JP2010136036A - Image processor, image conversion method, and computer program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To expand a binary image so as to make jaggies inconspicuous without using pattern matching. <P>SOLUTION: An image forming apparatus is provided with: a jaggy detecting section 30 for detecting a boundary pixel being a pixel that comes into contact with both a white pixel group and a black pixel group from the binary image, an on-dot counting section 31 and a gradation calculating section 32 for calculating the gradation of a gray scale of the detected boundary pixel on the basis of the boundary pixel and peripheral pixels of the boundary pixel, a pixel of interest gradation determining section 33 for converting the binary image into a first gray scale image being a gray scale image by correcting the value of the detected boundary image to the gradation calculated about the boundary image, and a gray scale image generating means for converting the first gray scale image into a second gray scale image by performing resolution conversion processing for improving resolution. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an apparatus and method for processing a binary image.

  In recent years, fax communication has become widespread. According to fax communication, binary images are exchanged between two devices. The receiving side may enlarge and print a binary image.

  When the binary image is enlarged, the slanted lines and the wobbles (jagged edges) of the curve become conspicuous. In view of this, a method for making rattling inconspicuous has been proposed.

  According to the method described in Patent Document 1, the frame memory can store binary image data and multi-value image data in a mixed state, and image processing of binary image data is performed by a binary image processing unit. The multi-value image processing unit performs image processing of the multi-value image data. At this time, a table stored in the RAM is referred to. The binary image processing unit and the multi-value image processing unit output density data of the pixel of interest, and the semiconductor laser driver performs pulse width modulation and power modulation of the semiconductor laser based on the density data. Further, the binary image processing unit or the multi-value image processing unit outputs direction data of the target pixel, and the semiconductor laser driver performs pulse width modulation and power modulation of the semiconductor laser based on the direction data. Image output is performed based on the image data processed in this way.

  According to the method described in Patent Document 2, the binarization circuit performs binarization processing on the character / line drawing portion of the multi-value image data based on the detection result of the Tag discrimination circuit. The smoothing enlargement circuit performs a smoothing enlargement process on the binarized character / line drawing data using the jaggy detection pattern and the enlarged output pattern stored in the ROM. The background calculation circuit calculates a pixel value (non-background value) of a pixel representing a character / line image and a pixel value (background value) of the other part based on the multi-value image data and the tag data. The binary multi-value conversion circuit converts the binary smoothed enlarged image data obtained by the smoothing enlargement circuit into multi-value image data based on the non-background value (multi-value data) and the background value (multi-value data).

  According to the method described in Patent Document 3, the binarization circuit performs binarization processing on the character / line drawing part of the multi-value image data based on the detection result of the Tag discrimination circuit. The pattern matching circuit detects jaggy from the binarized data using the jaggy detection pattern stored in the ROM. The background calculation circuit calculates a pixel value (non-background value) of a pixel representing a character / line image and a pixel value (background value: background) of the other part based on the multi-value image data and the tag data. The smoothing processing value calculation circuit calculates a conversion pixel value for performing the smoothing processing on the data of the character / line drawing part using the pixel conversion rate, the background value, and the non-background value.

According to the method described in Patent Document 4, the image processing apparatus sequentially extracts 4 × 4 size image blocks from the input image, and 2 × 2 jaggy, convex points, or isolated points are extracted from the extracted image blocks. The constituent pixels are extracted as degraded pixels by pattern matching. Next, the image processing apparatus corrects the deteriorated pixel by replacing the extracted deteriorated pixel with a pixel value having the highest appearance frequency in the pixel group existing around the deteriorated pixel. Enlarge the image with a high-quality enlargement algorithm.
JP 7-250246 A JP 2000-125134 A JP 2000-156784 A JP 2006-33308 A

  As described in Patent Documents 1 to 4, conventionally, a shaky portion in a binary image is extracted by matching with a predetermined pattern. However, the use of pattern matching increases the circuit scale.

  In view of such a problem, an object of the present invention is to enlarge a binary image so that rattling is not noticeable without using pattern matching.

  An image processing apparatus according to an aspect of the present invention includes a boundary pixel detection unit that detects a boundary pixel that is a pixel in contact with both a white pixel group and a black pixel group from a binary image, and a gray level of the boundary pixel. Gradation calculating means for obtaining the gradation of the scale based on the boundary pixel and surrounding pixels, and correcting the binary image by correcting the value of the boundary pixel to the gradation determined for the boundary pixel. A first conversion means for converting the first grayscale image, which is a grayscale image, and the first grayscale image is converted into a second grayscale image by performing a resolution conversion process for improving the resolution. And second conversion means.

