JPS6224373A - Color picture processor - Google Patents

Abstract

PURPOSE:To attain a picture producing system which requires no manual operation with a short time needed for production of information and with high efficiency, by converting automatically a given color picture into the picture information of a colored block style. CONSTITUTION:The picture stored in a picture memory 8 is converted into a color picture including 2 types of colors and stored in a colored block. A statistic measurement part 4 measures a statistic amount equivalent to the adjacency degree on the picture. Based on this statistic amount, a large area color deciding part 5 decides the Y value to be set in response to the large area color over the entire part of a color picture. Based on the Y value, a correspondence deciding part 6 allocates the two Y values to the >=2 types of colors included in each colored block and writes the Y vale corresponding to a color table of each colored block stored in a working memory 11. Then an information extracting part 7 reads out the values of picture elements in the memory 8 for each colored block and produces a Y value table with reference to the color table to store it in the memory 11. Furthermore the color table is rearranged to produce a correspondence table for color values corresponding to Y values of each colored block. Then this correspondence table is stored in the memory 11.

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 using color still images, such as videotex, teletext, and CD subcode, have been increasing. The images used in these applications have a special structure called a colored block format, and because color images are expressed using a relatively small amount of data, they are advantageous for storage and transmission. FIG. 4 is a diagram for explaining the colored block format, in which (a) is an example of a color image with a structure suitable for the colored block format, and (b') and (C) are colored blocks. This is an example of image information representing a format image. In FIG. 4(a), the minimum rectangle represents a pixel, and the type of color of the pixel is represented using hatching or the like.

Here, the image is a rectangular block of a predetermined size (in the example, 4×
It is divided into 4 pixels (hereinafter referred to as "coloring blocks"), and coloring is limited in units of coloring 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 a Y value) that specifies which of two or less colors to use.

FIGS. 4(b) and 4(C) are image information corresponding to the color image system of Ca) in FIG. 4, which corresponds to the upper colored block row.

For example, in the second colored block from the left, the Y value representing color value A is set to O, and the Y value representing color value B is set to 1.
A Y value is given to each of the six pixels. Here, if only one color is included, like the leftmost colored block, the Y value corresponding to that color can be either 0 or 1, and as in the example, the Y value O and the color value A are As long as they correspond, any color value may correspond to the other Y value of 1.

In FIG. 4(C), this is marked as X (don't care). In addition, the color value is not a value that directly represents the color, but
It is often a value indicating the number of a color in a predetermined set of colors. When a color image is expressed using image information as shown in Figures 4(b) and (c), the amount of data becomes extremely small compared to expressions that specify the color value of each pixel one by one. Since data compression of two or fewer color values in each colored block is possible through 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. 16th
The figure is a block diagram showing an example of the configuration of a conventional device for creating image information in a colored block format. In the figure, 1 is an image input unit for inputting a black and white image, and 35 is for creating or modifying a binary image. A binary image correction section 36 is a coloring specification section that specifies coloring in units of colored blocks, and 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 specifying unit 36 specifies the color to be given to pixels of value 0 and the color to be given to pixels of value 1 for each coloring block of the binary image, thereby performing coloring. The operator determines whether the shape of the image as a result of coloring is good or bad. If coloring that maintains the shape of the elemental figures that make up the image is not possible 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 colored block units. A typical system configuration of such a conventional image information creation device includes an image scanner as the image input unit 1, and other parts as an information processing device with a color graphic function (including image memory). It is a personal computer.

[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, inputting a binary image so that the colored block contains only two or less colors from the beginning requires a full-time designer who has mastered the colored block format. 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 takes time to create information. 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 has an information processing device that processes color image information stored in an image memory divide the color image stored in the image memory into colored blocks each having a predetermined number of pixels. A color number detection means for detecting the number of types of colors included in a colored block, and for colored blocks containing more than two types of colors detected by this detection means, pixels of colors other than the two priority types based on a predetermined threshold value. pixel color changing means for changing the color to one of the two priority colors mentioned above, and for each colored block of the image after the above change, a binary value indicating the distinction of colors within the block corresponds to each pixel unit. and statistical measurement for detecting a large area color that occupies a large proportion in terms of the number of pixels in the entire color image and the frequency with which these large area colors are adjacent to each other when there are a plurality of such large area colors. and a large-area color determining means for determining, prior to the correspondence determining means, a binary value that a specific large-area color should take based on the detection result.

[Effect]

The image processing device according to the present invention divides a color image created and input regardless of the color block format into color blocks, detects the number of types of colors included in each color block, and detects the number of types of colors included in each color block, and Change the colors of the necessary pixels in the colored block so that there are 2 types or less for the colored block containing , and then change the binary values to the 2 or less types of colors included in the colored block as a large area color. This system automatically performs a series of processes to allocate the data in consideration of a predetermined value.

