JP7049292B2 - Image processing equipment, image processing methods and programs - Google Patents

Description

The present disclosure relates to an image processing apparatus, an image processing method and a program.

As a result of the widespread use of color printers and color scanners in recent years, there are increasing opportunities for color documents to be handled electronically. For example, a color image generated by scanning a color document with a scanner is stored as an electronic file or transmitted / received via a network such as the Internet. However, since the large data size of a full-color image puts pressure on the capacity of the storage device or puts a load on the network, it is often desired to reduce the data size.

Conventionally, as techniques for compressing the data size of a color image, so-called dithering including an error diffusion method, JPEG compression, and ZIP compression and LZW compression with color reduction (for example, to 8-bit palette color) are known. ..

Patent Document 1 discloses a method of reducing an input color image to generate an indexed color image and corresponding color information, integrating similar indexed colors, and compressing and encoding a binary image of the remaining indexed color. ing. Such a technique is also called minority color compression. The compression coding of the binary image can be performed according to a coding method such as MH (Modified Huffman), MR (Modified READ) or MMR (Modified MR).

Japanese Patent No. 3890250

When a document is scanned by a scanner, noise due to uneven reading may occur in the image. Temporary compression or quantization in the middle of image processing can also cause noise in the image. These noises reduce the compression efficiency of compression coding based on coding methods that seek to reduce the amount of information in image data, especially by relying on the correlation of pixel values between nearby pixels, or the reproducibility of image information. To reduce.

The technique according to the present disclosure aims to at least alleviate the above-mentioned drawbacks of the existing method.

From a certain point of view, it is color image data expressing a color image, and at least the color image data generated by scanning the image of the original is subjected to color reduction processing to obtain the colors contained in the color image. The color reduction unit that generates color reduction image data including a small number of colors and the color of the pixel determined to be the isolated point in the color reduction image data are converted to another color based on the color of the pixel adjacent to the isolated point. A conversion unit that executes a conversion process and a generation process that generates at least one binary image data, and a coding unit that compresses and encodes the generated binary image data, and includes colors of the adjacent pixels. In the case where the color of the adjacent pixel includes a non-background color that is not the background color of the image based on the color image data, the other color based on the above is the non-background color having the largest number among the colors of the adjacent pixel. When it is one color, it is the most numerous non-background color among the colors of the adjacent pixels, and in the other colors based on the colors of the adjacent pixels, the color of the adjacent pixels includes the non-background color. In the case, when there are two or more non-background colors having the largest number among the colors of the adjacent pixels, the darkest color among the two or more non-background colors or the most from the background color in the color space. An image processing device , which is a distant color, is provided. Corresponding methods and programs may also be provided.

According to the present disclosure, when compressing a color image containing noise, higher compression efficiency can be achieved or the reproducibility of image information can be improved.

The schematic diagram which shows an example of the structure of the image processing system which concerns on one Embodiment. The block diagram which shows an example of the specific structure of the MFP which concerns on one Embodiment. The block diagram which shows an example of the detailed structure of the data processing part of the MFP which concerns on one Embodiment. Explanatory drawing which shows an example of the state of color reduction in a color-reduced image. Explanatory drawing which shows an example of an isolated point. Explanatory drawing for explaining correction of the color of the isolated point which concerns on one Embodiment. Explanatory drawing for explaining correction of the color of the isolated point which concerns on one Embodiment. Explanatory drawing for explaining correction of the color of the isolated point which concerns on one Embodiment. Explanatory drawing for explaining correction of the color of the isolated point which concerns on one Embodiment. An explanatory diagram for explaining the generation of a binary image from a color-reduced image. Explanatory drawing which shows an example of the file format of the compressed data file which concerns on one Embodiment. The flowchart which shows an example of the schematic flow of the minority color compression processing which concerns on one Embodiment. The flowchart which shows an example of the detailed flow of the isolated point correction process which concerns on one Embodiment. The flowchart which shows an example of the detailed flow of the color selection process which concerns on 1st Embodiment. The flowchart which shows an example of the detailed flow of the color selection process which concerns on 2nd Embodiment. An explanatory diagram for explaining the handling of isolated points according to a modified example. A flowchart showing an example of a detailed flow of isolated point correction processing according to a modification.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. The following embodiments do not limit the invention according to the claims. Although a plurality of features are described in the embodiment, not all of the plurality of features are essential for the invention, and the plurality of features may be arbitrarily combined. Further, in the accompanying drawings, the same or similar configurations are given the same reference numbers, and duplicate explanations are omitted.

<< 1. First Embodiment >>
<1-1. Overall configuration>
This section describes an example in which the technology according to the present disclosure is applied to a digital multifunction device (Multi-Function Peripheral (MFP)). Hereinafter, the digital multifunction device is also simply referred to as a multifunction device. However, the technique according to the present disclosure is not limited to the multifunction device, and may be applied to any kind of image processing apparatus.

FIG. 1 is a schematic diagram showing an example of the configuration of the image processing system 1 according to the first embodiment. The image processing system 1 includes an MFP 101 and a personal computer (PC) 102. The MFP 101 and the PC 102 are connected to each other via the network 103.

As shown by the dotted line 104 in FIG. 1, the MFP 101 generates image data of the document 3 by scanning the image of the document (for example, a paper document) 3 set by the user. The user can input to the MFP 101, for example, the destination of transmission of image data (for example, PC102) and various settings related to scanning and transmission via the operation unit 203 described later of the MFP 101. The settings entered here are, for example, color mode (color / black and white), resolution, image data compression ratio, and compression method (eg, JPEG, TIFF, PDF, minority color compression, minority color compression with OCR results). Can include one or more of. In the following description, it is assumed that minority color compression is specified as the compression method. Further, as shown by the dotted line 105, the MFP 101 transmits the image data of the original document generated by the specified compression method to the specified destination according to the above-mentioned user setting. The PC 102 has, for example, a viewer capable of decompressing the received image data and restoring the image, and displays the image of the restored original 3 on the display.