  Preferably, the boundary pixel detection unit is configured so that pixels included in the binary image are in contact with a first line and a second line that are parallel to each other, and the boundary line detection unit includes the first line and the second line. When all the other pixels included in one line are white and all the other pixels included in the other line are black, the pixel is detected as the boundary pixel, and the gradation calculation means The gradation of the boundary pixel is obtained based on the number of black pixels included in a third line sandwiched between the first line and the second line.

  Alternatively, the boundary pixel detection means includes a plurality of boundary pixel detection means, and each of the boundary pixel detection means detects the boundary pixels using the different first lines and the different second lines. A plurality of gradation calculation means are provided so as to correspond to the respective boundary pixel detection means, and each gradation calculation means has the gradation of the boundary pixel detected by the corresponding boundary pixel detection means. The first conversion means corresponds to the value of the boundary pixel detected by at least one of the plurality of boundary pixel detection means for each of the boundary pixel detection means that detected the boundary pixel. The binary image is converted into one of the gradations calculated by the gradation calculating means or converted into an average value of the gradations, thereby converting the binary image into the first grayscale. It converted to le image.

  Alternatively, at least one of the plurality of boundary pixel detection means detects the boundary pixel using two lines parallel to the main scanning direction as the first line and the second line, and at least one Detects the boundary pixel by using two lines parallel to the sub-scanning direction as the first line and the second line.

  Alternatively, all or some of the plurality of boundary pixel detection units detect the boundary pixels in accordance with the degree of improvement in the resolution in the resolution conversion process.

  According to the present invention, it is possible to enlarge a binary image so that the rattling is not noticeable without using pattern matching.

  1 is a diagram showing an example of the overall configuration of the fax communication system NT, FIG. 2 is a diagram showing an example of the hardware configuration of the image forming apparatus 1, and FIG. 3 is a diagram showing an example of the configuration of the correction circuit 10j. .

  As shown in FIG. 1, the fax communication system NT includes a plurality of image forming apparatuses 1 and communication lines 8. The two image forming apparatuses 1 can be connected to each other via the communication line 8. As the communication line 8, an analog telephone line or ISDN (Integrated Services Digital Network) is used.

  The image forming apparatus 1 is an apparatus generally called a multi-function peripheral or MFP (Multi Function Peripherals), and is an apparatus in which functions such as copying, facsimile (facsimile), network printing, scanning, and box are integrated.

  The network printing function is a function for receiving image data from the personal computer 2 and printing an image on paper. Sometimes called a “network printer function” or a “PC print function”.

  The box function is a function for giving a storage area called “box” or “personal box” for each user, and for each user to save and manage document data such as an image file in his / her storage area. That is, it is a function of the file server. A box corresponds to a “folder” or “directory” in a personal computer.

  As shown in FIG. 2, the image forming apparatus 1 includes a CPU (Central Processing Unit) 10a, a RAM (Random Access Memory) 10b, a ROM (Read Only Memory) 10c, a mass storage device 10d, a scanner 10e, a printing device 10f, In addition to the network interface 10g, the touch panel 10h, the modem 10i, and the correction circuit 10j, various control circuits are included.

  The scanner 10e is an apparatus that generates image data by reading an image such as a photograph, a character, a picture, or a chart written on a document.

  The printing device 10f prints an image read by the scanner 10e or an image indicated by image data received from another device. In addition, an image processed by a correction circuit 10j described later is printed.

  The touch panel 10h displays a screen for giving a message or an instruction to the user, a screen for the user to input processing commands and conditions, a screen showing the processing result of the CPU 10a, and the like. Moreover, the position which the user touched with the finger | toe is detected, and the signal which shows a detection result is transmitted to CPU10a.

  The network interface 10g is a network interface card (NIC) for communicating with other devices such as the personal computer 2 via the communication line 8 using TCP / IP (Transmission Control Protocol / Internet Protocol).

  The modem 10i is a device for exchanging image data with another fax terminal using a G3 protocol via a fixed telephone network. When image data is exchanged using the G4 protocol, a TA (Terminal Adapter) is used instead of the modem 10i.

  The ROM 10c or the large-capacity storage device 10d stores programs for realizing the above functions, such as an operating system, middleware, and various applications.

  The correction circuit 10j is an ASIC (Application Specific Integrated Circuit) that corrects an image indicated in the fax image data (hereinafter referred to as “fax image data 70”) received and digitized by the modem 10i. As shown in FIG. 3, the correction circuit 10j includes a memory 21, a rattling correction processing unit 22, a resolution conversion processing unit 23, an error diffusion processing unit 24, and the like.

