JPH01259363A - Image contour data generating method - Google Patents

Abstract

PURPOSE:To clearly detect a contour even if a density level difference of a specific image and a background image is small by comparing a differential value of a density level of a picture element with a reference level. CONSTITUTION:First of all, image data of each color resolution plate of YMCK of an image which has been stored in an image memory 5 is displayed as a color image on an image display device 9. Subsequently, a partial image block frame N containing a part of a contour line l of a specific image I is instructed with a stylus pen 11, image data corresponding to an area of the frame N is read out and a differential processing is performed at every picture element, and an obtained value is stored in a RAM 3. Next, a plate whose statistic quantity is maximum and whose line l is the clearest is selected, a prescribed differential value is determined to a reference level, and thereafter, based on its level, each differential value is binarized, and binary data is written in a mask memory 7. Subsequently, the processing is executed in the same way in order from the plate whose statistic quantity is large in the next place, and contour data is obtained.

Description

Detailed Description of the Invention <Industrial Application Field> The present invention relates to a method for creating image contour data used when creating a punching mask for an original image to be processed such as a photographic image. Used in photoengraving machines, layout scanners, automatic drafting machines, etc.

<Prior Art> A punching mask is used, for example, in photoengraving work to obtain a duplicate image of only a desired image area of a photographic image or to change the tone of only a desired image area.

For example, when printing a product catalog, the product photo used as the original print image usually has a background around the necessary product image area, but as a printed product, that background area is erased and only the product area is displayed. There are many things.

When performing such work, first create outline data for the required image area, then set either the internal or external area of the outline to the "H" level (physically opaque (or transparent)). ), and set the other to L” level (corresponding to
Cutting mask pattern data that is made transparent (corresponding to opaque) is created, and based on the punching mask pattern data, only a desired image area of the original image to be processed is extracted to obtain a duplicate image.

Japanese Patent Publication No. 63-5745 (title of the invention: ``Method for Preparing Cutout Mask Plate'') is known as one of the conventional excellent image contour data preparation methods. This method uses the difference between the density level of a specific image and the density level of a background image to obtain contour data of a specific image. The outline of the method is as follows.

First, convert the original image data to an image on a CRT monitor, etc. □
Display on a display device. A small area including an outline in a specific image to be extracted from the displayed image is specified using a partial image division frame (referred to as a nozzle).

The density level of each pixel in the area of the partial image division frame is compared with the reference density level, and for pixel portions where the pixel 4-change level is equal to or higher than the reference density level, this is set to H'' (
or "L"), and for pixel parts whose pixel density level is less than the reference density level, this is set to "L" (or "H").
''), contour data of the specific image in the area of the partial image partition frame is obtained.

Next, the partial image partition frame is moved to an adjacent area along the contour line of the specific image being displayed, and the same process as described above is performed. By moving and going around the 0 contour line that determines the contour data of the partition frame area, contour data for the entire contour line (closed loop) of the specific image is obtained.

In this conventional method, the reference concentration level can be changed as necessary. As the partial image section frame is moved along the contour line of the specific image, either or both of the density level of the specific image and the background image changes. If the reference concentration level is fixed, a place that should be H'' may be L, or a place that should be 'L' may be H.
Discontinuous portions will occur in the contour data for the entire contour line of the specific image. However, by changing the reference density level according to changes in the density level of a specific image, it is possible to always maintain a clear difference between the density level of the specific image and the background image density level, and to Contour data can be obtained.

<Problems to be Solved by the Invention> However, in the case of this conventional example, as described above, the operator has to change the setting of the reference density level each time the density level changes along the contour line. In addition, it is difficult to judge to what level changes should be made, so there is room for improvement in terms of work efficiency. Furthermore, even if it is possible to change the reference density level, in areas where the difference between the specific image density level and the background image density level is sufficiently small, the ability to detect contours will be low and it may not be possible to detect them. there is a possibility.

In addition, when a specific image is a multicolor image and is separated into multiple color separation plates, the operator must decide which plate to convert to 24a, and the outline may become thicker (the hue changes). In some cases, the partial image partition frame cannot be moved smoothly.

The present invention has been made in view of the above circumstances, and it is possible to omit the trouble of changing the reference density level, and also to clearly draw contour lines even if the difference in density level between a specific image and a background image is small. The purpose is to enable detection and automatic selection of color separations.

The present invention believes that the causes of the problems in the conventional example are that the outline was attempted to be detected by "density level difference" and that part of the selection of the reference density level and color separation plate was left to the operator. The problem was solved using a method like this.

