JP2000307844A - Automatic trap processor, device for detecting trap processing required location and device for detecting trap processing omission - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an automatic trap processor capable of automatically performing trap processing to image data to be printed, a trap processing required location detecting device that automatically detects a trap processing required location and a trap processing omission detecting device that detects trap processing omission. SOLUTION: An input operating means 1 designates the intensity of a basic color and a trap processing range, and subsequently, an external storage means 2 reads a processing object image. Next, a trap object pixel deciding means 6 defines color intensity on the basis of the intensity of the basic color and the density of the basic color, makes a pixel existing within the trap processing area on the read processing object image an pixel of interest, compares the color intensity of the interest pixel with the color intensity of ambient pixels existing within a prescribed range from the pixel of interest and decides whether the pixel of interest is a pixel (trap object pixel) that should be subjected to trap processing according to this comparison results. Then, an image changing means 7 performs trap processing by adding the color components of the ambient pixels, whose color configuration is different to the trap object pixel.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an automatic trap processing apparatus capable of automatically performing a trap process in which a gap is left at a color change so that a background color does not appear when performing multi-color printing. The present invention relates to a trap processing necessary portion detecting device for automatically detecting a trap processing necessary portion, and a trap processing leak detecting device for detecting a trap processing leak.

[0002]

2. Description of the Related Art In the case of performing multicolor printing, if printing misregistration occurs during printing, a gap may be left at a color change and a base color may appear. In particular, when printing is performed on a film that is frequently used for packaging materials, the film expands and contracts, and thus misregistration easily occurs. In the plate making process, adjacent colors are slightly overlapped with each other (called “overlapping process”), or the color of the background is changed to the color of the table so that the color of the background does not appear even when such misregistration occurs. Processing such as slightly shaving the periphery of the base color is performed so as not to protrude further outside (called “negation processing”). Such processing is generally called “trap processing”.

Conventionally, when performing a trapping process, the location of the trapping process (hereinafter referred to as a “trapping location”), the color of the trapping process, the width of the trapping process, and the like are determined by examining the combination of colors in the relevant area. Skilled plate-making workers themselves make judgments.

[0004]

However, the determination of the trap location, the color to be trapped, the width of the trapping process, and the like for a complicated picture requires a high work load and requires a high level of skill. In addition, since there is no target to be a correct answer, there is a variation in the quality among the workers, and human errors such as oversight are likely to occur. In addition, series products (eg:
In the case where tasks such as creating 12 types of the same item for each constellation) are assigned to each operator, the judgment is different depending on each operator, and therefore, a difference is generated in completed data. In addition, even if the same operator has been working for some time, the same operator may have different results. In this case, despite being the same item,
There is no sense of unity as a product. SUMMARY OF THE INVENTION In view of the above, the present invention provides an automatic trap processing device capable of automatically performing a trap process on image data to be printed, and a trap process required portion detection for automatically detecting a trap process required portion. An object of the present invention is to provide an apparatus and a trap processing omission detection device that detects trap processing omission.

[0005]

In order to solve the above-mentioned problems, according to the first aspect of the present invention, a range of peripheral pixels for processing a certain pixel of interest and an intensity of a basic color of an image to be processed are set. Input operation means, means for reading the image to be processed, and color intensity determined by the intensity and density of the basic color, and for the image to be processed, the color intensity of a pixel of interest and the pixel of interest A trap target pixel determining unit that determines whether the target pixel is a trap target pixel by comparing the color intensity of peripheral pixels within the set range with the target pixel. An automatic trap processing device is provided which has an image changing means for adding a color component of the image processing apparatus and an output means for outputting an image changed by the image changing means. In the invention according to claim 1, in particular,
Define the color intensity required by the intensity and density of the basic color,
The target pixel on the processing target image is compared with the color intensities of peripheral pixels within a width set from the target pixel, and based on the comparison result, it is determined whether to perform the trap process on the target pixel, Since the color components of the peripheral pixels are added to the pixels determined to be trapped, it is possible to determine whether or not to perform trapping in consideration of the intensity and density of the basic color type. It is possible to perform an optimal trap process.