  4 is a diagram illustrating an example of the configuration of the rattling correction processing unit 22, FIGS. 5 and 6 are diagrams for explaining the processing of the rattling correction processing unit 22, and FIG. 7 illustrates the number of black pixels and gray levels. It is a figure which shows the example of the relationship with the gradation of a scale.

  Hereinafter, the processing contents of each part of the correction circuit 10j will be described in detail.

  The memory 21 is a buffer that temporarily stores the fax image data 70 received and digitized by the modem 10i. The memory 21 is managed by FIFO (First In First Out). As the memory 21, a DRAM (Dynamic Random Access Memory) or an SRAM (Static Random Access Memory) is used.

  The memory 21 has a capacity capable of storing at least data for 7 lines of pixels in the main operation direction of the binary image. If a binary image of A3 size is handled, it has a capacity of about 8000 × 6 bits.

  Each pixel of the image PT0 shown in the fax image data 70 is either white or black. That is, the image PT0 is a binary image.

  The rattling correction processing unit 22 reduces shakiness by converting the image PT0 shown in the fax image data 70 into a black and white image of gray, that is, a grayscale image.

  As shown in FIG. 4, the rattling correction processing unit 22 includes a shading detection unit 30, an on-dot counting unit 31, a tone calculation unit 32, a target pixel tone determination unit 33, and a grayscale image generation unit 34. Consists of.

  The rattling detection unit 30 includes a first rattling detection unit 30a, a second rattling detection unit 30b, a third rattling detection unit 30c, a fourth rattling detection unit 30d, and a fifth The backlash detection unit 30e and the sixth backlash detection unit 30f are configured.

  The on dot count unit 31 includes a first on dot count unit 31a, a second on dot count unit 31b, a third on dot count unit 31c, a fourth on dot count unit 31d, and a fifth on dot count unit. 31e and a sixth on-dot count unit 31f.

  The gradation calculator 32 includes a first gradation calculator 32a, a second gradation calculator 32b, a third gradation calculator 32c, a fourth gradation calculator 32d, and a fifth gradation calculator. 32e and a sixth gradation calculation unit 32f.

  Here, with reference to FIG. 5 and FIG. 6, processing of each unit of the rattling correction processing unit 22 will be described in detail.

  In FIG. 5, the first rattling detector 30a, the first on-dot count unit 31a, and the first gradation calculation unit 32a are one of the pixels D constituting the binary image to be processed. The gray scale gradation (hereinafter simply referred to as “gradation”) of the pixel D (hereinafter referred to as “target pixel DW”) is the target pixel DW as in the 3 × 3 matrix MT1. And the process for calculating | requiring based on each value of the pixel D which surrounds it is performed.

  Hereinafter, a pixel D having x dots in the sub-scanning direction and y dots in the main scanning direction with the upper left corner of the binary image as the origin is referred to as “pixel Dxy”.

  The first rattling detection unit 30a detects whether or not the target pixel DW is located in the shaky portion in the binary image. Incidentally, rattling is usually found at the boundary between a white pixel group and a black pixel group.

  Therefore, the first rattling detection unit 30a detects whether or not the target pixel DW is located in the shaky portion as follows.

  The first rattling detection unit 30a includes a pixel D that is one pixel below the pixel of interest DW (a pixel D advanced by one in the sub-scanning direction) and the left and right pixels D that are adjacent to the pixel D (main scanning direction). The value of the pixel D advanced by 1 and the pixel D) returned by 1 is checked. That is, for example, if the target pixel DW is the pixel D44, the values of the pixels D53, D54, and D55 are checked. Hereinafter, the pixel group of these pixels D is referred to as a “first pixel group L1”.

  Further, the values of the pixel D one above the target pixel DW and the left and right pixels D adjacent to the pixel D are checked. If the target pixel DW is the pixel D44, the values of the pixels D33, D34, and D35 are checked. Hereinafter, the pixel group of these pixels D is referred to as “second pixel group L2”.

  The values of the pixels D in the first pixel group L1 are all “0” or all “1”, and all the values of the pixels D in the second pixel group L2 are all in the first pixel group. When the value is different from the value of the pixel D of L1, the first rattling detection unit 30a detects that the target pixel DW is located in the rattling portion. That is, if pixels D53, D54, and D55 are all white and pixels D33, D34, and D35 are all black, or pixels D53, D54, and D55 are all black and pixels D33, D34, and D35 are When all the pixels are white, it is detected that the target pixel DW is located in the shaky portion.