<1-2. MFP configuration>
FIG. 2 is a block diagram showing an example of a specific configuration of the MFP 101 according to the first embodiment. Referring to FIG. 2, the MFP 101 includes a scanner unit 201, a printer unit 202, an operation unit 203, and a control unit 204.

The scanner unit 201 is an image input device that scans an image of a document and generates image data expressing the image of the document. That is, the scanner unit 201 has a role as an image reading unit. The scanner unit 201, for example, reads the image of the original as a color image or a black-and-white image according to the color mode set by the user. The scanner unit 201 may automatically determine the color mode to be applied. The scanner unit 201 transmits the image data of the scanned document to the control unit 204. The printer unit 202 is an image output device that receives image data from the control unit 204 and prints an image on a sheet based on the received image data. The operation unit 203 is a user interface that accepts the operation of the MFP 101 by the user and the input of information to the MFP 101. Further, the operation unit 203 outputs information related to the operation of the MFP 101 (for example, displayed on a display).

The control unit 204 is a controller for controlling all the functions of the MFP 101. Referring to FIG. 2, the control unit 204 includes a CPU 205, a RAM 206, an operation interface (I / F) 207, a network I / F 208, a ROM 210 and a storage unit 211, and these components are interconnected via the system bus 216. .. The CPU 205 is a processor that controls the entire MFP 101. The RAM 206 is a work memory that temporarily stores programs and data for the operation of the CPU 205. The RAM 206 is also an image memory for temporarily storing image data. The operation I / F 207 is an interface that mediates communication between the control unit 204 and the operation unit 203. For example, the operation I / F 207 transmits a user interface image to be displayed on the operation unit 203 to the operation unit 203. Further, the operation I / F 207 receives the information input by the user from the operation unit 203. The network I / F 208 is an interface for connecting the MFP 101 to the network 103. The network 103 may be, for example, a LAN (Local Area Network). The ROM 210 is a boot ROM, and stores the boot program of the MFP 101 and other computer programs in advance. The storage unit 211 may be a secondary storage device such as an HDD (Hard Disk Drive), and stores various software for system control, setting data, and image data.

Further, the control unit 204 includes an image bus I / F212, a raster image processor (RIP) 213, a device I / F214, and a data processing unit 215, and these components are interconnected via the image bus 217. The image bus I / F 212 is a bus bridge that connects the image bus 217 to the system bus 216, and converts the data structure of the image data between these buses. The RIP 213 interprets a page description language (PDL) code that describes the content of the image to be drawn, and executes a so-called rendering process that expands the content of the image into a bitmap image having a specified resolution. The device I / F 214 is connected to the scanner unit 201 and the printer unit 202 via the respective signal lines. The device I / F 214 converts, for example, a synchronous / asynchronous system of image data. The data processing unit 215 executes image processing on the image data received from the scanner unit 201 and image processing on the image data for printing transmitted to the printer unit 202. The image processing performed by the data processing unit 215 may include, for example, minority color compression. For example, when minority color compression is set as the compression method for the document to be scanned, the data processing unit 215 executes minority color compression on the image data generated by scanning the image of the original by the scanner unit 201. do. The compressed data generated as a result of the minority color compression is transmitted to a designated destination (for example, PC 102) via, for example, the network I / F 208 and the network 103. The data processing unit 215 can also decompress the compressed data received via the network I / F 208 and restore the original image data. The image data restored by the data processing unit 215 is transmitted to the printer unit 202 for printing via, for example, the device I / F 214. The details of the data processing unit 215 will be further described in the next section. The image bus 217 is a signal line for transferring image data at high speed. The image bus 217 may be, for example, a PCI bus or an IEEE1394 bus.

<1-3. Details of data processing unit>
As described above, the data processing unit 215 shown in FIG. 2 executes various image processing on the image data generated by scanning the image of the original and the received image data. In particular, in the present embodiment, when the input image is a color image, the data processing unit 215 compresses the image data of the color image by performing minority color compression according to the setting. FIG. 3 is a block diagram showing an example of a detailed configuration of the data processing unit 215. Referring to FIG. 3, the data processing unit 215 includes a color reduction unit 310, a conversion unit 320, a coding unit 340, and a data combining unit 350. In the following description, for the sake of simplicity, the image data representing the image may be simply referred to as an "image".

(1) Color reduction unit The color reduction unit 310 executes at least a color reduction process on the input color image 301 to generate a color reduction image 315 containing a smaller number of colors than the colors included in the input color image 301. As shown in FIG. 3, the color reduction unit 310 may include a color reduction processing unit 311, a color integration unit 312, and an intermediate color reduction unit 313. The color reduction processing unit 311 executes color reduction processing on the input color image 301. The color reduction process may typically be a process of converting an image expression from a so-called full color expression or a true color expression to an index color expression. The number of colors contained in the image (also referred to as an index color image) generated as a result of the color reduction processing is the upper limit number of index colors that can be stored in the color palette at most.

