signals of the hue division unit 411.

  Each of the memories 412 to 415 corresponds to a region extraction unit, accumulates a 5 × 5 matrix based on each of the outputs c, m, y, and w of the hue division unit 411 and inputs the color pixel determination unit 416. To do.

  FIG. 6 shows the contents of the color pixel determination unit 416. Data of c, m, y, and w for the 5 × 5 matrix are input to the counting units 501 to 504 and the pattern matching units 505 to 508, respectively. First, the flow for obtaining the B / C signal will be described.

  The first counting unit 501 is an example of a second counting unit. When a w determination pixel for color determination is present in a 5 × 5 pixel matrix centered on the target pixel, the first pixel dividing unit 411 performs determination by the hue dividing unit 411 of the pixel. The corrected c, m, and y data are corrected to c = m = y = 0. This correction increases the white level of the pixel matrix. Then, the number of 1 of c, m, and y (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 c, m, and y, the number is counted for each plane in the N × N matrix, and the minimum value is assumed to be black. As a result, correction is possible even if black pixel reading omission occurs. Whether or not the pixel is a chromatic pixel is determined based on the difference between the maximum value and the minimum value. This corrects the pixel in which the black pixel is not read and extracts a chromatic pixel. If there is a certain number of chromatic pixels in the 5 × 5 pixel matrix centered on the pixel of interest, the pixel of interest is determined as a chromatic pixel.

  When the color pixel w pixel exists, the second pattern matching unit 506 corrects the pixel 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 second pattern matching unit 506 determines that all of c, m, and y of the target pixel determined by the hue dividing unit 411 are 1 (c = m = y = 1) or all 0 (c = m = y = It is determined by checking whether the 5 × 5 pixel matrix matches the next pattern whether it is a pixel (color pixel) other than the pixel 0).

  As shown in FIG. 16, the color pixel pattern group includes pattern 1-1 (pm1): D23 & D33 & D431, pattern 1-2 (pm2): D32 & D33 & D34, pattern 1-3 (pm3): D22 & D33 & D44, pattern 1-4 (pm4). : D24 & D33 & D42. The central pixel (target pixel) is D33. White circles on these patterns indicate color pixels. Pattern matching is used to prevent picking up isolated points. Conversely, 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 0 (c = m = y = 0). What is necessary is just to judge by whether there exists.

  Next, the second pattern matching unit 506 detects 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) at that time Pixel) is regarded as a color line pixel.

  The pattern group for fine color lines is pattern 2-1 (pw11a to pw11d): ((D12 & D13 & D14) & (D42 & D43 & D44)) # ((D12 & D13 & D14) & (D52 & D53 & D54)) # ((D22 & D23 & D42) & (D42 & D43 & D44) # (& D42 & D44) # (& ) & (D52 & D53 & D54)), pattern 2-2 (pw12a to pw12d): ((D21 & D31 & D41) & (D24 & D34 & D44)) # ((D21 & D31 & D41) & (D25 & D35 & D45)) # ((D22 & D23 & D24) & (D24 & D24 & D24 & D24 & D24 & D24 & D24 & D24 & D24 & D24 & D24 & D24 & D ) & (D25 & D35 & D45)), pattern 2-3 (pw13a to pw13d): ((D11 & D21 & D12) & ( 35 & D44 & D53)) # ((D11 & D21 & D12) & (D45 & D44 & D55)) # ((D13 & D22 & D31) & (D35 & D44 & D53)) # ((D13 & D22 & D31) & (D45 & D44 & D55)), pattern 2-4 (pw14a (pw14: D & D35 & p35D)) D41 & D51 & D52)) # ((D14 & D15 & D25) & (D41 & D51 & D52)) # ((D13 & D24 & D35) & (D31 & D42 & D53)) # ((D14 & D15 & D25) & (D31 & D42 & D53)).

  Next, the second pattern matching unit 506 performs pattern matching 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 one of the patterns pw21a to pw24d in FIG. 18, the target pixel (center pixel) at that time ) Is regarded as a white area pixel.