  The first on-dot counting unit 31a counts a pixel having a value of “1” (that is, a black pixel) among the target pixel DW and the left and right pixels D adjacent thereto. Hereinafter, the pixel group of these pixels D is referred to as a “third pixel group L3”. For example, when the target pixel DW is the pixel D44, the pixel D that is black among the pixels D43, D44, and D45 is counted.

  The first gradation calculation unit 32a detects the black counted by the first on-dot counting unit 31a when the first rattling detection unit 30a detects that the pixel of interest DW is located in the rattling portion. The gradation of the target pixel DW is calculated based on the number of pixels. However, as the number increases, the gradation is calculated so as to be closer to black. The gradation may be calculated by a predetermined function, or may be obtained by referring to a table as shown in FIG. Hereinafter, the gradation calculated by the first gradation calculation unit 32a is referred to as “first gradation SC1”.

  The second rattling detection unit 30b, the second on-dot counting unit 31b, and the second tone calculation unit 32b are also configured as a first rattling detection unit 30a, a first on-dot counting unit 31a, and Similar to the first gradation calculation unit 32a, a process for obtaining the gradation of the target pixel DW is performed. However, here, 15 pixels D centered on the target pixel DW, such as the matrix MT2, are referred to.

  Similar to the first rattling detection unit 30a, the second rattling detection unit 30b detects whether or not the target pixel DW is located in the rattling part. However, the second rattling detection unit 30b is configured such that the first pixel group L1 includes a pixel D that is one pixel below the pixel of interest DW and two pixels D that are adjacent to the pixel D. Detection is performed on the assumption that the second pixel group L2 is composed of a pixel D one above the target pixel DW and two pixels D adjacent to the pixel D. That is, for example, if the target pixel DW is the pixel D44, the first pixel group L1 is configured by the pixels D52, D53, D54, D55, and D56, and the second pixel group L2 is the pixels D32, D33, D34. , D35, and D36 are detected.

  Similar to the first on-dot count unit 31a, the second on-dot count unit 31b counts black pixels in the third pixel group L3. However, the second on-dot counting unit 31b counts that the third pixel group L3 is composed of the pixel of interest DW and two pixels D on each of the left and right adjacent thereto. For example, when the target pixel DW is the pixel D44, the pixel D that is black among the pixels D42, D43, D44, D45, and D46 is counted.

  The second tone calculation unit 32b detects the black counted by the second on-dot counting unit 31b when the second shakiness detection unit 30b detects that the pixel of interest DW is located in the backlash portion. The gradation of the target pixel DW is calculated based on the number of pixels. However, as the number increases, the gradation is calculated so as to be closer to black. The gradation may be calculated by a predetermined function, or may be obtained by referring to a table as shown in FIG. Hereinafter, the gradation calculated by the second gradation calculating unit 32b is referred to as “second gradation SC2”.

  Similarly, the third rattling detection unit 30c, the third on-dot count unit 31c, and the third tone calculation unit 32c perform processing for obtaining the tone of the pixel of interest DW. However, here, 21 pixels D centered on the target pixel DW, such as the matrix MT3, are referred to.

  The third rattling detection unit 30c detects whether or not the target pixel DW is located in the rattling part, like the first rattling detection unit 30a. However, in the third rattling detection unit 30c, the first pixel group L1 includes a pixel D that is one pixel below the pixel of interest DW, and three pixels D that are adjacent to the pixel D on the left and right sides. Detection is performed on the assumption that the second pixel group L2 includes a pixel D that is one pixel above the target pixel DW and three pixels D that are adjacent to the pixel D. That is, for example, if the target pixel DW is the pixel D44, the first pixel group L1 is configured by the pixels D51, D52, D53, D54, D55, D56, and D57, and the second pixel group L2 is the pixel D31. , D32, D33, D34, D35, D36, and D37 are detected.

  The third on-dot count unit 31c counts black pixels in the third pixel group L3 in the same manner as the first on-dot count unit 31a. However, the third on-dot counting unit 31c counts that the third pixel group L3 includes the pixel of interest DW and three pixels D on each of the left and right adjacent thereto. For example, when the target pixel DW is the pixel D44, the pixel D that is black among the pixels D41, D42, D43, D44, D45, D46, and D47 is counted.