The color integration unit 312 and the intermediate color reduction unit 313 are components that reduce the number of colors according to the method disclosed in Japanese Patent No. 3890250. As shown by the broken line in the figure, each of the color integration unit 312 and the intermediate color reduction unit 313 does not necessarily have to be included in the color reduction unit 310. The color integration unit 312 is, for example, two colors of index colors that are determined to be substantially the same color (for example, a pair of colors in which the absolute value of the difference between the component values of R, G, and B is all below the threshold value). Integrate one into the other. The intermediate color reduction unit 313 derives a luminance component and two color difference components for each of the index colors, and integrates colors close to each other in the color difference plane. For example, when there is a multi-step gradation of gray between white and black at the edge of a character written in black on a white background, the neutral color reduction unit 313 changes gray close to white to white and close to black. Gray can be integrated into black respectively. As a result of these processes, the number of different colors contained in the color-reduced image 315 can be reduced to a smaller number than the number of colors in a typical color palette (eg, 256 colors). As an example, a color-reduced image based on scanning a document with printed black and red characters and content handwritten with blue ink has four index colors: black, red, blue, and white, regardless of shade of color. May include.

FIG. 4 is an explanatory diagram showing an example of a state of color reduction in a color-reduced image. The character 401 shown on the left side of FIG. 4 is an example of a black character included in the input color image 301. When only a simple color reduction process is performed on the input color image 301, a gradation of intermediate colors as shown in the center of FIG. 4 appears at the edge portion 402 of the character 401. Specifically, the pixel 403 shows black, the pixel 404 shows gray close to black, and the pixel 405 shows gray close to white. In such a situation, as a result of the color reduction unit 310 integrating colors and reducing intermediate colors, the index colors included in the edge portion 402 are only two colors, white and black, as shown on the right side of FIG.

The color reduction unit 310 generates color information 316 in addition to the color reduction image 315. The color information 316 includes pixel number data, color center of gravity data, and distribution range data for each of the index colors included in the color reduction image 315. The pixel number data represents the number of pixels indicating individual index colors in the color-reduced image 315. The color center of gravity data represents the color center of gravity (for example, R, G, B component values) of each index color. The distribution range data represents the distribution range in the image of the pixels showing the individual index colors by the position coordinates of the upper left corner and the position coordinates of the lower right corner of the smallest rectangle including those pixels. The color reduction unit 310 outputs the color reduction image 315 and the color information 316 to the conversion unit 320.

(2) Conversion unit In the existing method, a binary image corresponding to each index color is generated from the above-mentioned reduced color image 315, and the binary image is compressed and coded. As a result, the data size of the resulting compressed data is significantly reduced as compared with the case where the original input color image is compressed and encoded as it is. The compression coding of the binary image can be performed according to a coding method such as MH, MR or MMR. Existing coding methods for compressing binary images generally rely on the correlation of pixel values between neighboring pixels to achieve high compression efficiency. This means that the smaller the transition of pixel values (eg, true to false or false to true) between adjacent pixels, the smaller the data size of the compressed data. However, when a document is scanned by a scanner, noise due to uneven reading may occur in the image. Temporary data compression or quantization that can be performed by a device such as a scanner can also cause noise in the image. These noises appear in the binary image as isolated points, disturb the original correlation between nearby pixels, and reduce the compression efficiency of the binary image. Although it depends on the content of the document to be read, isolated points appeared at a rate of about 1 pixel in 4 to 5 characters in the sample case investigated by the inventor.

If the isolated points are erased from the binary image, the pixel values become flat in the region near the isolated points, so that the decrease in compression efficiency can be alleviated. However, uniformly eliminating isolated points can result in loss of reproducibility of document content and unintended changes or omissions in information (eg, characters or other structural information written in the document). Therefore, in the present embodiment, the conversion unit 320 prevents a decrease in compression efficiency or a decrease in information reproducibility by converting the color of isolated points in the image, as described in detail below.

In the present embodiment, the conversion unit 320 converts the color of the pixel determined to be an isolated point in the color-reduced image 315 into another color based on the color of the pixel adjacent to the isolated point, and at least one. Performs a generation process to generate two binary images. Adjacent pixels refer to eight pixels at the upper left, upper, upper right, left, right, lower left, lower, and lower right for non-boundary pixels that are not located at the boundary of the image. For boundary pixels, the number of adjacent pixels can be, for example, 5 or 3. The other colors may be non-background colors, depending on the predefined conditions. That is, in the present embodiment, the conversion unit 320 does not uniformly erase the isolated points (convert the color of the isolated points to the background color).

Typically, the conversion unit 320 may determine that a pixel showing a color different from all of the adjacent pixels is an isolated point. FIG. 5 is an explanatory diagram showing an example of isolated points. The color-reduced image 315 shown as an example in FIG. 5 shows red characters shown by shaded rectangles in the figure, black characters shown by filled rectangles, and handwritten parts with blue ink shown by broken lines. include. There is a black pixel 501 on the edge of one red character at the top of the image 315. If a black binary image is generated from the image 315 without converting the color of the black pixel 501, the black pixel 501 becomes an isolated point in the black binary image. The blue pixel 502 in the central white region of image 315 can also be an isolated point. Similarly, the red pixel 503 located at the edge of the black character at the bottom of the image 315 can also be an isolated point. The determination condition for determining that a pixel is an isolated point is not limited to the above-mentioned example. In one modification, the conversion unit 320 may determine that a pixel is an isolated point, even if the pixel exhibits the same color as some of the adjacent pixels. An example of such a modification will be further described later.

Referring to FIG. 3 again, the conversion unit 320 includes a background selection unit 321, an isolated point correction unit 322, and a binary image generation unit 323.