  The white area pattern group includes pattern 3-1 (pw21a to pw21d): (D21 & D31 & D41) # (D22 & D32 & D42) # (D24 & D34 & D44) # (D25 & D35 & D45), pattern 3-2 (pw22a to pw22d): (D12 & D13 & D14) # (D24 & D24) (D42 & D43 & D44) # (D52 & D53 & D54), pattern 3-3 (pw23a to pw23d): (D52 & D51 & D41) # (D53 & D42 & D31) # (D35 & D24 & D13) # (D25 & D15 & D14), pattern 3-4 (pw24a to pwD & DD ) # (D31 & D22 & D13) # (D21 & D11 & D12).

  When the extracted pattern matching result satisfies the following conditions, the second pattern matching unit 506 sets the target pixel as the color determination candidate color pixel 2. The condition is ((pm1 == 1) & ((pw11 == 1) # (pw21! = 1))) # ((pm2 == 1) & ((pw12 == 1) # (pw22! = 1) )) # ((Pm3 == 1) & ((pw13 == 1) # (pw23! = 1))) # ((pm4 == 1) & ((pw14 == 1) # (pw24! = 1) )), Where (pm1 == 1) means that the data distribution centered on the pixel of interest matches the pattern pm1, and (pw11 == 1) is any of the patterns pw11a to pw11d (Pw21! = 1) means that it does not match any of the patterns pw21a to pw21d. & Means logical product, and # means logical sum. By 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.

  The fourth pattern matching unit 508 is an example of a pattern matching unit, and executes one-line color fine line pattern matching. The pattern matching unit 508 is a black pixel in which all of c, m, and y of the 3-bit plane assigned to each pixel in the hue dividing unit 411 are black, and a pixel in which all of c, m, and y are 0 in white. Pixels and others are color pixels, and an image region of a 5 × 5 pixel matrix is referred to determine whether or not the pattern shown in FIG. 26 is matched. If they match, the pixel of interest is set as a color pixel candidate 0. In FIG. 26, white circles represent color pixels and x represents white pixels. The blank may be any of black pixels, white pixels, and color pixels. The pattern of FIG. 26 has white pixels on both sides with a line of color pixels continuing in a certain direction. In the case of a color shift of a black character part due to shock jitter or the like, a line of color pixels continues in a certain direction, but no white pixel exists on either side of the line of color pixels. Therefore, by using this pattern, it is possible to appropriately detect the color shift of the black character portion due to the shock jitter.

  Here, the effect of the fourth pattern matching unit 508 will be described using a 5 × 5 matrix. When the scanner 1 reads one line color fine line on the white ground, only the white circles in FIG. 27 are color pixels. Here, in order to determine the target pixel as chromatic, it is necessary to set 5 or less as the threshold value of the difference between the maximum value and the minimum value in the count result by the first count unit 501 of the 3-bit plane of c, m, and y. I do not get. The 1-line color thin line has a difference between the maximum value and the minimum value of 5, and the first count unit 501 determines that the difference between the maximum value and the minimum value of each of c, m, and y is a predetermined threshold value. This is because the pixel of interest is a color pixel candidate on the above condition as one condition. In general, in the case of an m × m matrix (m is an integer), if m or more is not set as the threshold value of the difference between the maximum value and the minimum value, the color misregistration or the like of the black character part may be erroneously detected. Probability of color determination is increased and appropriate determination cannot be performed. If the fourth pattern matching unit does not exist and chromatic determination is performed only by the first count unit, the threshold value must be set to less than 5 in order to determine that one line color thin line is chromatic. If the threshold value is less than 5, the probability of erroneously determining chromaticity such as a color shift of the black character portion increases.

  In this way, pattern matching is executed by the fourth pattern matching unit 508, and one line color fine line can be detected with high accuracy. Therefore, the threshold value in the first count unit 501 is set large so that the color deviation of the black character portion is reduced. While avoiding the chromatic determination, the fourth pattern matching unit 508 can determine the chromatic color of one line color thin line.