  The third gradation calculation unit 32c detects the black counted by the third on-dot counting unit 31c when the third backlash detection unit 30c detects that the target pixel DW is located in the backlash portion. The gradation of the target pixel DW is calculated based on the number of pixels. However, as the number increases, the gradation is calculated so as to be closer to black. The gradation may be calculated by a predetermined function, or may be obtained by referring to a table as shown in FIG. Hereinafter, the gradation calculated by the third gradation calculating unit 32c is referred to as “third gradation SC3”.

  In FIG. 6, the fourth backlash detection unit 30d, the fourth on-dot count unit 31d, and the fourth tone calculation unit 32d are also provided with the first backlash detection unit 30a and the first on-dot count. Similarly to the unit 31a and the first gradation calculation unit 32a, processing for obtaining the gradation of the target pixel DW is performed based on the value of the target pixel DW and the values of the eight pixels D surrounding the target pixel DW. However, as will be described next, the directions of the first pixel group L1, the second pixel group L2, and the third pixel group L3 are different from those of the first rattling detection unit 30a and the like.

  The fourth rattling detection unit 30d detects whether or not the target pixel DW is located in the rattling part, like the first rattling detection unit 30a. However, in the fourth rattling detection unit 30d, the first pixel group L1 includes a pixel D right by one of the target pixel DW and upper and lower pixels D adjacent to the pixel D, and the second pixel group Detection is performed on the assumption that L2 is constituted by a pixel D to the left of the target pixel DW and upper and lower pixels D adjacent to the pixel D. That is, for example, if the target pixel DW is the pixel D44, the first pixel group L1 is configured by the pixels D35, D45, and D55, and the second pixel group L2 is configured by the pixels D33, D43, and D53. Detection.

  The fourth on-dot count unit 31d counts black pixels in the third pixel group L3 in the same manner as the first on-dot count unit 31a. However, the fourth on-dot counting unit 31d counts that the third pixel group L3 includes the target pixel DW and the upper and lower pixels D adjacent thereto. For example, when the target pixel DW is the pixel D44, the pixel D that is black among the pixels D34, D44, and D54 is counted.

  The fourth gradation calculation unit 32d detects the black counted by the fourth on-dot counting unit 31d when the fourth rattling detection unit 30d detects that the pixel of interest DW is located in the rattling portion. The gradation of the target pixel DW is calculated based on the number of pixels. However, as the number increases, the gradation is calculated so as to be closer to black. The gradation may be calculated by a predetermined function, or may be obtained by referring to a table as shown in FIG. Hereinafter, the gradation calculated by the fourth gradation calculating unit 32d is referred to as “fourth gradation SC4”.

  The fifth rattling detection unit 30e, the fifth on-dot counting unit 31e, and the fifth gradation calculation unit 32e are also provided with a fourth rattling detection unit 30d, a fourth on-dot counting unit 31d, and Similar to the fourth gradation calculation unit 32d, a process for obtaining the gradation of the target pixel DW is performed. However, here, 15 pixels D centered on the target pixel DW, such as the matrix MT5, are referred to.

  The fifth rattling detection unit 30e detects whether or not the target pixel DW is located in the rattling part, like the fourth rattling detection unit 30d. However, in the fifth rattling detection unit 30e, the first pixel group L1 is configured by a pixel D to the right of the target pixel DW and two pixels D adjacent to the pixel D, and two pixels D above and below. Detection is performed on the assumption that the second pixel group L2 includes a pixel D to the left of the target pixel DW and two pixels D adjacent to the pixel D. That is, for example, if the target pixel DW is the pixel D44, the first pixel group L1 is configured by the pixels D25, D35, D45, D55, and D65, and the second pixel group L2 is the pixels D23, D33, D43. , D53, and D63 are detected.

  The fifth on-dot count unit 31e counts black pixels in the third pixel group L3 in the same manner as the fourth on-dot count unit 31d. However, the fifth on-dot count unit 31e counts that the third pixel group L3 includes the pixel of interest DW and two pixels D that are adjacent to each other. For example, when the target pixel DW is the pixel D44, the pixel D that is black among the pixels D24, D34, D44, D54, and D64 is counted.

  The fifth gradation calculation unit 32e detects the black counted by the fifth on-dot counting unit 31e when the fifth rattling detection unit 30e detects that the target pixel DW is located in the rattling portion. The gradation of the target pixel DW is calculated based on the number of pixels. However, as the number increases, the gradation is calculated so as to be closer to black. The gradation may be calculated by a predetermined function, or may be obtained by referring to a table as shown in FIG. Hereinafter, the gradation calculated by the fifth gradation calculating unit 32e is referred to as “fifth gradation SC5”.

