JPH0467669B2 - - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a color image processing device for efficiently creating special image information in a colored block format, which has a small amount of data.

[Conventional technology]

In recent years, systems and services that use color still images, such as videotex, teletext, and CD subcode, have been increasing. The images used for these have a special structure called colored block format,
Color images are expressed with a relatively small amount of data, which is advantageous for storage and transmission. Figure 4 is a diagram for explaining the colored block format, in which figure a is an example of a color image with a structure suitable for the colored block format, and figures b and c are images expressing images in the colored block format. This is an example of information. In FIG. 4a, the minimum rectangle represents a pixel, and the type of color each pixel has is represented using hatching or the like. Here, the image is a rectangular block of a predetermined size (4 x 4 pixels in the example, hereinafter referred to as a "colored block").
), and restrictions are placed on coloring in units of colored blocks. That is, it is not possible to freely color each pixel, and the number of types of colors included in a colored block is limited to two or less. Therefore, such an image includes information indicating the values of two or less colors included in each colored block as shown in FIG.
It can be expressed by a binary value (hereinafter referred to as the Y value) that specifies which color to use among the colors below the species. FIGS. 4b and 4c show image information corresponding to the uppermost colored block row of the color image shown in FIG. 4a. For example, in the second colored block from the left,
A Y value is given to each of the 16 pixels, with the Y value representing color value A being 0 and the Y value representing color value B being 1. If only one color is included, like the colored block on the leftmost side, the Y value corresponding to that color can be either 0 or 1, and as in the example, the Y value of 0 and the color value A can be either 0 or 1. As long as they correspond, any color value may correspond to the other Y value of 1. In FIG. 4c, this is marked as X (don't care). Furthermore, the color value is often not a value that directly represents a color, but a value that indicates the number of a color in a predetermined set of colors. Color image is the 4th
When expressed using image information as shown in Figures b and c, the amount of data is extremely small compared to expressions that specify the color value of each pixel one by one. Since the value of can also be compressed by encoding, it is suitable for transmitting and storing color images.

However, because of the special image structure described above, it is not easy to create image information in the form of colored blocks. FIG. 16 is a block diagram showing an example of the configuration of a conventional apparatus for creating image information in a colored block format. 36 is a coloring specification section that specifies coloring in units of colored blocks; 7 is an information extraction section that extracts image information from an image that conforms to the colored block format.

Using such a device, an operator creates image information using the following procedure. First, a black and white binary image is input to the apparatus using the image input section 1. A binary image correction unit 35 having a display function and a figure drawing function performs additional drawing and corrected drawing of figures on this input image to create a desired binary image. Next, the coloring designation section 36 colors the binary image by designating the color to be given to pixels with a value of 0 and the color to be given to pixels with a value of 1 in units of coloring blocks. The operator determines whether the shape of the image as a result of coloring is good or bad. If it is not possible to color the block while maintaining the shape of the elemental figures that make up the image unless more than two colors are specified in the block, the binary image itself is corrected again by the binary image correction unit 35. . From the color image thus created, the information extraction section 7 automatically extracts image information in a colored block format consisting of the Y value, that is, the corrected binary image, and two or less color values in units of colored blocks. A typical system configuration of such a conventional image information creation device includes an image scanner as the image input section 1 and a color graphics function (including image memory) as the other parts.
This is a personal computer as an information processing device.

[Problem that the invention seeks to solve]

However, with conventional image information creation devices such as those described above, the operator is involved in most of the entire processing process, from correcting the binary image to specifying coloring, which is extremely labor-intensive and time-consuming. There was a problem that the cost increased. Additionally, in order to reduce the amount of correction operations for the above-mentioned binary image, a full-time designer who has mastered the colored block format is required to input a binary image so that the colored block contains only two or fewer colors from the beginning. As a result, the production cost increased.

This invention was made to solve the above-mentioned problems, and by automatically converting a given color image into image information in the form of colored blocks, it does not require much manpower and the information creation time is reduced. It is an object of the present invention to provide a color image processing device that enables efficient image creation in a short time.