(2-1) Background selection unit The background selection unit 321 selects one of the colors (that is, the index color) included in the color-reduced image 315 as the background color. The background color is often the background color of the document being scanned. The background color may be recognized as, for example, the color represented by the most pixels in the color-reduced image or the color distributed in the widest range in the color-reduced image. The background selection unit 321 may select a background color that meets the above conditions based on one or both of the pixel value data and the distribution range data of the color information 316. As for the background color, the binary image may not be generated by the binary image generation unit 323 described later. Instead, the background selection unit 321 extracts the information corresponding to the selected background color from the color information 316 as the background color information 316-M, and outputs the extracted background color information 316-M to the data combination unit 350.

(2-2) Isolated point correction unit The isolated point correction unit 322 converts each of the pixels determined to be isolated points in the color-reduced image 315 from the color of the adjacent pixel adjacent to the isolated point (the color after conversion (2-2). Hereinafter, it is referred to as a selected color), and the color of the isolated point is corrected to the selected color. In the following description, the word "correction" is used with substantially the same meaning as "conversion". In the first embodiment, the isolated point correction unit 322 totals the number of adjacent pixels for each isolated point for each color, and selects the color having the largest total number of adjacent pixels as the selected color for the isolated point. It is also good.

6A to 6D are explanatory views for explaining the correction of the color of isolated points. It is assumed that white is selected as the background color through these figures. The * mark in the figure indicates an isolated point. In the example of FIG. 6A, the color of the isolated point 601 before modification is red. The color of the adjacent pixels on the upper left, upper, upper right, left and right of the isolated point 601 is white, and the color of the adjacent pixels on the lower left, lower and lower right is black. Therefore, the colors of the adjacent pixels (selection candidates) include white and black, the number of adjacent pixels of white is 5, and the number of adjacent pixels of black is 3. Therefore, the selected color is white, and the isolated point correction unit 322 corrects the color of the isolated point 601 to white.

In the example of FIG. 6B, the color of the isolated point 602 before modification is red. The color of the adjacent pixels on the upper left, upper and upper right of the isolated point 602 is white, and the color of the adjacent pixels on the left, right, lower left, lower and lower right is black. Therefore, the colors of the adjacent pixels (selection candidates) include white and black, the number of adjacent pixels of white is 3, and the number of adjacent pixels of black is 5. Therefore, the selected color is black, and the isolated point correction unit 322 corrects the color of the isolated point 602 to black.

In the second embodiment, when the color of the adjacent pixel includes the non-background color, the isolated point correction unit 322 may select the non-background color having the largest number of adjacent pixels to be aggregated as the selection color. On the left side of FIG. 6C, the isolated point 601 before modification and its adjacent pixels are shown again. The color of the adjacent pixel of the isolated point 601 includes black, which is a non-background color. There are no other non-background colors that have more adjacent pixels than black. Therefore, in this embodiment, unlike the example of FIG. 6A, the isolated point correction unit 322 corrects the color of the isolated point 601 to black. According to this embodiment, even if the color of the pixel at the edge of the character is recognized as a color different from the original color due to noise and becomes an isolated point, the pixel is not buried in the background. The color of the pixel can be modified to the same color as the adjacent pixel that appropriately belongs to the character.

In the third embodiment, the isolated point correction unit 322 corrects the color of the isolated point to the darkest color among the two or more colors when there are two or more colors having the largest number of adjacent pixels. You may. In the example of FIG. 6D, the color of the isolated point 603 before modification is red. The color of the adjacent pixels on the upper left, upper, upper right, and right of the isolated point 603 is white, and the color of the adjacent pixels on the left, lower left, lower, and lower right is black. Therefore, the colors of the adjacent pixels (selection candidates) include white and black, and the number of adjacent pixels of white and the number of adjacent pixels of black are both four. Therefore, the isolated point correction unit 322 selects the darkest black color among white and black as the selection color for correcting the isolated point 603. The determination of color darkness may be made, for example, by comparing the values of lightness or luminance. When the background color is not white, the color farthest from the background color in the color space may be selected from the candidates instead of the darkest color. According to this embodiment, it is possible to increase the possibility of correction so that the color of isolated points becomes clear and prevent the loss of information in the image.

The third embodiment may be combined with the second embodiment described above. In that case, when there are two or more non-background colors having the largest number of adjacent pixels, the color of the isolated point can be corrected to the darkest non-background color among the two or more non-background colors.

In the present embodiment, the isolated point correction unit 322 sets index colors other than the background color included in the color reduction image 315 as processing targets in ascending order of the number of pixels, and corrects the colors of the isolated points indicating each index color. You may. In the following description, each index color is also referred to as a layer. In the example of image 315 of FIG. 5, the number of pixels indicating blue is the smallest, the number of pixels indicating red is the next smallest, followed by black. White is the background color. Therefore, the isolated point correction unit 322 first corrects the color of the isolated point (isolated point indicating blue) belonging to the blue layer. This modification can increase the number of red pixels, black pixels, and white pixels, and some isolated points of the layer to be processed after that can be non-isolated points. Next, the isolated point correction unit 322 corrects the color of the isolated point belonging to the red layer. This modification may increase the number of blue pixels, black pixels, and white pixels, and the isolated point of the layer to be processed next may be a non-isolated point. Next, the isolated point correction unit 322 corrects the color of the isolated point belonging to the black layer. According to this order of processing, the isolated points of non-dominant colors (colors with a smaller number of pixels) due to minute noise are changed to more dominant colors, and the isolated points of the layer of the more dominant color are eliminated as much as possible. After that, the color correction can be properly performed for the isolated points that still remain.

When the isolated point correction unit 322 corrects the color of the isolated point, the isolated point correction unit 322 updates the color information 316 based on the correction.