According to the second aspect of the present invention, input operation means for setting a range of peripheral pixels for performing processing on a certain pixel of interest, intensity of a basic color of an image to be processed, and means for reading the image to be processed And the color intensity determined by the intensity and density of the basic color, and for the image to be processed, the color intensity of a certain pixel of interest and the colors of peripheral pixels within the set range from the pixel of interest A pixel to be trapped by determining whether the pixel of interest is a pixel to be trapped by comparing the intensity with the pixel to be trapped, an image changing unit to assign a specific emphasis color to the pixel to be trapped, and an image changing unit. And an output unit for outputting a captured image. According to the second aspect of the present invention, in particular, the color intensity determined by the intensity and density of the basic color is defined, and the color of the target pixel on the processing target image and the colors of the peripheral pixels within the width set from the target pixel are defined. The intensity is compared, and based on the result of the comparison, it is determined whether or not to perform the trapping process on the target pixel, and the emphasis color is assigned to the pixel determined to be trapped. It is possible to determine whether or not to perform trap processing in consideration of the intensity and density of various color types, and it is possible to easily detect a portion requiring trap processing.

According to the third aspect of the present invention, input operation means for setting a range of peripheral pixels for processing a certain pixel of interest and an intensity of a basic color of the trapped image;
Means for reading the trapped image, color intensity determined by the intensity and density of the basic color, and the color intensity of a certain pixel of interest, and A pixel to be trapped which determines whether or not the pixel of interest is a pixel to be trapped by comparing the color intensities of the peripheral pixels within the trapped pixel, and an image for assigning a specific emphasized color to the pixel to be trapped A trap processing leak detection device having a changing unit and an output unit for outputting an image changed by the image changing unit is used. Claim 3
In the invention described in (1), in particular, the color intensity obtained by the intensity and density of the basic color is defined, and the color intensity of the target pixel on the trapped image and the peripheral pixels within the set width from the target pixel are defined. Based on the comparison result, it is determined whether or not to perform the trap processing on the target pixel, and the emphasis color is assigned to the pixel determined to be trapped. Taking into account the intensity and concentration of the type, it is possible to determine whether or not it is a place where trap processing should be performed, and it is possible to easily detect trap processing omission.

[0008]

Embodiments of the present invention will be described below in detail with reference to the drawings. FIG. 1 is a functional block diagram showing the configuration of an embodiment of the automatic trap processing apparatus according to the present invention. As shown in FIG. 1, the automatic trap processing apparatus includes an input operation unit 1, an external storage unit 2, an arithmetic processing unit 3, a display unit 4, and an output unit 5.

The input operation means 1 has a function of setting parameters for trap processing to be performed on the arithmetic processing unit 3 and instructing the execution, and is realized by a mouse, a keyboard, or the like. The external storage unit 2 stores an image to be subjected to a trapping process and an image after the trapping process, and stores various information generated in the processing process as needed. it can. The arithmetic processing device 3 includes a trap target pixel determining unit 6 and an image changing unit 7, and has a function of performing a trap process on an image to be processed. The arithmetic processing device 3 is realized by a CPU and a memory of a personal computer or a workstation, and the trap target pixel determining means 6 and the image changing means 7 therein can be realized by installing a dedicated program in a computer or the like. The display means 4 displays the processing target image read from the external storage means 2 into the arithmetic processing device 3, the image after the trap processing, and other necessary information.
This is realized by an RT monitor or the like. The output means 5 is for outputting trapped images in various formats, and various types of printers, MOs, networks and the like can be used.

Next, referring to the flowchart of FIG.
The processing operation of the automatic trap processor shown in FIG. First, in step S1, parameters necessary for performing a trap process from the input operation means 1 are set. There are mainly three parameters to be set: basic color intensity, trap processing range, and trap width. At the time of parameter setting, the contents as shown in FIG.

FIG. 3A shows a basic color intensity setting screen. The basic color intensity indicates the color intensity when printed at the same density. In the example shown in FIG.
Up to eight colors can be used, and a basic color to be used and its basic color intensity can be set by an operator according to the printing order. In the example of FIG. 3A, the image to be processed is C
(Cyan), M (Magenta), Y (Yellow), K (Black) are used, and the basic color intensity is C = 0.6, M
= 0.3, Y = 0.1, and K = 1.0. The larger the value, the deeper the color, indicating that K is the darkest and Y is the lightest.

FIG. 3B shows a screen for setting a trap processing range and a trap width. The trap processing range is a range in which a trap process is performed on a processing target image. If the trap processing range is not set, the entire area of the processing target image is set as the trap processing range. However, this device can set the trap processing range if you want to partially process under conditions different from the others, or perform partial processing, or conversely, do not perform processing. It has become. By specifying the necessary range, it is obvious that there is no need for trap processing that is the same color area and that it does not touch the image area with a different color at all, or to perform trap processing like a small character As a result, it is possible to omit a place where it is better not to perform a trapping process that results in another color. As shown in FIG. 3B, in the present apparatus, this trap processing range can be specified by a numerical value. Therefore, the X and Y coordinate values at the lower left end and the X and Y coordinate values at the upper right end of the trap processing range are designated by inputting them into the rectangular numerical value input area shown in FIG. 3B. In addition, a plurality of trap processing ranges can be specified for one processing target image. The trap width is a width setting for performing the trap processing, and the trap processing is performed by the width set here. The trap width can be set in units of millimeters in a rectangular numerical value input area as shown in FIG. 3B so that the operator can intuitively designate the printed matter on which the trap processing is finally performed. ing. Here, this trap width is also a width that determines the range of peripheral pixels to be compared with the target pixel. The target pixel and peripheral pixels will be described later. When a plurality of trap processing ranges are set, the trap width can be set for each trap processing range, or can be set to be the same for the entire processed image.