[Means for solving problems]

A color image processing device according to the present invention includes an image memory that stores input color image information, and an information processing device that processes the color image information stored in the image memory. The processing device includes a color number detecting means for dividing the color image information stored in the image memory into blocks each consisting of a predetermined number of pixels and detecting the number of colors included in each block; About color blocks
The frequency of appearance of each color included in this multicolor block is counted, the presence or absence of the same color in blocks adjacent to this multicolor block is detected, and two priority colors are selected based on this detection result and the frequency of appearance of each color. A pixel color that is selected and changes each pixel in the multicolor block that has a color different from the two prioritized colors to the color that appears more frequently among the two prioritized colors in pixels surrounding the pixel. a statistical measuring means for detecting the frequency with which the large area colors are adjacent to each other with respect to large area colors occupying a large number of pixels in a color image; a large-area color determining means for determining a large area color; and a correspondence determining means for associating a binary value indicating the color type of the pixel with each pixel in the block for each block after the change by the pixel color changing means. The selection of the two priority colors is performed by selecting a color whose appearance frequency exceeds the first threshold value, and if three or more colors are selected as a result, a second color having a frequency higher than the first threshold value is selected. Select a color that has an appearance frequency exceeding a threshold value or exists in an adjacent block, and if three or more colors are selected as a result, select a color that has an appearance frequency that exceeds the second threshold value. , Furthermore, if three or more colors or less than one color are selected as a result, the two colors with the highest frequency of appearance are selected, and the binary values of each pixel are mapped. For blocks that include a large-area color, a binary value is associated with the large-area color using the value determined by the large-area color determining means, and for blocks that cannot be associated with this, a binary value is already assigned. Detects whether or not it contains the same color as the adjacent block whose correspondence with the value of It is detected whether a connection request to be associated is consistent with multiple adjacent blocks, and if there is no conflict, the connection request is matched to match the connection request, and if there is a conflict, the connection request is This is done by matching the connection request with the highest priority according to a predetermined priority order for each type, and converting the color image information stored in the image memory into a binary value for each pixel. and information indicating two or less types of color values in block units are converted into image information in which they are associated with each other.

[Effect]

The image processing device according to the present invention divides a color image created and inputted into colored blocks regardless of the coloring block format, detects the number of types of colors contained in each colored block, and detects the number of types of colors contained in each colored block. Change the necessary pixel colors within the colored block so that there are no more than 2 types of pixels, and then change the values of 2 types to the 2 or less colors included in the colored block as a large area color. This system automatically performs a series of processes in which allotment is performed in consideration of predetermined values.

As a result, color image information not based on the colored block format is converted to image information in the colored block format consisting of binary values for each pixel and information indicating color values for each colored block.

[Embodiments of the invention]

An embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 is a functional block diagram showing the configuration of an embodiment of the present invention, in which 1 is an image input unit for inputting a color image to be processed, and 2 is a color unit for detecting the number of types of colors in a colored block. 3 is a pixel color changing unit that is a pixel color changing means for changing the pixel color of a colored block containing more than two types of colors; 4 is a color number detecting unit that is a color number detecting unit; 5 is a color image statistical measurement unit serving as a statistical measurement means for measuring the proportion of pixels occupied and the degree to which pixels of various colors and pixels of other colors are adjacent on a color image from information on color types included in each colored block; A large-area color determining unit 6 is a large-area color determining unit that determines the Y value to be associated with a color that occupies a large proportion of the total number of pixels (hereinafter referred to as a large-area color); a correspondence determining unit serving as a correspondence determining means for associating Y values with two or less types of colors; 7;
is an information extraction unit that extracts image information in the form of colored blocks from the processed image.

FIG. 2 is a system configuration diagram showing the system configuration of the embodiment shown in FIG. 1 above. 1 in the diagram is color
A color image input device such as a TV camera or a color scanner; 8 is an image memory that stores color images;
9 is a central processing unit such as a microprocessor, 1
0 is a program memory that stores programs for the central processing unit 9, and 11 is a working memory that stores data generated during processing. Of these, 9 to 11 correspond to a computer M as a normal information processing device such as a microcomputer, and the components 2 to 7 shown in FIG. 1 are realized thereby.