(2-3) Binary image generation unit The binary image generation unit 323 divides the color-reduced image 315 whose pixel value is corrected by the isolated point correction unit 322, so that the binary image corresponding to each of the non-background colors is obtained. To generate. FIG. 7 is an explanatory diagram for explaining the generation of a binary image from a color-reduced image. In contrast to the example of FIG. 5, in the example of FIG. 7, isolated points are eliminated as a result of color correction. The binary image generation unit 323 generates a red binary image 355-1, a black binary image 335-2, and a blue binary image 335-3 from the reduced color image 315. The red binary image 335-1 has a size corresponding to the distribution range of the red pixels in the color-reduced image 315, and the pixel value “1 (true)” is set in the red pixels and the pixel value “0 (”” in the other pixels. False) ”is shown. The black binary image 335-2 has a size corresponding to the distribution range of black pixels in the color-reduced image 315, and has a pixel value of “1 (true)” in the black pixels and a pixel value of “0 (” in the other pixels. False) ”is shown. The blue binary image 335-3 has a size corresponding to the distribution range of the blue pixels in the color-reduced image 315, and has a pixel value “1 (true)” in the blue pixels and a pixel value “0 (”” in the other pixels. False) ”is shown. The color of the pixel that does not show true in any binary image is the background color, and the background color is represented by the color center of gravity data of the background color information 316-M. In the example of FIG. 7, the background color is white. The size of each binary image may be the same as that of the color-reduced image 315 without being limited to the above-mentioned example.

The binary image generation unit 323 transfers one or more binary images 335-1, ..., N and the color information 316-1, ..., N of the non-background color to the coding unit 340. Output.

Here, an example in which the binary image generation unit 323 generates a binary image for each color after the isolated point correction unit 322 corrects (or converts) the color of the isolated point in the color-reduced image has been mainly described. However, the order of the correction process (conversion process) and the binary image generation process is not limited to the above-mentioned example. For example, the conversion unit 320 converts the color of the isolated point by switching the pixel value of the provisional binary image at the position corresponding to the isolated point in the color-reduced image after generating the provisional binary image from the color-reduced image. , A converted binary image may be generated. More specifically, the conversion unit 320 switches the pixel value of the binary image of the color before conversion from true to false, and switches the pixel value of the binary image of the color after conversion from false to true. The color of isolated points can be converted. In this case, the isolated point may correspond to, for example, a pixel indicating true in a binary image, and all (or almost) adjacent pixels indicating false.

(3) Coding unit The coding unit 340 compresses and encodes each of the binary images 335-1, ..., N input from the conversion unit 320 to generate compressed image data. The size of each binary image 335-1, ..., N is indicated by the distribution range data of the color information 316-1, ..., N. The compression coding here may be based on any existing coding method such as MH, MR or MMR. The coding unit 340 generates compressed data 345-1, ..., N including compressed image data generated by compression coding and corresponding color information for each of the non-background colors. Then, the coding unit 340 outputs the generated compressed data 345-1, ..., N to the data combining unit 350.

(4) Data combining unit The data combining unit 350 generates a compressed data file 355 by combining header data with the compressed image data input from the encoding unit 340. FIG. 8 is an explanatory diagram showing an example of a file format of a compressed data file that can be generated by the data combining unit 350. Referring to FIG. 8, the compressed data file 355 includes a header area 801 and N data areas 802-1, ..., N.

The header area 801 may include the attribute data of the scanned document and the background color information input from the conversion unit 320. The document attribute data may include, for example, the size of the input color image 301 (number of pixels in the vertical and horizontal directions) and scan-related setting values (eg, resolution and compression method). The background color information may include color centroid data representing the background color. As mentioned above, the background color can be the color having the largest number of pixels or the color occupying the widest range in the image. For example, if a document with content printed on red paper is scanned, red may usually be selected as the background color. However, since white paper is used in many cases, the data combining unit 350 does not have to include the background color information in the compressed data file when it is determined that the background color is white. An example of a method for determining whiteness is disclosed in Japanese Patent No. 3890250.

The i-th data area 802-i (i = 1, ..., N) includes the i-th non-background color color information and compressed image data. Assuming that the number of index colors remaining in the color-reduced image 315 is M, the number N of the data area 802 is equal to M-1. That is, the data area 802 can be repeated by the number N of non-background colors. When the input color image 301 is a monochromatic image (for example, when a blank document is scanned), N = 0, and the compressed data file 355 does not have to include the data area 802. When the input color image 301 is a black and white image, N = 1, and the compressed data file 355 may include only a single data area 802.

<< 2. Example of processing flow >>
<2-1. General flow>
FIG. 9 is a flowchart showing an example of a schematic flow of the minority color compression process executed by the data processing unit 215 of the control unit 204 in the present embodiment. In the following description, the processing step is abbreviated as S (step).

First, in S910, the color reduction unit 310 executes color reduction processing on an input color image (color image data expressing a color image) to generate an indexed color image and corresponding color information.

Next, in S920, the color reduction unit 310 integrates the index colors that are determined to be substantially the same color based on the comparison of the values of the color centers of gravity. The color reduction unit 310 updates the color information by recalculating the number of pixels, the color center of gravity, and the distribution range for the indexed colors to be integrated.

Next, in S930, the color reduction unit 310 derives the values of the luminance component and the two color difference components corresponding to the respective index colors, and reduces the intermediate color based on the comparison of the component values. The color reduction unit 310 updates the color information by recalculating the number of pixels, the color center of gravity, and the distribution range of each indexed color according to the reduction of the intermediate colors. As a result of S910 to S930, a color-reduced image (color-reduced image data) including a smaller number of colors than the colors included in the input color image is generated from the input color image.