  The first color pixel determination unit 509 is an example of a chromatic pixel determination unit. Based on the outputs of the first count unit 501, the second pattern matching unit 506, and the fourth pattern matching unit 508, whether the target pixel is a color pixel. Determine whether or not. If it is color pixel candidate 1 and color pixel candidate 2, it is determined that it is color pixel 1. If the color pixel candidate is 0, it is determined that it is the color pixel 1 regardless of whether it is the color pixel candidate 1 and the color pixel candidate 2. That is, when the fourth pattern matching unit 508 detects one line color thin line, the image processing apparatus prioritizes the detection result of the first count unit 501 and the second pattern matching unit 506, and Therefore, the first count unit 501 does not need to determine the chromaticity of one line color thin line, and the first count unit 501 can detect the black character part more strictly. As a result, the image The processing apparatus can appropriately determine the black character portion and the one-line color thin line.

  The first blocking unit 513 blocks the output of the first color pixel determination unit 509. 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 the first block forming unit 513, 4 × 4 pixels are regarded as one block and output in block units.

  The isolated point removing unit 517 removes the blocked data as isolated points if there is no color pixel block in the adjacent block of the target block.

  When there is one color pixel block, the expansion unit 521 expands the output of the isolated point removal unit 517 to 5 × 5 blocks. The expansion is to prevent black character processing around the color pixel. Here, the B / C signal to be output is L (chromatic) when the color pixel is one block, and H (achromatic) is output otherwise.

  When there is a color determination w pixel in the 5 × 5 pixel matrix centered on the target pixel, the second count unit 502 converts the c, m, and y data determined by the hue division unit 411 of the pixel to c = Correct to m = y = 0. This correction increases the white level of the pixel matrix. Then, the number of 1 of c, m, and y (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 the minimum value is less than thatmin, the target pixel is set as a color pixel candidate 1. “thacnt” and “thamin” are threshold values set before copying (processing).

  The second color pixel determination unit 510 determines whether or not the pixel is a color pixel based on the outputs of the second count unit 510, the second pattern matching unit 506, and the fourth pattern matching unit 508. If it is color pixel candidate 1 and color pixel candidate 2, it is determined that it is color pixel 2. If the color pixel candidate is 0, the color pixel candidate is determined to be the color pixel 2 regardless of whether the color pixel candidate is the color pixel candidate 1 or the color pixel candidate 2.

  As a result, the image processing apparatus can make a chromatic determination of a one-line color thin line without increasing the erroneous determination of color misregistration in the black character portion. As a result, it is possible to determine that a document with one line color fine line is a chromatic document while reducing the probability of erroneously determining an achromatic document as chromatic.

  The second blocking unit 514 blocks the output of the second color pixel determination unit 510. 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 the second blocking unit 514, 4 × 4 pixels are output as a block in a block.

  The first density unit 518 removes the 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), Let it be an active block (color pixel 2 block).

  The third counting unit 503 counts the number of 1 of c, m, and y (c = 1, m = 1, y = 1) of each pixel in the 5 × 5 pixel matrix centered on the target pixel. If the difference between the maximum value and the minimum value of the count values for 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, the color pixel candidate 3 is determined. tha1cnt and tha1min are threshold values set before copying (processing).

  The first pattern matching unit 505 determines whether or not the pixel (c, m, y) determined by the hue dividing unit 411 is a color pixel by pattern matching using a 5 × 5 pixel matrix. The pattern is the same as that of the second pattern matching unit 506. The pixel matched by pattern matching is set as a color pixel candidate 4.

  The third color pixel determination unit 511 determines the color pixel 3 if it is the color pixel candidate 3 and the color pixel candidate 4.

  The third blocking unit 515 blocks the output of the third color pixel determination unit 511. 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. The processing after the third blocking unit 515 outputs 4 × 4 as one block.

  The second density unit 519 has three or more active conditions (color pixel 3 blocks) in the 3 × 3 block for removing the isolated block, and if the target block is active (color pixel 3), the target block Is an active block (3 blocks of color pixels).

  The fourth count unit 504 has 1 of c, m, and y determined by the hue division unit 411 (c = 1, m = 1, y = 1) of each pixel in the 5 × 5 pixel matrix centered on the target pixel. ) Count. If the minimum value of the count values 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).

  The third pattern matching unit 507 performs pattern matching of pixels with c = m = y = 1 in a 5 × 5 pixel matrix centered on the target pixel.