The specified trap processing range is shown in FIG.
It is displayed on the screen as shown in (c). In FIG. 3C, the outer rectangle indicates the processing target image, and the inner shaded area indicates the trap processing range. The example of FIG. 3C shows a state where three trap processing ranges are specified. The display contents shown in FIGS. 3A, 3B, and 3C may be simultaneously displayed on the display unit 4 or may be separately displayed.

Next, in step S2, an instruction to read an image to be processed is issued by the input operation means 1. Then, the processing target image is read from the external storage unit 2 into the arithmetic processing unit 3. The external storage means 2 previously stores processing target image data edited by editing software such as draw software, photo retouching software, and layout software having a function of editing composition data. The processing target image data stored in the external storage unit 2 may be in a vector data format such as PostScript or EPS, or may be in a raster data format. If the processing target image is in the vector data format at the time of reading, the read processing target image is subjected to RIP expansion and converted into a raster data format. On the other hand, if the read processing target image is raster data, the processing is performed in the same format.

In step S3, the trap target pixel determining means 6 determines a trap target pixel according to the set parameters. The trap target pixel is a pixel whose pixel value is actually changed for the trap processing. This processing is performed by paying attention to a certain pixel of interest and comparing the pixel of interest with surrounding pixels around the pixel of interest. Here, the relationship between the target pixel and the peripheral pixels in the processing target image will be described with reference to FIG. In FIG. 4, a mark indicates a pixel of interest, and a mark indicates a peripheral pixel.
A circle centered on the target pixel is a circle having a radius equal to the set trap width. For example, in step S1, when the trap width is set to 0.2 mm and the resolution of the processing target image is 300 dpi, as shown in FIG. Become. Of these, the central pixel is the pixel of interest, and the remaining 24 pixels are peripheral pixels.

Next, a description will be given of a determination condition for determining a trap target pixel using the above noted pixel of interest and surrounding pixels. First, when one of the following three conditions is satisfied, the target pixel is not a trap target pixel. (1) When the color of the target pixel is transparent, that is, when the values of all color components are 0. (2) A case where white is included as a color component, and the color of the pixel of interest is not only the value of the white component is 0 but all other color components are 0. (3) The pixel of interest and all peripheral pixels have a value of 0 other than the white component
Not have common color components.

If none of the above three conditions is met and there is at least one peripheral pixel having a lower color intensity than the pixel of interest,
The target pixel becomes a trap target pixel. Here, the color intensity is obtained by multiplying the intensity of the basic color set in step S1 by the density. For example, C = 0.6,
The relationship between the color configuration and the color intensity when M = 0.3, Y = 0.1, and K = 1.0 is as follows.

C100% → 0.6 = 0.6 × 100% C50%, M100% → 0.6 = 0.6 × 50% + 0.
3 × 100% C100%, M100%, Y100% → 1.0 = 0.6 × 100% +
0.3 x 100% + 0.1 x 100%

Here, a specific example will be described. For example, let us consider a case where a pixel at a position shown in FIG. 5A is set as a target pixel in an image including an image area of 100% C and an image area of 100% M. FIG. 5 (a)
, The left side of the central bold line is an image area of 100% C,
The right side shows an image area of M100%. in this case,
The value of the target pixel is C100%, and M10 is within the comparison range.
It will include 0% of peripheral pixels. Since the color intensity of the C100% pixel is 0.6 and the color intensity of the M100% pixel is 0.3, there is a peripheral pixel having a lower color intensity than the target pixel. It becomes a trap target pixel. When processing is performed with the entire image shown in FIG. 5A as a trap processing range, each pixel in two columns shaded in FIG. 5B is a trap target pixel. Trap target pixel determination processing as described above is performed using all the pixels within the trap processing range designated in step S1 as the target pixel. When the trap target pixels within the trap processing range are determined, the process proceeds to step S4.