Next, in S940, the conversion unit 320 selects a background color from the index colors included in the color-reduced image, and extracts the background color information from the color information.

Next, in S950, the conversion unit 320 converts the color of the isolated point in the color-reduced image into another color based on the color of the pixel adjacent to the isolated point by executing the isolated point correction process. The details of the isolated point correction process executed here will be further described later.

Next, in S970, the conversion unit 320 generates a binary image (binary image data) corresponding to each of the non-background colors from the converted color-reduced image.

Next, in S980, the coding unit 340 compresses and encodes each of the generated binary images to generate compressed image data. The coding unit 340 may further generate compressed data including compressed image data and color information.

Next, in S990, the data combining unit 350 generates a compressed data file by combining the header data including the background color information with the compressed data generated by the encoding unit 340.

The compressed data file generated as a result of such a minority color compression process can be transmitted, for example, to a destination specified by the user via the network 103.

The receiving device that has received the compressed data file draws the entire image area with, for example, the color indicated by the background color information in the header area (or the default background color that is, for example, white). Further, the receiving device overwrites the indexed color image on the image area based on the binary image restored by decompressing the compressed image data in each data area. As a result, the color-reduced image can be restored in the receiving device. The color-reduced image may be stored in a storage medium, displayed on a display, or printed by a printer.

<2-2. Isolated point correction process>
FIG. 10 is a flowchart showing an example of a detailed flow of the isolated point correction process shown in S950 of FIG. The isolated point correction process can be executed by the conversion unit 320 as described above.

First, in S951, the conversion unit 320 sets the layer of the color having the smallest number of pixels among the unprocessed layers (other than the background color) as the layer of interest based on the pixel number data of the color information.

Next, in S952, the conversion unit 320 sets one pixel of the attention layer (a pixel indicating the color of the attention layer in the color-reduced image) as the attention pixel. For example, the conversion unit 320 may set the pixels of interest in the so-called raster scan order. However, the order of selecting the pixels of interest is not limited to this example.

Next, in S953, the conversion unit 320 determines whether the pixel of interest is an isolated point based on the pixel value of the adjacent pixel adjacent to the pixel of interest. Typically, the conversion unit 320 may determine that the pixel of interest is an isolated point when the pixel of interest exhibits a different color than all of the adjacent pixels. Here, if it is determined that the pixel of interest is an isolated point, the process proceeds to S954. If not, the process proceeds to S960.

In S954, the conversion unit 320 selects a color for conversion from the colors of the adjacent pixels of the pixel of interest, which is an isolated point, by executing the color selection process. The selected color here can be a non-background color, depending on the predefined conditions. 11A and 11B show an example of a detailed flow of the color selection process according to the first embodiment and the second embodiment described above, respectively.

In the first embodiment, as shown in FIG. 11A, in S955, the conversion unit 320 selects the color having the largest number of corresponding adjacent pixels among the colors of the adjacent pixels, and whether or not the color is the background color. Regardless, it is selected as the selected color.

In the second embodiment, as shown in FIG. 11B, first, in S956, the conversion unit 320 determines whether all the colors of the adjacent pixels are the background colors. When all the colors of the adjacent pixels are the background colors, in S957, the conversion unit 320 selects the background color as the selection color. If this is not the case, in S958, the conversion unit 320 selects the non-background color having the largest number of corresponding adjacent pixels among the colors of the adjacent pixels as the selection color. In any of the embodiments, if there are two or more colors having the largest number of corresponding adjacent pixels, the darkest color among those colors may be selected.

Returning to FIG. 10, in S959, the conversion unit 320 corrects (that is, converts) the color of the pixel of interest to the selected color selected in S954. The conversion unit 320 updates the color information according to this modification.

In S960, the conversion unit 320 determines whether or not pixels to be processed remain in the layer of interest. If there are no pixels remaining to be processed, the process proceeds to S961. On the other hand, when the pixel to be processed remains, the processing returns to S952.

In S961, the conversion unit 320 determines whether or not the layer to be processed remains. If there are no layers left to be processed, the isolated point correction process ends. If the layer to be processed remains, the process returns to S951.

Although an example of selecting layers (each of the reduced colors) in ascending order of the number of pixels and proceeding with color conversion of isolated points has been described here, the present embodiment is not limited to such an example. Layers may be selected in other order (eg, in descending order of pixel count or in order of index list). Also, the color conversion of isolated points may be performed after the generation of the binary image.

As described above, according to the present embodiment, at least the color reduction process is executed for the input color image, and the color of the pixel determined to be the isolated point in the reduced color image is based on the color of the pixel adjacent to the isolated point. Converted to other colors. Then, at least one binary image based on the conversion is compressed and coded by a coding method suitable for the binary image such as MMR. Therefore, even when reading unevenness or noise due to some image processing is present in the input color image, it is possible to correct the disorder of the correlation of the pixel values caused by the noise and achieve high compression efficiency. As a result, the file size of the compressed data file stored by the image processing device such as the MFP 101 or communicated with other devices is suppressed to a small size. Further, since the color of the isolated point is converted to the selected color that is adaptively selected, the deterioration of the reproducibility of the image information is prevented.

Further, according to the present embodiment, the color of the isolated point can be converted into the non-background color among the colors of the adjacent pixels, depending on the predetermined conditions. Therefore, instead of uniformly eliminating isolated points, the isolation of non-background color pixels can be eliminated, effectively avoiding unintended changes or omissions in the information contained in the scanned document. be able to.