As a result, color image information not based on the colored block format is converted to image information in the colored block format, which includes binary values in pixel units and information indicating color values in units of coloring units.

[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 that inputs a color image to be processed, and 2 is a color block that detects the number of types of colors in a colored block. 3 is a pixel color changing unit that is a pixel color changing unit that changes 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; A statistical measuring unit serving as a statistical measuring means for measuring the occupying ratio and the degree to which pixels of various colors and pixels of other colors are adjacent on a color image from information on the color types included in each colored block; 5 is a color image; Colors that occupy a large proportion of the total number of pixels (hereinafter referred to as large area colors)
a large-area color determining unit serving as a large-area color determining unit that determines a Y value to be associated with a color; 6 a correspondence determining unit serving as a correspondence determining unit that associates Y values with two or less types of colors in each colored block;
Reference numeral 7 denotes 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. In the figure, 1 is a color image input device such as a color TV camera or a color scanner, 8 is an image memory for storing color images, 9 is a central processing unit such as a microprocessor, and 1° stores the program of the central processing unit 9. 11 is a working memory that stores data generated in the process of processing. Of these, 9 to 11 correspond to a computer M as an information processing device such as a microcomputer, and are shown in FIG. Components 2 to 7 shown are realized by this.

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 calculates 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 unit 3 changes the colors of a small number of pixels in the colored block so that the colors are equal to or less than two 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 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, first, colors whose appearance frequency is less than or equal to the first threshold Tl are excluded. If you cannot narrow it down to two types or less,
First, colors that do not exist in adjacent blocks with an appearance frequency that is less than or equal to the second threshold T2 are first excluded, and if the number of occurrences does not exceed two types, all colors that are less than or equal to the threshold T2 are excluded.

Furthermore, if more than two colors remain, or if too many colors are excluded, the two colors with the highest frequency of appearance are selected. The colors outside the two or less color primaries selected in this way are deleted from the color table, and the pixels with that color are
In step 15, the color is changed to the selected color (if there are two colors, one of them) in the colored block. For this change, the central processing unit 9 examines the surrounding pixels of the pixel whose color should be changed within the coloring block, and changes the color 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 proportions of various colors in the entire color image and the degree of adjacency of various hue pressures 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 alphabet 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 calculated by counting the proportion of each color when only one type exists in the colored block as shown in Figure 5 ('a), and by counting the proportion of each color when only one type exists in the colored block as shown in Figure 5 ('b). If color is included, it is determined by not counting. 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 degree of adjacency of each color is calculated for the combination of two colors. When the colored block includes two colors, color A and color B, as shown in FIG. 5(C), the color combinations (A/B) are counted.

Even if there is only one type of color in a colored block as shown in Figure 5(d'), refer to the adjacent colored blocks on the upper and left side and if they contain only one type of color different from the colored block, Count the combinations of two colors. In other cases, it is not counted (Figure 5(e)).

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. Further, on the diagonal line, 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 value on the diagonal line in the histogram shown in FIG. 6, is checked, and a color having a count value equal to or greater than a predetermined first threshold value is determined as 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, the corresponding Y value has already been determined from the histogram, and the large area has the largest degree of contiguity among the colors whose count value of degree of contiguity with brown i is greater than or equal to the second threshold. Select color j (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, the Y value of color i is set to 0 (Yi=0) in step 20. Next, in step 21, a large-area color k for which the Y value has not yet been determined is selected among the colors whose adjacency degree count value is greater than or equal to the second threshold value with respect to the color i for which the corresponding Y value has just been determined, and in step 22 For every color k, determine a value different from the Y value associated with color i (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 the Y value in the working memory 11. Enter the corresponding Y value in the color table for each colored block. Next, the information extracting section 7 reads out the pixel values in the image memory 8 in units of colored blocks, determines the Y value of each pixel while referring to this color table, and calculates the Y value of each pixel as shown in FIG. 4(b). A table of Y values is created and stored in the working memory 11. Furthermore, the information extraction unit 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. 4(C), and stores it in the working memory 11. Store and complete 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 that have been determined to correspond to different Y values, it is possible to immediately determine the Y value, so the large-area color is determined in step 24. Using the determined Y value, two or less colors in 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 the neighboring colored blocks is determined as described below.Connection of local color areas of the color image Correlate the Y values according to the relationship.

In step 25, the colored block that should first undergo the correspondence determination process is an adjacent colored block (the upper and left colored blocks) for which the correspondence with the Y value has already been determined.
Detects whether the same color is included. This detection is performed by the central processing unit 9 referring to the color table in the working memory 11. If they do not contain the same color, the color of the upper left pixel in the colored block is associated with the Y value of O, and the other colors are associated with the Y value of 1. If the same color is included, the correspondence is determined in accordance with a request for correspondence so that the same color has the same Y value as an adjacent colored block (hereinafter referred to as a connection request). In step 26,
It is detected whether or not there is a contradiction 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 inconsistent. 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. 9(a), 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.