Means for Solving the Problems> A first image contour data creation method of the present invention displays a floor image including a specific image, and designates a partial image section frame including a part of the contour of the specific image. Then, a differential process is applied to each pixel within the partial image division frame area, and the differential value of each pixel is binarized based on a comparison between the differential value of the density level of each pixel and an appropriate reference level. The value data is stored as contour data in the partial image partition frame, and the partial image partition frame is moved one step along the contour line of the specific image, and the same processing as described above is performed on each partial image partition frame. Ta2
(A data is sequentially stored to obtain contour data regarding the contour line of a specific image.

In the second method for creating image contour data of the present invention, in the first method, when the original image to be processed including the specific image is a multicolor original image, the image data of the specific image is color-separated into a plurality of color separation plates. , select one or more color separations in order from those with clear outlines,
Differential processing in each sub-image partition frame for each selected color separation.

2 of the differential value by comparing the differential value with the reference level (for each color separation plate obtained earlier when performing petrification and sequentially storing the binary data obtained for each color separation plate in each partial image partition frame) If there is binary data, the logical OR with that binary data is calculated and stored.

A third image contour data creation method of the present invention includes, in the second method, selecting a color separation plate having a clear contour line for each partial image partition frame within the partial image partition frame of each color separation plate. This is performed in descending order of the statistical amount indicating the dispersion of the differential value of each pixel.

A fourth image contour data creation method of the present invention is to determine a reference level for each partial image partition frame based on the p-tile ratio in the statistics in the first or second method.

In this specification, the term "density" is used not only to refer to optical density values in a narrow sense, but also to optical density values, such as the Munsell value, the output signal level of an original image reading device, and the halftone area ratio in halftone image recording. This term is used to refer to a general amount depending on the concentration value.

Effects> The effects of each of the above configurations of the present invention are as follows.

According to the first method, the target for obtaining binary data by comparison with a reference level is not the density level of a pixel but the differential value of that density level, so the difference between the specific image density level and the background image density level Even if the value is small, the contour detection ability is improved and the reference level is changed less frequently.

The second method deals with the case where the original image to be processed including the specific image is a multicolor original image, and since the clarity of the outline differs depending on the color separation version, clear color separation of the outline is necessary. Differential processing is performed in each partial image division frame for each color separation plate selected in order from the plate, and the differential value is binarized by comparing the differential value with a reference level. Since the binary data obtained for each color separation plate is sequentially stored, the logical OR with the 2-value data for each color separation plate obtained earlier is calculated and the detection ability is reduced due to the difference in differential values. I can cover it.

According to the third method, the color separation plates in the second method are selected in descending order of the statistical amount indicating the dispersion of the differential value of each pixel in each partial image section frame of the color separation plate. This makes it possible to automate the selection.

According to the fourth method, in the first or second method,
Since the reference level is determined for each partial image partition frame based on the p-tile ratio in the statistics, the same ring gV1m
Even if there are parts where the density changes gradually and parts where the density changes steeply, the reference level corresponding to each part is automatically determined.

<Example> Hereinafter, an example of the present invention will be described in detail based on the drawings.

FIG. 1 shows a schematic configuration of a system implementing the image contour data creation method of the present invention.

In the figure, reference numeral 1 denotes a CPU in a microcomputer for controlling the entire system.

2 is a ROM (or RA) that stores the execution program.
M), 3 is a differential value table 3a which will be described later.

Differential value frequency distribution (histogram) table 3b.

This is a RAM that has other data tables.

4 is multivalued image data obtained by photoelectrically scanning the original image to be processed, which is Y (yellow) and 2M (magenta).

A disk memory 5 stores color separation into four colors, C (cyan) and K (black), and 5 indicates each color separation of YMCK read out from the disk memory 4 via a pass line 6 under the control of the CPU 1. An image memory for storing image data of a plate, including Y memory 5v, M memory 5, 4 . C
Memory 56. and memory 5.

7 is a mask memory that stores the created contour data;
8 is a D/A conversion function, which converts the image data of each color separation version of YMCK read from the image memory 5 into R (red) and G (
Digitizer 10, function to convert into green) and B (blue) signals
A function to display the shape of the partial image division frame (nozzle) N according to A function to display semi-transparently,
This image display adjustment device has a function of changing the display priority order, a function of superimposing and displaying data in the image memory 5 and data in the mask memory 7, and the like. 9 is a color image display device such as a CRT display.