In step S4, the image changing means 7 changes the pixel value of the trap target pixel. this is,
This is performed by adding a color component of a peripheral pixel having another color component to the pixel value of the trap target pixel. For example, FIG.
In the case of (b), the original pixel value of the trap target pixel is C
Since the pixel value of the peripheral pixel having another color component is M100%, the pixel value of the trap target pixel is:
It is changed to C100% + M100%.

Here, a case where there are two or more types of peripheral pixels having a lower color intensity than the pixel of interest within the determination range will be described. In this case, the target pixel is affected by peripheral pixels that are closer to the target pixel. Further, the color intensities of the peripheral pixels closer to the target pixel and the peripheral pixels farther from the target pixel are compared, and the color intensity of the peripheral pixel farther than the color intensity of the closer peripheral pixel is compared. If it is strong, even if the color intensity of the distant peripheral pixel is weaker than the color intensity of the pixel of interest,
The distant peripheral pixels do not affect the target pixel. For example, in a processing target image having three image areas as shown in FIG. 6, the image area A is 100% C, the image area B is 100% M, and the image area C is 100% Y. Assuming that the ink intensities are C = 0.6, M = 0.3, and Y = 0.1, the color intensities of the image areas A, B, and C are 0.6, 0.
3, 0.1.

Here, comparing the distance between the target pixel and the image area B and the image area C, the image area B is closer, so that the color intensity of the target pixel and the peripheral pixels on the image area B are compared. Will be The color intensity of the pixel of interest on the image area A is 0.
6. The color intensity of the peripheral pixels on the image area B is 0.3,
Since the color intensity of the target pixel is higher, the image area B affects the target pixel. Next, a comparison is made for the farther image area C. The color intensity of the peripheral pixels on the image area C is 0.1, and the color intensity of the pixel of interest in the image area A is 0.1.
6. Since the color intensity of the peripheral pixels of the image area B is smaller than 0.3, the image area C also affects the target pixel. As a result, the pixel of interest in the image area A is
And the trapping process under the influence of the image area C, the result is C100% + M100% + Y100%.

Next, in the processing target image shown in FIG.
A case where the values of the image area B and the image area C are reversed will be described. In this case, the image area A is 100% C, the image area B is 100% Y, and the image area C is 100% M. That is, the color intensities of the image areas A, B, and C are each set to 0.
6, 0.1 and 0.3. At this time, the color intensity of the image area B closer to the target pixel is 0.1, which is lower than the color intensity 0.6 of the target pixel, so that the image area B affects the target pixel. The image area C farther from the target pixel has a color intensity of 0.3, which is lower than the color intensity 0.6 of the target pixel, but is larger than the color intensity 0.1 of the image region B. It will not affect the pixels. The same theory is applied to the case where there are three or more image areas other than the pixel color of interest in the comparison range.

In step S4, the image changed by the image changing means 7 is output from the processing unit 3 as a processed image. Although various output forms are conceivable, the most common method is to store the data in the external storage means 2. Further, the output means 5 such as a printer can output in the form of paper, film, or the like.
When a network is connected as above, it is also possible to transmit to another.

Although the embodiments of the present invention have been described above, the present invention is not limited to the above embodiments, and various modifications are possible. For example, in the above embodiment, the trapping process is performed by directly adding another color component to the trapping target pixel by the image changing unit 7, but the trapping process is not directly performed and used for another purpose. Is also possible. For example, for a trap target pixel,
By unconditionally assigning a conspicuous color such as M (magenta) 100% and displaying it on a screen or outputting it to a printer, it is possible to manually specify a necessary portion for trap processing. In this case, what is output to the printer is
It becomes a trap processing instruction. In addition, it is also possible to detect the omission of the trap processing by detecting the trap target pixel in the trapped image instead of the processing target image and highlighting the detected image. Further, in the above embodiment, the determination of the trap target pixel is determined based on the strength of the color intensity. However, in the case where the color intensities are the same although the color configurations are not the same, the printing order is set as the priority, Alternatively, it is also possible to perform the processing on the assumption that the color having the basic color with the smaller number of the printing order has higher color intensity. Also,
In the above embodiment, the setting of the trap processing range in step S1 is performed by directly inputting a numerical value. However, the image to be processed is read in advance, displayed on the display unit 4, and dragged on the screen with a mouse. It is also possible to set. The image to be processed is often created with commercially available drawing software, but the device can be used to specify the area on this screen and then receive the trap processing area as numerical information. It is. Also, in the above embodiment, FIG.
Although the trap processing range is set as a rectangular area as shown in (1), it is possible to specify the trap processing area in various shapes other than a rectangle, such as a polygon, an ellipse, and the like.