  Patterns used are pattern 1-1 (pm1): D23 & D33 & D43, pattern 1-2 (pm2): D32 & D33 & d34, pattern 1-3 (pm3): D22 & D33 & D44, 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. If it matches any of these patterns, the pixel of interest is designated as a black pixel candidate 2.

  If the target pixel is the black pixel candidate 1 and the black pixel candidate 2, the achromatic determination unit 512 determines the black pixel.

  The fourth blocking unit 516 blocks the output of the achromatic determination unit 512. 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 the fourth block forming unit 516, 4 × 4 pixels are regarded as one block and output in block units.

  The second expansion unit 520 makes the target block non-active (non-black pixel) if the target block is active (black pixel block) and its peripheral pixels are non-active (non-black pixel) in a 3 × 3 block matrix. Block).

  The overall color pixel determination unit 522 determines that the target block is determined to be active (color pixel 2) by the second color pixel determination unit 510 and is not determined to be active (black pixel) by the achromatic determination unit 512. It is determined that the target block is a color (color block). Also, when the third color pixel determination unit 511 is active (color pixel), it is determined that the block is a color block.

  The third expansion unit 523 is configured so that even a single block is included in a 9 × 9 block matrix centered on the target block in order that the total color pixel determination unit 522 considers small characters continuous with respect to the block determined to be a color. If there is an active block, the target block is set as the active block. Here, the reason for the large expansion is to fill the gap between the characters.

  The continuous count unit 524 is an example of a chromatic image determination unit, and determines whether a color document or a monochrome document by looking at the continuity of color pixel blocks. Further, by counting the number of consecutive color pixels in the output data (color pixel block) of the third expansion unit 523, it is determined whether or not the document is a color document.

  FIG. 7 shows the contents of this determination process. When the target pixel is in the color pixel block, the color pixel continuous number of the target pixel is calculated with reference to the color pixel continuous number of the upper left, upper, upper right and left pixels of the target pixel (steps S21 to S26). 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 target pixel is not in the color pixel block, the number of continuous color pixels is set to 0 (steps S21 to S27).

  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 S22). A value obtained by adding 1 to the number of continuous color pixels of (b4) is given (step S24), 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 S23). 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 S25). 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 S26).

  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 greater than the set value THACS (step S28). (Step S29), and the processing of the continuous counting unit 524 is finished 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 document, if the number of continuous color pixels is less than the set value THACS until the end (steps S30 to S34), it is determined that the document is a monochrome image.

  The number of continuous color pixels is substantially the sum of vertical colored line segments and horizontal colored line segments. 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. (Steps S28 and 29).

  The reason why it is separated from the first to third color pixel determination units is to increase the accuracy of determining whether a color document or a monochrome document. The color pixel determination for black character processing is not so conspicuous locally 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 first to fourth counting units are independent. Originally, it is better to make the hue dividing unit 411 independent. However, making the hue dividing unit 411 independent is not preferable because the memory of the first to fourth pattern matching units increases. By changing the parameters of the color pixels (color pixels 1 to 3) with the parameters of the first to fourth counting units (color pixel candidates 1 and 3 and black pixel candidate 1), the increase in the amount of memory is reduced. ing. The reason why the second and third color pixel determination units are provided is to detect a low density color such as yellow of a fluorescent pen, and further, the achromatic determination (black pixel determination) unit 512 is provided with a density. This is because correction is made when a false detection is made. For a light color such as a highlighter, there is no problem even if it is corrected with black data within a certain range. 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.

  Since the count value is counted by the continuous count unit 524 by referring to the count data of the previous line and the count data of the current line, it is possible to accurately count the continuity of the peripheral pixels. It is possible to count continuations. In this embodiment, the hue determination is performed on the R, G, and B image data. However, the hue determination is not limited to the R, G, and B image data, and the hue determination is performed on the luminance color difference (for example, Lab). It is easy.

  As shown in FIG. 4, the overall determination unit 45 includes a character determination unit 451, an expansion processing unit 452, a character determination unit 453, and a decoding unit 454.

  When the result of the edge extraction unit 43 is an edge, the result of the halftone extraction unit 44 is no halftone, and the result of the white region extraction unit 42 is a white region, the character determination unit 451 determines that the character edge. Otherwise, it is determined as a non-character edge (whether a pattern or a character), and the result is output to the expansion processing unit 452 as shown in FIG.