10, by specifying the coordinate point with the stylus pen 11,
It is an X-Y digitizer or the like that inputs coordinate point data corresponding to addresses in the image memory 5 and mask memory 7, and the specified coordinate points are displayed as a partial image section frame at the corresponding position on the screen of the image display device 9. Ru. By pressing the switch attached to the stylus pen 11, the stylus pen 11 instructs the CPU to detect the outline of the partial image partition frame displayed on the screen of the image display device 9.

12 is a keyboard for instructing how many color separations to adopt from among the YMCK color separations starting from those with clear outlines and inputting necessary instructions; 13 is a partial image division frame N; The first step is to set and change the size (radius) of
Encoder 14 is a second encoder that sets and changes the p-tile ratio, which will be described below.

Next, the operation of this embodiment will be explained with reference to the flowchart of FIG. 2 and the operation diagrams of FIGS. 3 to 9.

In step S1, according to an operator's instruction, the CPU reads image data of each YMCK color separation version of the image including the specific image to be extracted from the disk memory 4,
Corresponding Y memory 5y and M memory 5 of image memory 5
N, C memory5. .

K memory 5, respectively. In step S2, the mask memory 7 is cleared.

In step S3, when the image data of each color separation version of YMCK is sent from the image memory 5 to the image display adjustment device 8, those image data are transferred to the image display adjustment device 8.
After the /A conversion, the image is converted into RGB signals, and a color image including the specific image is displayed on the image display device 9. That-
An example is shown in FIG. 3(A), where ■ represents a specific image and 2 represents a contour line.

Next, by operating the keyboard 12, the operator selects the number T of YMCK color separations to be adopted, starting from the one with the clearest outline (this point will be described later). Enter the initial value, but the CPU
In step S4, data of the input version number T is stored in the RAM3.

Next, in step S5, the coordinate point data specified by the operator with the stylus pen 11 on the digitizer 10 and the size of the partial image division frame N specified with the first encoder 13 are read and stored in the RAM 3, and the data on the image display device 9 are read. The partial image division frame N is displayed in the specified size with the corresponding position on the screen as the center. Figure 3 (A
) indicates an example. The position and size of the partial image division frame N change as the stylus pen 11 moves and the first encoder 13 is operated. The operator, while looking at the screen of the image display device 9, selects the specific image I being displayed.
The stylus pen 11 is operated so that the partial image division frame N is placed on the contour line 2 of .

In step S6, it is determined whether an instruction to end the process has been input from the keyboard 12, but since the detection of contour data has not been completed, the process proceeds to the next step S7. When the line P is on or near the contour line P, the operator presses a switch on the stylus pen 11 to instruct contour detection, which is determined in step S7. This judgment is NO
This indicates that the partial image division frame N is being moved, and in that case, the process returns to step S5.

In step S8, the image data of each color separation version of YMCK corresponding to the area of the partial image division frame N is sequentially read out from the image memory 5, and differential processing is performed for each pixel of each version. The differential values are stored in the differential value table 3a of the RAM 3, a differential value frequency distribution (histogram) table 3b of the RAM 3 is created, and statistics representing variations (distribution) of the differential values are calculated and stored in the RAM 3.

To give a specific example, as shown in FIG. 4(A), the level PI (i=1.2°3...・・rz
n is the total number of pixels in the area of the partial image division frame N),
Perform a known differential operation on mXm pixels to calculate the differential value Ei (+=1.2.3...n), and store it in the differential value table 3a as shown in FIG. 4(B). The level P1 of the 0 pixel changes greatly with the contour line 2 as a boundary, and maintains a substantially constant value on both sides of the contour line l. Therefore, the differential value E1 takes a large value in pixels forming the contour line l, and takes a small value in flat pixels of other levels.

The differential value (IIE+) usually differs for each color separation of YMCK.The differential value Ei for each YMCK is expressed as EYi+EIIi+Li+EK!, and the statistics indicating the respective variations are SV, S, respectively.

Represented by Sc and S. The statistical quantities indicating dispersion include variance, the sum of absolute values of residuals, etc., and each is calculated based on, for example, the following equation.

Sum of absolute values of residuals = Σ 1Ei4 However, here, It is.

Each statistic Sv, s+4. Sc, S11 are the differential values of each color separation of YMCK EYj+ ENI+ EC1, Ex+
It shows the bias in the distribution of color separations, where color separations with clear outlines have large values, and color separations with unclear outlines have small values.