[0026]

As described above, according to the automatic trap processing apparatus of the present invention, the color intensity obtained from the intensity and density of the basic color is defined, and the target pixel on the image to be processed and the target pixel are determined. The color intensities of the peripheral pixels within the set width are compared, and based on the comparison result, it is determined whether or not to perform the trapping process on the target pixel. Since the color components of the peripheral pixels are added, it is possible to determine whether or not to perform the trap process in consideration of the intensity and density of the basic color type, and it is possible to perform the optimal trap process. . Further, according to the trap processing necessary portion detecting device of the present invention, the color intensity obtained by the intensity and density of the basic color is defined, and the target pixel on the processing target image and the target pixel are within the width set from the target pixel. The color intensities of the peripheral pixels are compared, and based on the result of the comparison, it is determined whether or not to perform the trap processing on the target pixel, and the emphasis color is assigned to the pixel determined to be subjected to the trap processing. Therefore, it is possible to determine whether or not to perform the trap processing in consideration of the intensity and density of the basic color type, and it is possible to easily detect a portion requiring the trap processing. Further, according to the trap processing omission detection device of the present invention, the color intensity obtained by the intensity and density of the basic color is defined, and the target pixel on the trapped image and the target pixel are within the width set from the target pixel. The color intensities of the peripheral pixels are compared, and based on the result of the comparison, it is determined whether or not to perform the trap processing on the target pixel, and the emphasis color is assigned to the pixel determined to be subjected to the trap processing. So, considering the intensity and density of the basic color type,
It is possible to determine whether or not it is a place where trap processing should be performed, and it is possible to easily detect omission of trap processing.

[Brief description of the drawings]

FIG. 1 is a configuration diagram showing one embodiment of an automatic trap processing apparatus of the present invention.

FIG. 2 is a flowchart showing a processing operation of the automatic trap processing device of the present invention.

FIG. 3 is a view showing a parameter setting screen in step S1 of the flowchart in FIG. 2;

FIG. 4 is a diagram showing a relationship between a target pixel, peripheral pixels, and a trap width.

FIG. 5 is a diagram for explaining trap target pixel determination processing in step S3 of the flowchart in FIG. 2;

FIG. 6 is a diagram for explaining trap target pixel determination processing when there are two or more types of peripheral pixels having a lower color intensity than a target pixel.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 ... Input operation means 2 ... External storage means 3 ... Arithmetic processing unit 4 ... Display means 5 ... Output means 6 ... Trap object pixel determination means 7 ... Image change means

Continued on the front page F-term (reference) 2H084 AE06 AE07 AE10 CC18 5B057 AA01 BA06 CA01 CB01 CC03 CE08 CE10 CE16 DA16 DB06 5C076 AA02 AA12 BA02 BA03 BA04 BA05 BA06 5C079 HA11 HB03 KA03 LA10 LA39 LA40 LB12 MA05 MA07 MA19 BA08 EA33 EA37 FA41

Claims (3)

[Claims] 1. An input operation means for setting a range of peripheral pixels for performing processing on a certain pixel of interest, an intensity of a basic color included in an image to be processed, a means for reading the image to be processed, and an intensity of the basic color. And the color intensity determined by the density and comparing the color intensity of a certain pixel of interest and the color intensity of peripheral pixels within the set range from the pixel of interest with respect to the processing target image. A trap target pixel determining unit that determines whether the target pixel is a trap target pixel, an image changing unit that adds a color component of the peripheral pixel to the trap target pixel, and an image changed by the image changing unit. And an output unit for outputting the data. 2. An input operation means for setting a range of peripheral pixels to be processed with respect to a certain pixel of interest, a basic color intensity of an image to be processed, a means for reading the image to be processed, and an intensity of the basic color. And the color intensity determined by the density and comparing the color intensity of a certain pixel of interest and the color intensity of peripheral pixels within the set range from the pixel of interest with respect to the processing target image. A trap target pixel determining unit that determines whether the target pixel is a trap target pixel, an image changing unit that assigns a specific enhancement color to the trap target pixel, and an output that outputs an image changed by the image changing unit. Means for detecting a portion required for trap processing. 3. An input operation means for setting a range of peripheral pixels to be processed for a pixel of interest, an intensity of a basic color of the trapped image, a means for reading the trapped image, and the basic color. Define the color intensity determined by the intensity and density of the trapped image, the color intensity of a certain pixel of interest, and the color intensity of peripheral pixels within the set range from the pixel of interest, A trap target pixel determining unit that determines whether the target pixel is a trap target pixel by comparing, an image changing unit that assigns a specific highlight color to the trap target pixel, and an image changed by the image changing unit. Output means for outputting the trap processing leakage detection device.