In addition, in FIG. 9(b), the two colors B in the block,
C is Y for both the upper colored block and the left colored block
It is associated with the value 1, making it a contradictory connection request.

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 highest priority is selected based on a predetermined priority order according to the type of connection request. A connection request having a value of

FIG. 10 shows specific examples of types of connection requests. The notation in the figure is the same as that in FIG. 9, and in each case of (a) to CC) in the figure, the lower right colored block is the block to which the Y value should be associated. Further, FIG. 11 is a flowchart showing priorities for types of connection requests. First, as shown in Figure 1O (a>), if the colored block in question contains only one type of color B, and the colored block to the left also contains only one type of the same color, the Y value of the same color is Make it the same value as the block on the left (
FIG. 11 steps 28 and 31).

Next, as shown in Figure 1θ Bb), the colored block contains two colors B and C, and there is a difference in the number of connection requests from the supernatant colored block and the number of connection requests from the colored block on the left. If there are (in the example, there are two connection requests for colors B and C from the supernatant, and one connection request for color C from the left neighbor), the colors and Y values are matched so as to satisfy the connection request that has more connections. (11th
Figure steps 29 and 31). As a connection request with the lowest priority, color B, which has a connection request from the colored block to the left, is also continuously included in the colored block to the left, as shown in FIG. 10(c). , and the Y value has been determined even though there is a conflict 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) There is a conflict of connection requests in the colored block, and the Y value is determined to O), and the connection request from the left side is considered "weak".
If there is a connection request contrary to this from the supernatant colored block, the Y value is associated so that that connection request is satisfied preferentially (steps 30 and 31 in FIG. 11).

Furthermore, if the Y value cannot be determined 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 will be satisfied with priority over the connection request from the supernatant. Corresponding Y values (Step 32 in Figure 11)
).

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 according to 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 Y
It can be seen that the binary image created from values preserves well the shapes of the graphical elements contained in the original color image.

By the way, in the correspondence determination unit 6, the 2 included in each colored block is
Although there is no problem in color image expression even if the Y values are mechanically allocated to different colors, in that case, the binary image created by the Y values will look like a random pattern and cannot be created using conventional image creation equipment. This information is completely different from the Y value information of the image information. 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 addition, although the size of the colored block was explained as 4x4 pixels in the above embodiment, the block size may generally be mxn pixels.

Further, the specific method of limiting the number of types of colors in each colored block to two or less as explained in the above embodiment is not limited to the method shown in FIG. It is also possible to simply select the two colors with the highest frequency within the colored block without reference. Furthermore, when referring to a color included in an adjacent colored block, a more complicated method is used, such as taking into account whether areas of the same color are connected between the concerned block and the adjacent colored block in determining the two priority colors. You can also take

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 each colored block using a color table. The effect remains the same.

FIGS. 13 and 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, 33 is a statistical measurement unit that creates a histogram similar to Fig. 6 by counting pixel units;
Other functional blocks are the same as in FIG. 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. 14th
The figure shows a specific counting method. The ratio of pixels occupied by each color included in a color image is as shown in FIG. 14(a). If the color of the read pixel is A, the frequency count value of color A in the working memory 11 is counted by 1. This is done by amplifying.

In addition, the counting of the degree of adjacency of colors is shown in Fig. 14 (b) to (d).
This is done by referring to the color of the pixel to the left of each pixel and the supernatant pixel, and counting up the combination of the two colors when the colors of the two pixels adjacent to the left and right or top and bottom are different. . It goes without saying that based on the results of such counting, the processes subsequent to 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. 15th
The figure is a flowchart illustrating another method. In FIG. 7, after the Y value to which color i should correspond is determined, in steps 21 and 22, the count value of the degree of adjacency with color i is determined by the second
It is assumed that all Y values of undetermined colors that are equal to or higher than the second threshold are determined, but in FIG. It is assumed that a color k having a degree of adjacency is selected and its Y value is determined. For other steps 16 to 22, please refer to the 7th step.
The figure and FIG. 15 are similar.

Furthermore, in FIG. 15, except for steps 34 and 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 left-hand neighbor and the supernatant block.