Next, the operation of the image processing apparatus in the above embodiment will be explained. The color image input by the color image input device 1 is stored in the image memory 8, and the central processing unit 9 becomes in a state where the values of pixels at arbitrary positions can be read out or changed. In this state, first, the color number detection unit 2 controls the pixel readout position from the image memory 8, sequentially reads out the 4×4 pixels forming each colored block, and detects the number of color types of the pixels included therein. Detect. Next, for each colored block containing more than two types of colors, the pixel color changing section 3 changes the colors of a small number of pixels in the colored block so that the colors become two or less types.

FIG. 3 is a flowchart showing this specific method. In step 12, the color values of the pixels forming each colored block are sequentially read out, and the frequency of appearance of each color is counted by the central processing unit 9, thereby creating a table of color types and their frequencies for each colored block. It is stored in the working memory 11. Next, with reference to this color table, for colored blocks containing more than two colors, the number of colors is narrowed down to two. First, in step 13, it is detected whether the same type of color as the color included in the colored block is also present in an adjacent colored block. Then, in step 14, two colors to be left preferentially are selected in a predetermined manner based on this detection result and the appearance frequency of the previously detected color. That is, among more than two types of colors, colors whose appearance frequency is less than or equal to the first threshold value _T1 are excluded. If you cannot narrow it down to two types or less, first exclude colors that do not exist in adjacent blocks with an appearance frequency less than or equal to the second threshold T ₂ (T ₂ is greater than T ₁ ), and still reduce the number to two or less. If not, all colors below the threshold T ₂ are excluded. Furthermore, if more than two colors remain, or if too many colors are excluded (first
(including when excluding colors below the threshold T of ₁ ),
Select the two colors that appear most frequently. Colors other than the two or less colors selected in this way are erased from the color table, and pixels with that color are erased from the selected color (if there are two colors, then the selected color) in the colored block. either). In this change, the central processing unit 9 examines the surrounding pixels of the pixel whose color should be changed within the colored block, and changes the pixel to the same color as the color that appears more frequently in the surrounding pixels.

By the above method, the image in the image memory 8 is converted into a color image in which each colored block contains only two or less colors, and the color table in the working memory 11 contains two or less colors in each colored block. Colors are memorized. From this color table, the statistical measurement unit 4 calculates statistics corresponding to the proportions of pixels of various colors included in the entire color image and the degree to which pixels of various colors and pixels of other colors are adjacent on the color image. Measure. Based on this measurement result, the large area color determination unit 5 determines the Y value to be associated with the large area color over the entire color image.

5 to 8 are for explaining the specific method of the above processing in the statistical measuring section 4 and the large area determining section 5. FIG. FIG. 5 shows a counting method for obtaining the ratio of various colors in the entire color image and the degree of adjacency of various colors to each other as a histogram from the color table for each colored block in the statistical measuring section 4. In the figure, the rectangles represent colored blocks, and the alphanumeric symbols written inside the rectangles represent the types of colors contained within the colored blocks.

First, the proportion of each color in the image is shown in Figure 5a.
When only one type of color exists in a colored block, the color is counted, as shown in FIG. Since it is quite common for only one type of large-area color to exist in a colored block, a sufficient approximation can be obtained using the statistics of large-area colors. Next, the adjacency degree of each color is
Counting is performed for combinations of two colors. When the colored block includes two colors, color A and color B, as shown in FIG. 5c, the color combinations (A/B) are counted.
Even if there is only one type of color in a colored block as shown in Figure 5d, by referring to the adjacent colored blocks on the upper and left side, you can select a color that is different from the colored block in question.
If only types are included, the combinations of those two colors are counted. Otherwise, do not count (Figure 5e).
The above two counts can be executed in parallel while the central processing unit 9 sequentially refers to the color table in the working memory 11, and the counting results are created in the working memory 11 as a histogram.

FIG. 6 is a diagram showing an example of this histogram. Color numbers representing the types of colors are plotted on the vertical and horizontal axes, and counts of adjacency degrees are stored in array positions corresponding to the combination of two types of colors. Also, on the diagonal,
A count value corresponding to the proportion of each color in the image is stored. Since the count value of the degree of adjacency is symmetrical with respect to the diagonal, only one of them may actually be stored.