  The expansion processing unit 452 performs OR processing of 8 × 8 blocks on the result of the character determination unit 451, and then performs AND processing of 3 × 3 blocks to perform 4-block expansion processing. 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 Is a character edge, the block of interest is determined to be a character edge, and a total of four blocks including the block of interest and three adjacent blocks are regarded as a character edge. The reason for performing the AND process after the OR process is that, especially in the case of a black character, if there is a small non-black character area around the black character area, a sense of incongruity may occur depending on the difference in processing, for example, black appears to be light. It is. 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.

  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 a time other than black image formation, this black character area becomes thin. Thereafter, AND processing of 3 × 3 blocks is performed, and when image formation other than Bk is performed, OR processing of 5 × 5 blocks is performed, and thereafter, AND processing of 1 × 1 block is performed. Note that 1 × 1 AND processing is synonymous with no processing since the result is the same as before processing. The result of the expansion process is output to the decoding unit 454 as a character edge signal.

  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 if the character is light relative to the edge of the character, the density is saturated, so there is no sense of incongruity.

  FIG. 20 schematically shows an enlargement of the overlapping of 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 is applied to other than Bk and lightens. FIG. 20 (f) shows a preferable case in which only Bk is processed with black characters according to this embodiment, and FIG. 20 (g) shows that only Bk is processed with black characters according to this embodiment, and only Bk is not corrected. , Bk shows a suitable case where correction is applied.

  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). (C) of FIG. 20 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.

  The decoding unit 454 outputs a C / P signal. The C / P signal is as follows.

Further, the color determination unit 41 outputs a B / C signal as shown in FIGS. Thus, the image area processing unit 21 outputs a C / P signal that is a 2-bit signal and a B / C signal that is a 1-bit signal. The C / P signal and the B / C signal are input to the filter processing unit 22, the color correction unit 23, and the scaling processing unit 24 of the scanner correction unit 2 in synchronization with the image data separated into RGB or CMYBk. Alternatively, reference is made as necessary. The C / P signal and the B / C signal are input to the printer correction unit 8 through the compression processing unit 3 and the expansion processing unit 7 together with the image data, or are referred to as necessary.

  FIG. 28 shows a color determination unit used in the second embodiment. 4 has four memories (5 × 5) corresponding to c, m, y, and w, whereas the color determination unit 41 of Example 2 has Bk, Col, and Wh. It is different in that it has three memories (5 × 5) 601 to 603 corresponding to. While the RGB signal is input to the hue division unit 411 of the first embodiment and four signals of CMYW are output, the hue division unit 411 of the second embodiment outputs three signals of Bk, Col, and Wh. Because it is done. Here, Bk represents a black pixel, Wh represents a white pixel, and Col represents a pixel that is neither a white pixel nor a black pixel (R, G, B, C, M, Y pixel) in the hue dividing unit 411 of the first embodiment. ). As a result, R, G, B, C, M, and Y pixels can be combined into 1 bit as Col.

  FIG. 29 is a diagram illustrating a configuration example of the color pixel determination unit 416 used in the second embodiment. Except that the inputs c, m, y, and w in the first embodiment are Bk, Col, and Wh, they are the same as those shown in FIG.

  In the second embodiment, the first to fourth counting units, which are examples of the first counting unit, count the number of “1” of Bk and Col of each pixel in the 5 × 5 pixel matrix. Each count unit determines that the pixel region is an achromatic pixel region when the count number for Bk is equal to or greater than thbk and the count number for Col is equal to or less than thcol. thbk and thcol are threshold values set before copying (processing).

  Thereby, in the second embodiment, since c, m, and y are not assigned to the 3-bit plane as in the first embodiment, it is possible to save the memory. The effect of preventing the black character portion from being determined as a color pixel is the same as that of the first embodiment even when there is a certain amount of color misalignment around the black character portion due to a reading position shift. Further, in the chromatic determination of the document 11, it is possible to determine the chromaticity of one line color thin line by pattern matching without increasing the probability of erroneous determination (determination that it is chromatic) due to color misalignment around the black character portion. This is possible as in the first embodiment. That is, while saving the memory used in comparison with the first embodiment, an original with one line color thin line is a chromatic original without increasing the probability of erroneously determining an achromatic original as chromatic. Can be determined. Therefore, in this embodiment, it is possible to determine the chromaticity of one line color thin line and to accurately determine the black character portion as achromatic. As a result, it is possible to provide a full-color digital copying machine that outputs high-quality black characters without outputting one-line fine line to the transfer paper in the K plate single color.