FIGS. 5(A) to (D) show the differential value Evt of each color separation plate,
An example of a histogram of E, l, EC1, and BKI is shown, where the horizontal axis represents the differential value and the vertical axis represents the frequency. In this example,
Statistics representing the dispersion ISy, SM, Sc.

S is such that Sc>Sv>S14>SK.

In step S4, by operating the keyboard 12, Y
Among the MCK color separations, it was decided to adopt several color separations in order from those with clear outlines, but this was done based on the magnitude relationship of the statistics Sv, Ss, Sc, and SK. For example, in the case of FIG. 5, when three color separation plates are employed, the 0 edition, Y edition, and 0M edition are adopted from the one with the largest statistical amount.

Next, in step S9, if there is an instruction to change the adopted version number T from the keyboard 12, the adopted version number T stored in the RAM 3 is updated. If there is no change, the adopted version number T already stored in RAMa is retained.

At step 310, the p-tile ratio α is read from the second encoder 14 and stored in the RAM 3. p-tile ratio α
is predetermined as follows. That is, FIG. 6 is a histogram showing the statistics of any one of the color separations of MMCK. The number of pixels P. 8 and the number of pixels P that turns OFF
. F, the ratio of area (area ratio in the histogram), i.e., p-tile ratio-PaN/P OFF or p-tile ratio-P. Defined as FF/P ON.

The p-tile ratio is the total number of pixels and O by binarization.
Number of pixels P that is N (or 0FF). , l (or PO
FF), i.e. p-tile ratio-P o+i/
(P(lN+POFF) or p-tile ratio=P(IFF/(PllN+)
It may also be defined as P o□).

Next, in step 311, statistics are calculated from among the color separations of the adopted version number T1 updated in step S9 or, if there is no update in step S9, of the adopted version number T set in step S4. Select the largest color separation with the clearest outline.

In step S12, based on the p-tile ratio α read in step S10, the histogram in the area of the current partial image division frame N for the selected color separation is divided into parts, and the differential value corresponding to the boundary of the part is divided. , the differential value 2
Determined as the reference level Eth for 41i conversion, RA
Store in M3. In the example of FIG. 6, p-tile ratio-P
The histogram is divided based on OFF/(P ON+POFF).

From this histogram and the p-tile ratio, the reference level Et
The method for determining h is, for example, when you want to determine the reference level Eth so that a certain percentage of pixels in the area of the partial image partition frame N form a contour line as shown in FIG. 7, even if the differential value is Even if the distribution is biased towards the large side as shown in Figure 8 (A), or conversely towards the small side as shown in Figure 8 (B), it can be automatically calculated by simply giving the same p-tile ratio. Since the reference level Eth is determined by adjusting the reference level Eth, stable results can be obtained even when detecting the contour of a specific image that has both a gentle contour and a steep contour on the same contour due to density changes. can get.

For example, in FIG. 7, the number of pixels in the contour is A, the numbers of pixels on both sides of the contour are Av and Az, and the division ratio Ax is
/ (Ax + Av + Az) ""If you want to set it to 20%, the p-tile ratio is 80/100, which is 80%, and when the histogram is divided into 80:20 parts, the 8th
In the case of diagram (A), Eth-70, and in the case of diagram (B), Eth-70
It is th-30. However, the horizontal axis in FIG. 8 represents the relative differential value.

In step 513, within the area of the partial image division frame N, the differential value of each pixel of the selected color separation is read from the differential value table 3a in the RAM 3, and the differential value is compared with the determined reference level Eth. Binarize based on
The binary data and the data in the mask memory 7 are logically summed (OR)ed, and the result is written into the mask memory 7 again. Such 2 (unification, logical sum operation, and writing) are sequentially performed for each pixel within the area of the partial image division frame N.

In the case of the logical sum for the first selected color separation with the clearest outline, the mask memory 7 has been cleared in advance in step S3, so a binary data of only that selected color separation is written into the mask memory 7. It will be done.

The reason for calculating the logical sum is to smoothly connect the contour line detected by the area of this partial image partition frame N with the contour line detected by the adjacent partial image partition frame N before and after it, and to calculate the selected color. This is because with only the separated version, the binary data that becomes "H" (or L) may not be continuous in pixels along the entire length of the contour line within the area of the partial image division frame N. In other words, the color This is because, depending on the decomposition version, there may be pixel parts where there is almost no difference in pixel level between the inside and outside of the contour line l of the specific image (■).This point will become clearer from the explanation of the operation described later. becomes.