The large area determination unit 5 refers to this histogram and sequentially determines the Y values of the large area colors. FIG. 7 is a flowchart showing the procedure of this process. First, in step 16, the proportion of each color in the image, that is, the count values on the diagonal line of the histogram shown in FIG. 6, is checked, and a color having a count value greater than a predetermined first threshold value is determined to be a large area color. Next, Y values corresponding to the determined large-area colors are sequentially determined as follows.
In step 17, the color i having the largest count value is selected among the large area colors whose Y values have not yet been determined. If color i does not exist, this process ends. If color i exists, we already have the corresponding Y from the histogram
A large area color i having the maximum degree of adjacency is selected from among the colors whose value has been determined and the count value of the degree of adjacency with color i is greater than or equal to the second threshold value (step 18).
If color j exists, in step 19 the Y value of color i is determined to be different from the Y value corresponding to color j (Yi=
1-Yj). If color j does not exist, step 20
Set the Y value of color i to 0 (Yi=0). Next, in step 21, a large-area color k whose Y value has not yet been determined is selected among the colors whose adjacency degree count value is greater than or equal to a second threshold value with the color i whose corresponding Y value has just been determined;
In step 22, a value different from the Y value associated with color i is determined for all colors k (Yk=1-Yi).

As described above, the corresponding Y values are determined for all large-area colors in the color image.

Next, using the Y value determined for the large-area color, the correspondence determining unit 6 distributes and associates the two Y values with two or less colors included in each colored block, and stores them in the working memory 11. Enter the corresponding Y value in the color table for each colored block. Next, the information extraction section 7 reads out the pixel values in the image memory 8 in units of colored blocks.
The Y value of each pixel is determined while referring to this color table, and a Y value table as shown in FIG. 4b is created and stored in the working memory 11. Furthermore, the information extraction section 7 organizes the color table described above to create a correspondence table of color values corresponding to each Y value of each colored block as shown in FIG. 4c, and stores it in the working memory 11. , completes the series of processing.

FIG. 8 is a flowchart showing an outline of a method for associating Y values in the correspondence determination unit 6. This correspondence determination process is performed in a predetermined order so that the colored blocks in the image are scanned from the upper left.

In step 23, it is first detected whether there is a large area color within the colored block. If a colored block contains only one color and that color is a large-area color, or if a colored block contains two colors and only one of them is a large-area color, an additional colored block If two types of colors are included in the image, and both of them are large-area colors whose correspondence has been determined to different Y values, it is possible to immediately determine the Y value, so in step 24, the large-area color is Using the determined Y value, two or less colors within the colored block are associated with the Y value. If the result of detecting a large-area color within a colored block in step 23 is other than the above, the relationship between the colored block and adjacent colored blocks is checked as described below, and the local color areas of the color image are connected. Correlate the Y values according to the relationship.

In step 25, it is first determined whether the colored block to be subjected to the correspondence determination process contains the same color as the adjacent colored blocks (the upper and left colored blocks) for which the correspondence with the Y value has already been determined. To detect. This detection is performed by the central processing unit 9 referring to the color table in the working memory 11. If the pixels do not contain the same color, the color of the upper left pixel in the colored block is associated with a Y value of 0, and the other colors are associated with a Y value of 1. If the same color is included, the correspondence is determined in accordance with a request (hereinafter referred to as a connection request) to associate the same color so that it takes the same Y value as the adjacent colored block. In step 26, it is detected whether there is a conflict in this connection request. This is because there may be a plurality of connection requests, and moreover, mutually contradictory mappings may be requested. Figure 9 shows an example of a case where connection requests are contradictory. In the figure, rectangles indicate colored blocks, hatching etc. represent pixel colors, and numerical values are associated with the colors within the colored blocks. Represents the Y value. In FIG. 9a, one color c in the colored block is associated with a Y value of 0 in the upper colored block and a Y value of 1 in the left colored block, and it is not possible to satisfy both connection requests.

Furthermore, in FIG. 9b, the two colors B and C in the block are both associated with a Y value of 1 in the upper colored block and the left colored block, resulting in contradictory connection requests.