  The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the above-described embodiments, and various modifications and substitutions can be made to the above-described embodiments without departing from the scope of the present invention. Can be added.

  For example, the functions of the image processing apparatus according to the above-described embodiments may be realized by causing a computer to execute a program. The program may be stored in a computer-readable storage medium. A computer such as an image processing apparatus that intends to execute the function reads the program from a storage medium, stores the program in a storage medium included in the image forming apparatus or the like, reads the stored program, and executes the function . The computer not only realizes the functions of the above-described embodiments by executing the read program, but an operating system or the like running on the computer realizes the functions based on instructions of the program. You may perform all or one part of a process. Further, after the program read from the storage medium is written to the memory provided in the function expansion card or function expansion unit mounted on the computer, the program is read into the function expansion card or function expansion unit based on the instruction of the program code. The provided CPU or the like may execute all or part of the processing for realizing the function.

1 is a block diagram illustrating a schematic configuration example of a full-color image forming apparatus. It is a figure which shows the structural example of a scanner correction | amendment part. It is a figure which shows the structural example of a printer correction | amendment part. It is a figure which shows the structural example of an image area process part. It is a flowchart which shows the process sequence of the update of state variables MS and SS [I] used for white determination. FIG. 3 is a functional block diagram (part 1) illustrating a configuration example of a color pixel determination unit. It is a flowchart which shows the flow of the determination processing procedure in a continuous count part. It is a figure which shows a 600 dpi line pattern and a 400 dpi line pattern. It is a figure which shows the example of a pattern used with a black pixel continuous detection part and a white pixel continuous detection part. It is a figure which shows the example of a pattern used for the white background separation of a RGB white background detection part. It is a figure which shows the example of a pattern used for a color ground detection. It is a figure which shows typically the present line (target line) of the line memory LMP. It is a figure for demonstrating the process of a white area extraction part. It is a figure for demonstrating the detection process of the 1st halftone peak detection part of a halftone extraction part. It is a figure for demonstrating the process of a color determination part. It is a figure for demonstrating the pattern matching in color pixel determination. It is a figure which shows the example of a pattern used for the detection of the color thin line enclosed with white. It is a figure which shows the example of a pattern used for a white area | region detection. It is a figure which shows the specific data of a color pixel continuous number. It is a figure which expands and shows the overlap of the color colorant by color copying typically. It is a block diagram which shows the structural example of a white area extraction part. It is a figure which shows the example of a pattern used for a gray pixel detection. It is a block diagram which shows the detail of a halftone dot extraction part. It is a figure for demonstrating the detection process of a 3rd halftone peak detection part. It is a figure for demonstrating the processing content of the comprehensive determination part. It is a figure which shows the example of a pattern used for 1 line color thin line detection. It is a figure for demonstrating the problem at the time of determining 1 line color thin line. It is a figure which shows the structural example of a color determination part. It is a functional block diagram (the 2) which shows the structural example of a color pixel determination part.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Scanner part 2 Scanner correction | amendment part 3 Compression processing part 4 Controller 5 HDD
6 NIC
7 Decompression processing unit 8 Printer correction unit 9 Plotter 10 General-purpose bus 11 Document 12 External PC terminal 13 Copy image 20 Scanner γ correction unit 21 Image area separation unit 22 Filter processing unit 23 Color correction unit 24 Scaling processing unit 30 Printer γ correction unit 31 gradation processing unit 40 filter unit 41 color determination unit 42 white area extraction unit 43 edge extraction unit 44 halftone dot separation unit 45 total determination unit 411 hue separation unit 412 413 414 415 memory 416 color pixel determination unit 431 three values Conversion unit 432 Black pixel continuous detection unit 433 White pixel continuous detection unit 434 Neighboring pixel detection unit 435 Isolated point removal unit 451 Character determination unit 452 Expansion processing unit 453 Character middle determination unit 454 Decoding unit 501, 502, 503, 504 Count unit 505 , 506, 507, 508 Pattern matching unit 509, 51 511 Color pixel determination unit 512 Achromatic determination unit 513, 514, 515, 516 Blocking unit 517 Isolated point removal unit 518, 519 Density unit 520, 521, 523 Expansion unit 522 Total color pixel determination unit 524 Continuous count unit 601, 602, 603 Memory 4201 Binary unit 4202 RGB white extraction unit 4203 White determination unit 4204 White pattern matching unit 4205 White pattern correction unit 4206 White expansion unit 4207 White contraction unit 4208 White correction unit 4209 Gray pattern matching unit 4210 Gray expansion unit 4211 Determination unit 4212 Gray pixel detection unit 4213 Color pixel detection unit 4214 RGB white detection unit 4401, 4402, 4403 Halftone peak detection unit 4404, 4405 Halftone region detection unit 4406 Temporary storage means