When sequential binary data writing for all pixels within the area of the partial image division frame N is completed, the process proceeds to step S14, and the color separation plate with the second largest statistic is selected.

In step S15, it is determined whether the total number of color separation plates selected so far has become larger than the adopted number T,
If it has not been reached, the process returns to step S12, and steps 312 to 515 are executed in the same manner as described above.

That is, for the second color separation with clear outlines,
Based on the same p-tile ratio as before, the reference level E at the same sub-image partition frame N for the second selected color separation.
The determination of th, the binarization, and the writing of the binary data after the OR processing into the mask memory 7 are sequentially performed pixel by pixel for all pixels within the area of the partial image division frame N.

In this case, when writing to the mask memory 7, the binary data is logically ORed with the binary data for the first selected color separation already stored in the mask memory 7, in other words, By combining the first and second binary data, binary data will be written to some or all of the pixel parts that were discontinuous in the first binary data, and the binary data will be written as contour data. Continuity will be improved.

If it is determined in step S15 regarding the second selected color separation plate that the total number of color separation plates selected up to that point has not yet reached the adoption number T, the process returns to step S12 again, and the third largest statistic is selected. Steps 312 to S15 are executed in the same manner as described above for the color separations. This further improves the continuity of the contour data.0 If it is a normal original image to be processed, the contour data will be divided into its partial image partition frame N
It is continuous along the entire length of the contour line l of the specific image I existing within the area. The contour data in the mask memory 7 at this time is visually represented as shown in FIG. 9(A).

When the above-mentioned processing is completed for all the color separations of the adopted version number T, the process proceeds to step S16, where binary data representing contour data is sent from the mask memory 7 to the image display adjustment device 8, and coloring processing and half-coloring processing are performed. The partial detected contour line in the partial image division frame N is re-displayed on the image display device 9 together with the specific image by performing a process of transparency or the like.

Next, the process returns to step S5, and by operating the stylus pen 11 on the digitizer 10, the adjacent second partial image partition frame N is displayed on the image display device 9 in a state that it partially overlaps the previous first partial image partition frame N. This time, the same operation as described above is performed in the second partial image division frame N. As a result, the mask memory 7 contains 1
The contour data of the th partial image partition frame N and the contour data of the second partial image partition frame N are stored.

That is, this is because the logical sum operation is performed in step S13.

Then, the partial detected contour line in the second partial image partition frame N is displayed on the image display device 9 in a state that it is continuous with the partial detected contour line in the first partial image partition frame N.

Thereafter, in the same manner, as shown in FIG. 3 (B) to (C), while sequentially moving the partial image partition frame N to the third, fourth, etc. along the outline l, Perform similar processing. Finally, processing is executed in the partial image partition frame N that partially overlaps the first partial image partition frame N.
With the above, one round of processing along contour line 2 is completed,
The image display device 9 displays the final closed-loop detection contour line in which all the partial detection contour lines are continuous.

The contour data in the mask memory 7 at the stage of FIG. 3(B) is visually represented as shown in FIG. 9(B), and the contour data in the mask memory 7 at the stage of FIG.
The contour data in the mask memory 7 at step C) is visually represented as shown in FIG. 9(C).

Then, when the operator gives an instruction to end the process from the keyboard 12, the sequence operation is ended in step S6. The instruction to end this process may be configured to be issued from the digitizer 10.

It goes without saying that the closed-loop contour data is stored in the mask memory 7 at the stage when the closed-loop detection contour line is displayed. ,
So-called filling in which all pixel groups located inside or outside of a closed loop pixel group having detected contour data as "H" (or "L") are converted to H°" (or "L") by a known method, An extraction mask can be created by electronically performing vectorization processing on the closed-loop pixel group.

The size of the partial image partition frame N can be changed by the first encoder 13, so even if areas with different density levels are intricately included, the partial image partition frame N can be changed to a smaller size. By using this method, it is possible to detect the contour data of only the specific image to be extracted.
On the other hand, if the partial image partition frame N can be made larger, the number of times the stylus pen 11 is used to specify the position of the partial image partition frame N is reduced, and workability can be improved.

Note that the shape of the partial image division frame (nozzle) N does not have to be limited to a circle, and any shape other than a rectangle can be used. Further, as for how to move the partial image division frame N, it is not necessarily necessary to move it continuously along the contour line 1, but it may be moved intermittently or it may be formed repeatedly at the same location.