According to one embodiment, the colors of isolated points can be converted into the color having the largest number of adjacent pixels aggregated for each color. In this case, the color of the isolated point generated by noise in the small area where the non-background color is predominant can be converted into the predominant non-background color without assimilating it into the background, and the image information can be left. According to another embodiment, the color of isolated points can be converted to the non-background color having the largest number of adjacent pixels when the color of one or more adjacent pixels is a non-background color. In this case, the color of an isolated point generated at the edge of a certain color region (for example, the edge portion of a character) is appropriately changed to the color of the isolated point even if the majority around the isolated point is the background color. It can be restored.

<< 3. Modification example >>
The present invention is not limited to the above embodiment, and various modifications are possible. For example, in the above embodiment, an example in which a pixel showing a color different from all of the adjacent pixels is treated as an isolated point has been mainly described. However, the noise for which the color should be corrected does not necessarily appear only in a single pixel, but may appear across a plurality of pixels. In order to deal with such a possibility, as a modification, the conversion unit 320 has a pixel group of the same color adjacent to each other, and each pixel in the pixel group whose number of pixels in the group is less than the threshold is an isolated point. If there is, it may be further determined. The threshold value here is an integer of 2 or more. The threshold may be fixedly defined or dynamically set depending on user settings or document attributes. An example will be described below in which each pixel of two or less pixels of the same color adjacent to each other is treated as an isolated point because the threshold value is equal to 3.

FIG. 12 is an explanatory diagram for explaining the handling of isolated points in this modified example. In the example of FIG. 12, it is assumed that the red layer is the layer of interest in the isolated point correction process. The pixel of interest 1201 before modification is red. The seven adjacent pixels of the upper left, upper, upper right, left, right, lower and lower right of the pixel of interest 1201 are not red, and the adjacent pixel 1202 at the lower left is red. Here, for convenience of explanation, the adjacent pixels 1202 are referred to as accompanying pixels of the pixel of interest 1201. Focusing on the accompanying pixel 1202, the seven adjacent pixels on the upper left, upper, left, right, lower left, lower and lower right of the accompanying pixel 1202 before modification are not red, and the adjacent pixel 1201 on the upper right is red. Therefore, in this modification, the conversion unit 320 determines that both the attention pixel 1201 and the accompanying pixel 1202 are isolated points. This is because the pixel of interest 1201 and the accompanying pixel 1202 form two pixel groups of the same color. Therefore, the conversion unit 320 selects, for example, black from the colors of the eight adjacent pixels of the pixel of interest 1201, and corrects the color of the pixel of interest 1201 to black. Similarly, the conversion unit 320 selects, for example, white from the colors of the eight adjacent pixels of the accompanying pixel 1202, and corrects the color of the accompanying pixel 1202 to white. The selected color here may be selected according to any of the first, second and third embodiments described above.

FIG. 13 is a flowchart showing an example of a detailed flow of the isolated point correction process according to the present modification.

First, in S1301, the conversion unit 320 sets the layer of the color having the smallest number of pixels among the unprocessed layers (other than the background color) as the layer of interest based on the pixel number data of the color information.

Next, in S1302, the conversion unit 320 sets one pixel of the attention layer as the pixel of interest. For example, the conversion unit 320 may set the pixels of interest in the so-called raster scan order. However, the order of selecting the pixels of interest is not limited to this example.

Next, in S1303, the conversion unit 320 determines whether or not the number of adjacent pixels having the same color as the pixel of interest among the adjacent pixels adjacent to the pixel of interest is one or less. Here, if the number of adjacent pixels having the same color as the pixel of interest is one or less, the process proceeds to S1304. If this is not the case, the pixel of interest is not an isolated point, and the process proceeds to S1312.

In S1304, the conversion unit 320 determines whether the number of adjacent pixels having the same color as the pixel of interest is equal to zero. When the number of adjacent pixels having the same color as the pixel of interest is equal to zero, the process proceeds to S1305. If not, the process proceeds to S1307.

In S1305, the conversion unit 320 selects a color for conversion from the colors of the adjacent pixels of the pixel of interest by executing the color selection process. The selected color here can be a non-background color, depending on the predefined conditions. The flow of the color selection process may be the same as the flow described with reference to FIGS. 11A and 11B. Next, in S1306, the conversion unit 320 corrects (that is, converts) the color of the pixel of interest to the selected color selected in S1305.

When the processing proceeds to S1307, there is one adjacent pixel having the same color as the pixel of interest, that is, one accompanying pixel. In S1307, the conversion unit 320 determines whether the number of adjacent pixels having the same color as the accompanying pixel and adjacent to the accompanying pixel is one or less. When the number of such adjacent pixels is one or less, the pixel of interest and the accompanying pixel form two pixel groups of the same color, and are therefore treated as isolated points. In this case, the process proceeds to S1308. If this is not the case, since the pixel of interest and the accompanying pixel are included in a group of three or more pixels of the same color, it is determined that these pixels are not isolated points, and the process proceeds to S1312.

In S1308, the conversion unit 320 selects a color for conversion from the colors of the adjacent pixels of the pixel of interest by executing the color selection process. The selected color here can be a non-background color, depending on the predefined conditions. Next, in S1309, the conversion unit 320 corrects (that is, converts) the color of the pixel of interest to the selected color selected in S1308.

Next, in S1310, the conversion unit 320 selects a color for conversion from the colors of the adjacent pixels of the accompanying pixel by executing the color selection process. The selected color here can be a non-background color, depending on the predefined conditions. Next, in S1311, the conversion unit 320 corrects (that is, converts) the color of the accompanying pixel to the selected color selected in S1310.