In step 27, if there is no conflict in the connection request in step 26, the color and Y value are associated according to the connection request, and if there is a conflict, the color and Y value are associated based on the priority order determined in advance according to the type of connection request. The connection request with the highest priority is determined, and Y values are associated to satisfy that connection request.

FIG. 10 shows specific examples of types of connection requests. The notation in the figure is the same as in Figure 9,
In each of the cases a to c in the figure, it is assumed that the colored block at the lower right is the block to which the Y value is to be associated. Further, FIG. 11 is a flowchart showing priorities for types of connection requests. First, as shown in Figure 10a, if the colored block in question contains only one type of color B, and the colored block on the left also contains only one type of the same color, the Y value of the same color is (steps 28 and 31 in Figure 11).

Next, as shown in Figure 10b, the colored blocks are
If there is a difference between the number of connection requests from the colored block next to the top and the number of connection requests from the colored block next to the left, including the seed colors B and C (in the example, there are two connections for colors B and C from the top). , and there is one connection request for color C from the neighbor on the left), and the colors and Y values are matched to satisfy the connection request with the largest number of connections (see step 11 in Figure 11).
29 and 31). As a connection request with the lowest priority, color B, which has a connection request from the colored block on the left, is also continuously included in the colored block on the left, as shown in Figure 10c. If the Y value has been determined despite the inconsistency in the connection request (in the example, color B continues from the colored block three blocks to the left of the colored block in question, but the color B continues from the colored block two blocks to the left) (The Y value is determined to be 0 due to a conflicting connection request in the block), the connection request from the left side is considered to be "weak", and if there is a connection request from the colored block next to the top that contradicts this, that connection request is The Y values are associated so as to prioritize and satisfy (steps 30 and 31 in Fig. 11). Furthermore, if it is not possible to determine the Y value from conflicting connection requests even using the priority order of connection requests as described above, the connection request from the colored block on the left is given priority over the connection request from the top neighbor. Corresponding Y values (first
Figure 1 Step 32).

FIG. 12 is an example of an image in which two or less colors included in each colored block in the image are associated with Y values in accordance with the priority order of connection requests as described above. The notation in the figure is the same as in FIG. 9. There is a remarkable tendency for the same Y value to be associated with connected areas consisting of pixels of the same color in an image, and the 2
It can be seen that the value image preserves well the shapes of the graphical elements contained in the original color image.

By the way, even if the correspondence determination unit 6 mechanically allocates Y values to two or less types of colors included in each colored block, there is no problem in terms of color image expression, but in that case, the binary image created with Y values will be random. It looks like a pattern and is completely different from the Y value information of the image information created with a conventional image creation device. The method shown in FIGS. 5 and 11 means that it is possible to associate Y values such that the shapes of graphic elements included in the original color image are preserved.

In the above embodiment, the size of the colored block was explained as 4×4 pixels, but the block size may generally be m×n pixels.

In addition, in the above embodiment, a method was explained in which statistics regarding large-area colors and their degree of adjacency are performed by counting in units of colored blocks using a color table, but the counting method can be performed in units of colored blocks or in units of pixels. The effect remains the same.

FIGS. 13 to 14 are diagrams for explaining an embodiment in which statistics regarding large-area colors are counted on a pixel-by-pixel basis. In FIG. 13, numeral 33 is a statistical measurement unit that creates a histogram similar to that in FIG. 6 by counting in pixel units, and other functional blocks are the same as in FIG. 1. Pixel-by-pixel counting is performed by the central processing unit 9 by reading out each pixel from the color image in the image memory 8, and creates a histogram of the counting results in the working memory 11. FIG. 14 shows a specific counting method. The proportion of pixels occupied by each color in a color image is
As shown in FIG. 14a, if the color of the read pixel is A, this is done by incrementing the frequency counting value of color A in the working memory 11 by 1. In addition, the degree of adjacency of colors is calculated by referring to the colors of the pixels to the left and above of each pixel, as shown in Figures 14 b to d, and when the colors of two pixels adjacent to the left and right or top and bottom are different. This is done by counting up the combinations of the two colors. It goes without saying that based on the results of such counting, the processes following the determination of the large area color can be performed in the same way as in the embodiment shown in FIG.