  Similarly, the sixth rattling detection unit 30f, the sixth on-dot count unit 31f, and the sixth tone calculation unit 32f perform processing for obtaining the tone of the pixel of interest DW. However, here, 21 pixels D centered on the target pixel DW, such as the matrix MT6, are referred to.

  The sixth rattling detection unit 30f detects whether or not the target pixel DW is located in the rattling part, similarly to the fourth rattling detection unit 30d and the like. However, the sixth rattling detection unit 30f is configured such that the first pixel group L1 includes a pixel D to the right of the pixel of interest DW and three pixels D adjacent to the pixel D, and three pixels D above and below. Detection is performed on the assumption that the second pixel group L2 includes a pixel D to the left of the pixel of interest DW and three pixels D adjacent to the pixel D. That is, for example, if the target pixel DW is the pixel D44, the first pixel group L1 is configured by the pixels D15, D25, D35, D45, D55, D65, and D75, and the second pixel group L2 is the pixel D13. , D23, D33, D43, D53, D63, and D73 are detected.

  The sixth on-dot count unit 31f counts black pixels in the third pixel group L3 in the same manner as the fourth on-dot count unit 31d. However, the sixth on-dot counting unit 31f counts that the third pixel group L3 includes the pixel of interest DW and three pixels D that are adjacent to each other. For example, when the target pixel DW is the pixel D44, the pixel D that is black among the pixels D14, D24, D34, D44, D54, D64, and D74 is counted.

  The sixth tone calculation unit 32f detects the black counted by the sixth on-dot counting unit 31f when the sixth rattling detection unit 30f detects that the pixel of interest DW is located in the rattling portion. The gradation of the target pixel DW is calculated based on the number of pixels. However, as the number increases, the gradation is calculated so as to be closer to black. The gradation may be calculated by a predetermined function, or may be obtained by referring to a table as shown in FIG. Hereinafter, the gradation calculated by the sixth gradation calculating unit 32f is referred to as “sixth gradation SC6”. The first gradation SC1 to the sixth gradation SC6 may be collectively referred to as “gradation SC”.

  Returning to FIG. 4, the pixel-of-interest gradation determination unit 33 changes the first gradation SC1 to the sixth gradation SC6 obtained by the first gradation calculation unit 32a to the sixth gradation calculation unit 32f. Based on this, the gradation of the target pixel DW is determined as follows.

  Priorities are assigned in advance to the first gradation SC1 to the sixth gradation SC6. For example, the priority is higher in the order of the third gradation SC3, the sixth gradation SC6, the second gradation SC2, the fifth gradation SC5, the first gradation SC1, and the fourth gradation SC4. Shall. Then, the gradation SC having the highest priority among the obtained first gradation SC1 to sixth gradation SC6 is determined as the gradation of the target pixel DW.

  Alternatively, the average value of the first gradation SC1 to the sixth gradation SC6 may be determined as the gradation of the target pixel DW.

  However, when one of the first gradation SC1 to the sixth gradation SC6 is not obtained, that is, the first rattling detection unit 30a to the sixth gradation described with reference to FIGS. If it is not detected that the pixel of interest DW is located in the portion of the wobble detection unit 30f that is wobbled, the gradation is determined to be “0” if the pixel of interest DW is white, and if it is black. The gradation is determined to be “255” (in the case of 256 gradations).

  As described above, the rattling detection unit 30, the on-dot count unit 31, the tone calculation unit 32, and the target pixel tone determination unit 33 of the rattling correction processing unit 22 apply the received fax image data 70 to the received fax image data 70. The gradation of each pixel D is determined while paying attention to each pixel D of the binary image shown.

  Then, the gray scale image generation unit 34 converts the value of each pixel of the binary image into a gray scale image by replacing the gray level determined by the target pixel gray level determination unit 33. That is, the binary image is converted into a gray scale image. Hereinafter, the image obtained by the rattling correction processing unit 22 is referred to as “image PT1”.

  Returning to FIG. 3, the resolution conversion processing unit 23 includes a main scanning resolution conversion unit 23a, a sub-scanning resolution conversion unit 23b, and the like, and performs a process of increasing the resolution of the image PT1 using a Bicubic algorithm. The main scanning resolution conversion unit 23a increases the resolution in the main scanning direction, and the sub scanning resolution conversion unit 23b increases the resolution in the sub scanning direction. For example, the resolution increases from 200 dpi to 600 dpi. Hereinafter, the image obtained by the resolution conversion processing unit 23 is referred to as “image PT2”.