However, ultimately it is necessary to cover the entire length range of the contour line P.

Further, in the present invention, since the detected contour line is logically added to the mask memory 7 and added to the mask memory 7, correction means may include erasing the entire surface of the mask memory 7 or partially by specifying the coordinates of the digitizer 10. You can make additions using straight lines and arcs by specifying the coordinates.

If the conditions of the original image to be processed are good and the outline of the specific image to be extracted is clear in just one color separation, the adopted version number T should be 1 and only that color separation should be selected. Furthermore, when the original image to be processed is monochrome, four Y memories 5Y, M memories 50 .
C memory 5c.

Only one of the K memories 5 may be used.

<Effect of the invention> According to the present invention, the following effects are achieved.

The first method is to compare the density level of a pixel with the differential value of the density level to obtain binary data, rather than the density level of the pixel.
According to the above method, even if the difference between the specific image density level and the background image density level is small, the ability to detect contour lines can be improved, and the number of changes in the reference level can be reduced, thereby improving work efficiency.

According to the second method, when the specific image is a multicolor image, processing is performed in order from color separations with clear outlines, and the outline data is logically summed with binary data for each color separation. Since it is stored as , it is possible to compensate for the decrease in detection ability caused by the difference in differential values between color separation plates.

According to the third method, the color separation plates in the second method are selected in descending order of the statistical amount indicating the dispersion of the differential value of each pixel in each partial image partition frame.
The selection can be easily automated to further improve work efficiency.

According to the fourth method, in the first or second method,
Since the reference level is determined based on the p-tile ratio in the statistics for each partial image partition frame, even if there are parts with gradual density changes and parts with steep changes on the same contour line, the The reference level can be determined automatically,
Flexibility with respect to changes in the state of the original image to be processed can be expanded.

[Brief explanation of the drawing]

1 to 9 relate to embodiments of the present invention, FIG. 1 is a schematic configuration diagram of a system implementing the image contour data creation method, FIG. 2 is a flowchart for explaining the operation, and FIG. 3 is a partial image An explanatory diagram of the sequential movement of the division frame, Fig. 4 is an explanatory diagram of the differential value of the density level of each pixel within the partial image division frame area, and Fig. 5 is an explanation of the state of the histogram that differs for each color separation. Figure 6 is an explanatory diagram of the method for determining the reference level from the histogram, Figure 7 is a diagram showing an example of the contour line of a specific image, Figure 8 is a diagram showing changes in the state of the histogram, and Figure 9 is the mask memory. FIG. 3 is a diagram illustrating contour data that is sequentially stored. ■...Specific image 2...Contour line N...Partial image division frame Eth...Reference level E length...Differential value Applicant Dainippon Screen Manufacturing Co., Ltd. Agent Patent attorney Tsutomu Sugitani No. 3 Figure 9 Figure 4 (A) 5th (A) (B) □Gourmet NaoE (B) Figure (C) CD)

Claims (4)

[Claims] (1) Displaying a gradation image including a specific image, specifying a partial image partitioning frame that includes a part of the outline of the specific image, and performing differential processing for each pixel within the partial image partitioning frame area, The differential value of each pixel is binarized based on the comparison between the differential value of the density level of each pixel and an appropriate reference level, and the binary data is stored as outline data in the partial image partition frame, and is sequentially moved along the contour line of a specific image, the same processing as described above is performed on each partial image partition frame, and the obtained binary data is sequentially stored to obtain contour data about the contour line of the specific image. How to create contour data. (2) In the method according to claim (1), when the original image to be processed including the specific image is a multicolor original image and has been color-separated into a plurality of color separation plates, a contour line is selected from among the color separation plates. One or more color separations are selected in order from the clearest one, and for each selected color separation, differential processing is performed in each partial image partition frame, and the differential value is binarized by comparing the differential value with a reference level. When the binary data obtained for each color separation plate is sequentially stored in each partial image partition frame, if there is binary data for each color separation plate obtained earlier, the logic with that binary data is calculated. A method for creating image contour data that calculates the sum and stores it. (3) In the method according to claim (2), selecting a color separation plate having a clear outline for each partial image partition frame,
A method for creating image contour data in descending order of the statistical amount indicating the variation in the differential value of each pixel within the partial image partition frame of each color separation. (4) An image contour data creation method according to claim (1) or (2), in which the reference level is determined for each partial image partition frame based on the p-tile ratio in the statistics.