Next, the method of predetermining the Y value to be taken by the large area color explained in the above embodiment is not limited to the method shown in FIG. 7. FIG. 15 is a flowchart showing another method. In FIG. 7, after the Y value to which color i should correspond is determined, all Y values of undetermined color k whose adjacency degree count value with color i is equal to or higher than the second threshold are determined in steps 21 and 22. We decided to determine the value, but the 15th
In the figure, in step 34, color k having the maximum degree of adjacency with color i is selected from among the undetermined colors whose adjacency degree count with color i is greater than or equal to the second threshold value, and its Y value is determined. Regarding the other steps 16 to 22, FIGS. 7 and 15 are the same. Furthermore, the first
In Figure 5, except for step 34 and step 22,
The corresponding color may be determined one by one for each undetermined color i.

Furthermore, regarding the colored blocks in the image, the order of the colored blocks when performing Y-value correspondence is not limited to the scanning order from the upper left to the lower right as explained in the example, but may be performed in the scanning order in other directions. It is possible to do this, and therefore, the adjacent colored blocks to be referred to when making Y-value correspondences are not limited to the adjacent blocks on the left and the adjacent blocks above.

In addition, regarding the specific method of associating two or less colors in each colored block with Y values, we will also discuss how to use Y values that are previously associated with large area colors, the types of connection requests, and the priority given to connection requests. It goes without saying that the ranking is not limited to that described in the above embodiment.

In addition, in this invention, after automatically changing the pixel colors so that the number of color types in each colored block of a color image is 2 or less, a color graphics function is added as an additional function not shown in FIG. As with conventional devices, parts of the color image can be changed interactively (of course, the restriction of no more than two colors in a colored block must be met at this time as well), and then Y-value matching is automatically performed. It is also possible to do this. Even in this case, it goes without saying that the amount of manual interactive processing can be kept to an extremely small amount compared to conventional image creation devices.

Furthermore, the present invention does not particularly limit the method for inputting color images. In the example, a color image is input using a color TV camera or a color scanner, but even if the image is input interactively using the color graphics function (regardless of the colored block format), the same series of results as in the example will be obtained. It is obvious that processing is possible.

〔Effect of the invention〕

As described above, according to the present invention, an information processing apparatus that processes color image information stored in an image memory divides the color image information stored in the image memory into blocks each consisting of a predetermined number of pixels. A color number detection means for detecting the number of colors included in a block, and a multicolor block having three or more colors,
The frequency of appearance of each color included in this multicolor block is counted, the presence or absence of the same color in blocks adjacent to this multicolor block is detected, and two priority colors are selected based on this detection result and the frequency of appearance of each color. A pixel color that is selected and changes each pixel in the multicolor block that has a color different from the two prioritized colors to the color that appears more frequently among the two prioritized colors in pixels surrounding the pixel. a statistical measuring means for detecting the frequency with which the large area colors are adjacent to each other with respect to large area colors occupying a large number of pixels in a color image; a large-area color determining means for determining a large area color; and a correspondence determining means for associating a binary value indicating the color type of the pixel with each pixel in the block for each block after the change by the pixel color changing means. The selection of the two priority colors involves selecting a color whose appearance frequency exceeds a first threshold value, and if three or more colors are selected as a result, a second threshold value that is larger than the first threshold value is selected. Select a color that has a frequency of occurrence greater than 3 or is present in adjacent blocks, and then
If more than one color is selected, a color with an appearance frequency exceeding a second threshold is selected, and if three or more colors or one or less colors are selected, a color with an appearance frequency exceeding a second threshold is selected. This is done by selecting the two largest colors, and the correspondence between the binary values of each pixel is determined by the value determined by the large area color determination means for the large area color for the block containing the large area color. For blocks that cannot be matched by this, it is detected whether or not they contain the same color as the adjacent block for which the correspondence with the binary value has already been determined, and the same color is detected. If the same color contains the same binary value as the adjacent block, a connection request is made to detect whether or not there is a conflict in relation to multiple adjacent blocks, and to check whether or not there is a conflict. If there is no such connection request, it is matched to that connection request, and if there is a conflict, it is matched to the connection request with the highest priority according to the predetermined priority order for the type of connection request. By doing this, it is possible to automatically convert a color image created regardless of the block into image information in the form of a colored block, which reflects the characteristics of the shape of the image as a whole in binary values. This has the effect of providing a color image processing device that can efficiently create images that conform to the colored block format.