  The error diffusion processing unit 24 converts the image PT2 into a binary image by an error diffusion method. Hereinafter, an image obtained by the error diffusion processing unit 24 is referred to as “image PT3”. Then, the image PT3 is printed by the printing device 10f.

  FIG. 8 is a flowchart for explaining an example of the overall processing flow of the image forming apparatus 1. Next, the flow of processing when receiving a fax in the image forming apparatus 1 will be described with reference to the flowchart of FIG.

  When receiving the fax image data 70 (# 11 in FIG. 8), the image forming apparatus 1 focuses on the first pixel D of the image PT0 indicated in the fax image data 70 (# 12). That is, the first pixel D is set as the target pixel DW.

  The image forming apparatus 1 counts the number of black pixels D on the line (third pixel group L3) including the target pixel DW by the six methods described in FIGS. 5 and 6 (# 14). It is detected whether or not the target pixel DW is located in the shaky part (# 15). If it is determined that the position is in the shaky portion (Yes in # 16), the gradation is obtained (# 17).

  The image forming apparatus 1 determines the gradation of the target pixel DW based on the first gradation SC1 to the sixth gradation SC6 obtained by the six methods (# 20).

  If a pixel D that has not been noticed still remains (# 21), the pixel D is noticed (# 22), and the gradation is determined by the above-described processing (# 13 to # 20).

  The image forming apparatus 1 can convert the image PT0 into the grayscale image PT1 by determining the gradation of all the pixels D in this way.

  Further, the image forming apparatus 1 increases the resolution of the image PT1 by Bicubic algorithm to generate the image PT2 (# 23), binarizes the image PT2 by the error diffusion method, and generates the image PT3 (# 24). Then, the image forming apparatus 1 prints the image PT3 on a sheet (# 25).

  According to the present embodiment, the binary image can be enlarged without using the pattern matching so that the rattling is not noticeable.

  In this embodiment, the case where the image forming apparatus 1 receives the fax image data 70 and corrects and prints the binary image has been described as an example. However, the present invention can also be applied to an apparatus dedicated to fax.

  In the present embodiment, correction processing is performed by the correction circuit 10j, but may be performed by software. According to the correction circuit 10j, it is possible to detect (detect) six pixels D located in a shaky portion and obtain a gradation in parallel. However, when performed by software, it is performed in parallel by a plurality of CPUs. It may be performed one by one by one CPU.

  9 and 10 are diagrams showing examples of the relationship between the number of black pixels and the gray scale gradation.

  In the present embodiment, the six rattling detection units (first rattling detection unit 30a to sixth rattling detection unit 30f) included in the rattling correction processing unit 22, six on-dot counts. Part (first on-dot counting part 31a to sixth on-dot counting part 31f) and six gradation calculation parts (first gradation calculation part 32a to sixth gradation calculation part 32f) were used. However, what is used may be changed according to the degree of improvement in resolution when the resolution conversion processing unit 23 converts the image PT1 into the image PT2. However, it is desirable to use more as the degree of improvement increases.

  For example, when a 200 dpi image PT0 is converted to a 600 dpi image PT1, all the above-described units are used. Then, of the first gradation SC1 to the sixth gradation SC6, the highest priority order that can be obtained is determined as the gradation of the target pixel DW. Note that the table shown in FIG. 9 may be used instead of the table shown in FIGS.

  Alternatively, when converting the 400 dpi image PT0 to the 600 dpi image PT1, the first rattling detection unit 30a, the second rattling detection unit 30b, the fourth rattling detection unit 30d, and the fifth The rattling detection unit 30e and an on-dot count unit and a gradation calculation unit corresponding to each rattling detection unit are used. Then, among the first gradation SC1, the second gradation SC2, the fourth gradation SC4, and the fifth gradation SC5, the highest priority order that can be obtained is determined as the target pixel DW. The gradation is determined. Note that the table shown in FIG. 10 may be used instead of the table shown in FIGS.

  Alternatively, when the 600 dpi image PT0 is converted to the 600 dpi image PT1, the first rattling detection unit 30a and the fourth rattling detection unit 30d and the on-dots corresponding to the respective rattling detection units. A count unit and a gradation calculation unit are used. Of the first gradation SC1 and the fourth gradation SC4, the one that can be obtained is determined as the gradation of the target pixel DW.

  The resolution of the image PT2 to be converted may be specified by the user on the touch panel 10h.