Claims (8)

Pixel classification means for classifying pixels of a read image read from a document into white pixels, black pixels, and non-monochrome pixels;
Number of vertical and horizontal pixels are a plurality of identification pattern group is a predetermined number, vertical, horizontal, or are arranged on both sides of the non-white pixel group and the non-white pixel group of one pixel width continuously over the predetermined number of diagonally A plurality of identification pattern groups for detecting one line color fine line on the white ground, including a white pixel group ;
A region extracting means for extracting a local region including the target pixel in the read image and having a number of vertical and horizontal pixels equal to or larger than the predetermined number from the read image;
Pattern matching means for checking whether one of the identification pattern groups matches the arrangement of the white pixels and the non-monochrome pixels in the local area extracted by the area extraction means;
Chromatic pixel determining means for determining whether or not the target pixel is a chromatic pixel based on a matching result of the pattern matching means;
An image processing apparatus comprising: First counting means for counting the number of the black pixels and the non-monochrome pixels in the local area,
The chromatic pixel determining means determines whether or not the pixel of interest is a chromatic pixel based on a counting result of the first counting means and a matching result of the pattern matching means;
The image processing apparatus according to claim 1. A 3-bit signal representing C (cyan), M (magenta), Y (yellow), R (red), G (green), Bk (black), and W (white) is output from each pixel of the read image read from the document. Bit plane forming means for generating and further forming three bit planes from these three bit signals;
From the three bit planes having a value of “0” or “1” corresponding to each pixel of the local area , the number of bit planes having a value of “1” is distributed over the entire local area. Second counting means for counting for each bit plane ,
The chromatic pixel determining means determines whether or not the pixel of interest is a chromatic pixel based on a counting result of the second counting means and a matching result of the pattern matching means.
The image processing apparatus according to claim 1.   4. The chromatic image determination unit according to claim 1, further comprising: a chromatic image determination unit configured to determine whether the read image is a chromatic image based on a determination result of the chromatic pixel determination unit. The image processing apparatus described.   An image forming apparatus comprising the image processing apparatus according to claim 1. Number of vertical and horizontal pixels are a plurality of identification pattern group is a predetermined number, vertical, horizontal, or are arranged on both sides of the non-white pixel group and the non-white pixel group of one pixel width continuously over the predetermined number of diagonally An image processing method having a plurality of identification pattern groups for detecting one line color fine line on the white ground including a white pixel group ,
An original reading step for reading an original;
A pixel classification step of classifying pixels of the read image acquired in the document reading step into white pixels, black pixels, and non-monochrome pixels;
A region extracting step of extracting a local region including the target pixel in the read image and having a number of vertical and horizontal pixels equal to or larger than the predetermined number from the read image;
A pattern matching step for collating whether one of the identification pattern groups matches the arrangement of the white pixels and the non-monochrome pixels in the local region extracted by the region extraction unit;
A chromatic pixel determination step for determining whether or not the target pixel is a chromatic pixel based on a matching result in the pattern matching step;
An image processing method comprising:   A program for causing a computer to execute the image processing method according to claim 6.   A computer-readable storage medium storing the program according to claim 7.