In S1312, the conversion unit 320 determines whether or not the pixel to be processed remains in the layer of interest. If there are no pixels remaining to be processed, the process proceeds to S1313. On the other hand, when the pixel to be processed remains, the processing returns to S1302.

In S1313, the conversion unit 320 determines whether or not the layer to be processed remains. If there are no layers left to be processed, the isolated point correction process ends. If the layer to be processed remains, the process returns to S1301.

According to this modification, when reading unevenness or noise due to some image processing occurs across a plurality of pixels, the colors of those pixels can be corrected based on the colors of adjacent pixels. As a result, it is possible to prevent a decrease in the reproducibility of the image information while reducing the decrease in the compression efficiency due to the noise.

In this specification, an example of converting the color of isolated points in an image of a document read by a scanner has been mainly described. However, the embodiments described above are also applicable to other types of color images. For example, the embodiments described above may also be applied to compression coding of photographic images. Further, the technique according to the present disclosure may be utilized by an image processing apparatus that performs arbitrary image processing that may cause noise in the image.

<< 4. Other embodiments >>
INDUSTRIAL APPLICABILITY The present invention supplies a program that realizes one or more functions of the above-described embodiment to a system or device via a network or storage medium, and one or more processors in the computer of the system or device reads the program. It can also be realized in the form of processing to be executed. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

The present invention is not limited to the embodiments described above, and various modifications and modifications can be made without departing from the spirit and scope of the invention. Therefore, a claim is attached to publicize the scope of the invention.

101: Multifunction device, 201: Scanner unit (image reader), 204: Control unit, 301: Input color image, 310: Color reduction unit, 315: Color reduction image, 320: Conversion unit, 335-1, ..., N: Two Value image, 340: Encoding unit

Claims (8)

Color image data expressing a color image , which is generated by scanning the image of the original, is subjected to at least color reduction processing to produce a smaller number of colors than the colors contained in the color image. A color reduction part that generates color reduction image data including
A conversion process for converting the color of a pixel determined to be an isolated point in the color-reduced image data to another color based on the color of a pixel adjacent to the isolated point, and a generation process for generating at least one binary image data. And the converter that executes
A coding unit that compresses and encodes the generated binary image data,
Equipped with
The other color based on the color of the adjacent pixel is the largest number among the colors of the adjacent pixel when the color of the adjacent pixel includes a non-background color that is not the background color of the image based on the color image data. When the number of non-background colors is one, it is the non-background color having the largest number among the colors of the adjacent pixels.
The other colors based on the colors of the adjacent pixels are when the colors of the adjacent pixels include the non-background color, and when two or more non-background colors having the largest number among the colors of the adjacent pixels are present. Is the darkest of the two or more non-background colors or the color farthest from the background color in the color space.
Image processing device. The image processing apparatus according to claim 1 , wherein the conversion unit generates the binary image data for each non-background color included in the reduced color image data. The image processing apparatus according to claim 1 or 2 , wherein the background color is a color represented by the most pixels in the color-reduced image data, or a color distributed in the widest range in the color-reduced image data. Image processing device. The image processing apparatus according to any one of claims 1 to 3 , wherein the conversion unit determines that a pixel showing a color different from all of the adjacent pixels is an isolated point. The image processing apparatus according to claim 4 , wherein the conversion unit sets each pixel in the pixel group, which is a group of pixels of the same color adjacent to each other and whose number of pixels in the group is lower than the threshold value, at the isolated point. An image processing device that further determines that it exists. The image processing apparatus according to any one of claims 1 to 5 , further comprising an image reading unit that scans an image of the original and generates the color image data. An image processing method executed by an image processing device.
Color image data expressing a color image , which is generated by scanning the image of the original, is subjected to at least color reduction processing to produce a smaller number of colors than the colors contained in the color image. To generate decolorized image data including
A conversion process for converting the color of a pixel determined to be an isolated point in the color-reduced image data to another color based on the color of a pixel adjacent to the isolated point, and a generation process for generating at least one binary image data. And to do
Compressing and coding the generated binary image data and
Including
The other color based on the color of the adjacent pixel is the largest number among the colors of the adjacent pixel when the color of the adjacent pixel includes a non-background color that is not the background color of the image based on the color image data. When the number of non-background colors is one, it is the non-background color having the largest number among the colors of the adjacent pixels.
The other colors based on the colors of the adjacent pixels are when the colors of the adjacent pixels include the non-background color, and when two or more non-background colors having the largest number among the colors of the adjacent pixels are present. Is the darkest of the two or more non-background colors or the color farthest from the background color in the color space.
Image processing method. The processor of the image processing device,
Color image data expressing a color image , which is generated by scanning the image of the original, is subjected to at least color reduction processing to produce a smaller number of colors than the colors contained in the color image. A color reduction part that generates color reduction image data including
A conversion process for converting the color of a pixel determined to be an isolated point in the color-reduced image data to another color based on the color of a pixel adjacent to the isolated point, and a generation process for generating at least one binary image data. And the converter that executes
A coding unit that compresses and encodes the generated binary image data,
It is a program to function as
The other color based on the color of the adjacent pixel is the largest number among the colors of the adjacent pixel when the color of the adjacent pixel includes a non-background color that is not the background color of the image based on the color image data. When the number of non-background colors is one, it is the non-background color having the largest number among the colors of the adjacent pixels.
The other colors based on the colors of the adjacent pixels are when the colors of the adjacent pixels include the non-background color, and when two or more non-background colors having the largest number among the colors of the adjacent pixels are present. Is the darkest of the two or more non-background colors or the color farthest from the background color in the color space.
Program .

Images