  In addition, the configuration of the entire image forming apparatus 1 or each unit, the processing content, the processing order, the configuration of the database, and the like can be appropriately changed in accordance with the spirit of the present invention.

It is a figure which shows the example of the whole structure of a fax communication system. 2 is a diagram illustrating an example of a hardware configuration of an image forming apparatus. FIG. It is a figure which shows the example of a structure of a correction circuit. It is a figure which shows the example of a structure of a rattling correction process part. It is a figure for demonstrating the process of a rattling correction process part. It is a figure for demonstrating the process of a rattling correction process part. It is a figure which shows the example of the relationship between the number of black pixels, and the grayscale gradation. 6 is a flowchart illustrating an example of the overall processing flow of the image forming apparatus. It is a figure which shows the example of the relationship between the number of black pixels, and the grayscale gradation. It is a figure which shows the example of the relationship between the number of black pixels, and the grayscale gradation.

Explanation of symbols

1 Image forming device (image processing device)
23 Resolution conversion processing unit (second conversion means)
30a-30f 1st thru | or 6th rattling detection part (boundary pixel detection means)
31a to 31f First to sixth on-dot count units (gradation calculation means)
32a-32f 1st gradation calculation part (1st conversion means)
33 attention pixel gradation determination section (first conversion means)
34 Grayscale image generator (first conversion means)

Claims (7)

Boundary pixel detection means for detecting a boundary pixel that is a pixel in contact with both a white pixel group and a black pixel group from a binary image;
A gradation calculation means for obtaining a grayscale gradation of the boundary pixel based on the boundary pixel and surrounding pixels;
First conversion means for converting the binary image into a first grayscale image that is a grayscale image by correcting the value of the boundary pixel to the gradation obtained for the boundary pixel;
A second conversion means for converting the first grayscale image into a second grayscale image by performing a resolution conversion process for improving resolution;
An image processing apparatus comprising: The boundary pixel detection unit is configured such that pixels included in the binary image are in contact with a first line and a second line that are parallel to each other, and one of the first line and the second line. When the other pixels included in the line are all white and the other pixels included in the other line are all black, the pixel is detected as the boundary pixel,
The gradation calculation means obtains the gradation of the boundary pixel based on the number of black pixels included in a third line sandwiched between the first line and the second line.
The image processing apparatus according to claim 1. A plurality of the boundary pixel detection means, and each of the boundary pixel detection means detects the boundary pixels using the different first lines and the different second lines;
A plurality of the gradation calculation means are provided so as to correspond to the respective boundary pixel detection means, and each of the gradation calculation means corresponds to the floor of the boundary pixel detected by the corresponding boundary pixel detection means. Seeking key,
The first conversion unit is configured to convert the value of the boundary pixel detected by at least one of the plurality of boundary pixel detection units to the level corresponding to each of the boundary pixel detection units that detected the boundary pixel. Converting the binary image into the first grayscale image by converting to one of the gradations calculated by the tone calculation means or converting it to an average value of the gradations;
The image processing apparatus according to claim 2. At least one of the plurality of boundary pixel detection means detects the boundary pixel using two lines parallel to the main scanning direction as the first line and the second line, and at least one of the boundary pixel detection means Detecting the boundary pixel using two lines parallel to the scanning direction as the first line and the second line;
The image processing apparatus according to claim 3. Depending on the degree of improvement in the resolution in the resolution conversion process, all or part of the plurality of boundary pixel detection means detect the boundary pixels.
The image processing apparatus according to claim 3 or 4. In the image processing device,
Execute a process of detecting a boundary pixel that is a pixel in contact with both the white pixel group and the black pixel group from the binary image,
Performing a process for obtaining a grayscale gradation of the boundary pixel based on the boundary pixel and surrounding pixels;
Executing the process of converting the binary image into a first grayscale image that is a grayscale image by correcting the value of the boundary pixel to the gradation obtained for the boundary pixel;
Performing a process of converting the first grayscale image into a second grayscale image by performing a resolution conversion process for improving resolution;
An image conversion method characterized by that. In the image processing device,
Execute a process of detecting a boundary pixel that is a pixel in contact with both the white pixel group and the black pixel group from the binary image,
Performing a process for obtaining a grayscale gradation of the boundary pixel based on the boundary pixel and surrounding pixels;
Executing the process of converting the binary image into a first grayscale image that is a grayscale image by correcting the value of the boundary pixel to the gradation obtained for the boundary pixel;
Performing a process of converting the first grayscale image into a second grayscale image by performing a resolution conversion process for improving resolution;
A computer program characterized by the above.

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