In addition, in the specific method of associating Y values with two or less types of colors in each colored block, 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 the color image is 2 or less, a color graph ink function is added as an additional function not shown in FIG. , you can interactively change parts of the color image in the same way as with conventional devices (of course, at this time as well, you have to satisfy the restriction of 2 colors or less in a colored block), and then automatically change the Y value correspondence. 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 a color graphic 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 device that processes color image information stored in an image memory is provided with a color image stored in the image memory divided into colored blocks each having a predetermined number of pixels. Color number detection means detects the number of types of colors contained in each colored block, and for colored blocks containing more than two types of colors detected by this detection means, colors other than the two priority types are detected based on a predetermined threshold value. pixel color changing means for changing the pixel to one of the two priority colors;
For each colored block of the image after the above change, a correspondence determining means is provided for associating a binary value indicating color distinction within the block with each pixel unit, and the number of pixels is determined based on the overall color image. A statistical measuring means for detecting a large area color that occupies a large proportion and the frequency with which these large area colors are adjacent to each other when there are multiple large area colors, and a binary value that a specific large area color should take based on this detection result. By being equipped with a large-area color determining means that determines the color prior to the above-mentioned correspondence determining means, the color image created regardless of the coloring block is automatically reflected in the binary values of the shape characteristics of the entire image. The present invention has the effect of providing a color image processing device that can convert image information into colored block format image information and efficiently create an image that conforms to the colored block format.

[Brief explanation of the drawing]

FIG. 1 is a functional block diagram showing an embodiment of the present invention, FIG. 2 is a system configuration diagram thereof, and FIG. 3 is a flowchart showing a specific method for reducing the number of colors in a colored block to two or less.
Fig. 4 is an explanatory diagram of the colored block format, Fig. 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 adjacent colors, and Fig. 6 is a diagram showing an example of a histogram of the counting results. , FIG. 7 is a flowchart showing a method for determining the Y value to correspond to a large area color, FIG. 8 is a flowchart showing a method for associating Y values with two or less colors in each colored block, and FIG. 9 is an explanatory diagram showing an example of a case where connection requests are inconsistent, FIG. 10 is an explanatory diagram showing a specific example of the types of connection requests, FIG. 11 is a flowchart showing an example of the priority order of connection requests, and FIG. 12 is a Y An example of an image in which values are associated, FIG. 13 is a functional block diagram showing another embodiment of the present invention,
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;
The figure is a block diagram showing the configuration of a conventional image creation device. In the figure, 1 is an image input section, and 2 is a color number detection section (means).
, 3 is a pixel color changing unit (means), 4 is a statistical measurement unit (means)
, 5 is a large area color determination unit (means), 6 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, M is a It is an information processing device. Note that the same reference numerals in each figure indicate the same or corresponding parts. Agent Masuo Oone (and 2 others) Figure 1 Figure 2 Figure 12 Figure 15 Procedural amendment (self-knowledge 1° incident 0 indication Patent Application No. 163208-1982 2)
Name of the invention Color image processing device 3, Representative of the person making the correction Moriya Shiki 5, Scope of patent claims to be corrected, Column for detailed description of the invention. 6. Contents of amendment (1) The claims are amended as shown in the attached sheet. (2) In the specification, page 7, line 15, and page 27, lines 3 and 4, the phrase "based on a predetermined threshold value" is amended to "based on a predetermined determination method." Claims 2. Claims A color image processing device comprising an image memory for storing an inputted color image and an information processing device for processing color image information stored in the image memory, the color image processing device comprising: The processing device includes a color number detection means for dividing the color image stored in the image memory into colored blocks each having a predetermined number of pixels and detecting the number of types of colors included in each colored block; For colored blocks containing more than two detected colors, Priority 2 based on Tokorono Hai Toskin
pixel color changing means for changing pixels of a color other than the color to one of the two priority types, and a binary value indicating color distinction within the block for each colored block of the image after the change. a large-area color that occupies a large proportion in terms of the number of pixels in the entire color image, and the frequency with which these large-area colors are adjacent to each other when there are a plurality of such large-area colors. A statistical measuring means for detecting the color image information, and a large area color determining means for determining the binary value that a specific large area color should take based on the detection result prior to the correspondence determining means, What is claimed is: 1. A color image processing device that converts a color image into image information consisting of a binary value and information indicating a color value in units of colored blocks.

Claims (1)

[Claims] A color image processing device comprising an image memory that stores an input color image, and an information processing device that processes color image information stored in the image memory, the information processing device including a computer that processes the color image information stored in the image memory. Color number detection means for dividing a stored color image into colored blocks each having a predetermined number of pixels and detecting the number of types of colors contained in each colored block, and more than two types of colors detected by this detection means. a pixel color changing means for changing a pixel of a color other than the two priority types based on a predetermined threshold value to one of the two priority types, for each colored block of the image after the change; and a correspondence determination means for associating a binary value indicating color distinction within each pixel unit, and
A statistical measuring means for detecting a large area color that occupies a large proportion in terms of the number of pixels in the entire color image and the frequency with which these large area colors are adjacent to each other when there are multiple large area colors, and a specific large area color based on this detection result. large-area color determining means for determining a binary value that the area color should take prior to the correspondence determining means, the color image information indicating a binary value for each pixel and a color value for each colored block; A color image processing device characterized by converting information into image information consisting of.