[Brief explanation of drawings]

FIG. 1 is a functional block diagram showing an embodiment of the present invention, FIG. 2 is a system configuration diagram thereof, FIG. 3 is a flowchart showing a specific method for reducing the number of colors in a colored block to two or less, and FIG. Figure 5 is an explanatory diagram of the colored block format, Figure 5 is an explanatory diagram of the method of counting the ratio of each color pixel in the entire color image and the frequency of adjacency between colors, Figure 6 is a diagram showing an example of a histogram of the counting results, Figure 7 is a flowchart showing a method for determining the Y value to correspond to a large area color, Figure 8 is a flowchart showing a method for associating Y values with two or less colors in each colored block, and Figure 9. is an explanatory diagram showing an example when connection requests are contradictory, FIG. 10 is an explanatory diagram showing specific examples of types of connection requests, FIG. 11 is a flowchart showing an example of priority order of connection requests, and FIG. An example of an image in which Y values are associated, FIG. 13 is a functional block diagram showing another embodiment of the present invention, and FIG. 14 is an explanatory diagram of another method for counting the proportion of each color pixel and the frequency of adjacency between colors. , FIG. 15 is a flowchart showing another method for determining the Y value corresponding to a large area color, and FIG. 16 is a block diagram showing the configuration of a conventional image creating apparatus. In the figure, 1 is an image input section, 2 is a color number detection section (means), 3 is a pixel color change section (means), 4 is a statistical measurement section (means), 5 is a large area color determination section (means), and 6 7 is a correspondence determination unit (means), 7 is an information extraction unit, 8 is an image memory, 9 is a central processing unit, 10 is a program memory, 11 is a working memory, and M is an information processing device. Note that the same reference numerals in each figure indicate the same or corresponding parts.

Claims (1)

[Scope of Claims] 1. A color image processing device comprising an image memory that stores input color image information, and an information processing device that processes the color image information stored in the image memory, comprising: The apparatus includes a color number detection means for dividing the color image information stored in the image memory into blocks each having a predetermined number of pixels and detecting the number of colors included in each block; For a multicolor block having the above number of colors, the frequency of appearance of each color included in the multicolor block is counted, and the presence or absence of the same color in the blocks adjacent to the multicolor block is detected, and the detection result and each of the above colors are calculated. The two priority colors are selected based on the frequency of appearance of each pixel in the multicolor block, and each pixel having a color different from the two priority colors is selected based on the frequency of occurrence of the two priority colors in the pixels surrounding the pixel. pixel color changing means for changing the color to a color with a high appearance frequency; statistical measuring means for detecting the frequency with which large area colors occupying a large number of pixels in the color image are adjacent to each other; large area color determining means for determining the binary value taken by the large area color based on the frequency; and a correspondence determining means for associating binary values indicating color types, and the selection of the two priority colors selects a color whose appearance frequency exceeds the first threshold value, and as a result, three or more colors are selected. If a color is selected, select a color that has the appearance frequency exceeding a second threshold value that is greater than the first threshold value or exists in an adjacent block;
Furthermore, if three or more colors are selected as a result, a color with the frequency of appearance exceeding the second threshold is selected, and as a result, three or more colors or one or less colors are selected. In this case, the two colors with the highest frequency of appearance are selected, and the correspondence between the binary values of each pixel is as follows: Binary values are associated with each other using the values determined by the large-area color determining means, and the blocks that cannot be associated are of the same color as those included in the adjacent blocks for which the association with binary values has been determined. The connection request for detecting the presence or absence of the same color and associating it so that the same color takes the same binary value as the adjacent blocks mentioned above is inconsistent with the relation with the plurality of neighboring blocks mentioned above. The presence or absence is detected, and if there is no conflict, it is matched to the connection request, and if there is a conflict, it is matched to the connection request with the highest priority according to the predetermined priority for the type of connection request. Image information is obtained by associating the color image information stored in the image memory with information indicating binary values in pixel units and information indicating two or less color values in block units. A color image processing device characterized by converting images into images.