JPH03258165A - Picture processing method - Google Patents

Abstract

PURPOSE:To prevent deterioration in picture quality due to jaggedness caused at an edge at binarization when a binary picture is subject to geometric conversion by deciding a threshold level for re-binarization processing properly in advance. CONSTITUTION:A database system is provided with a color scanner 1 separating a color picture being an original and outputting the color-separated picture to a magnetic disk 2, the magnetic disk 2 storing the picture data inputted from the scanner 1, and an optical disk 3 or the like registering the picture data and its cut-out mask data as data base data respectively. Then a computer 4 calculates a density at which a line close to a diagonal line and most similar to a straight line is drawn as a threshold level as to a density of the edge and decides properly the threshold level when re-binarizing processing is implemented to a cut-out mask data after geometrical conversion by means of the hyperbolic interpolation method. Thus, the deterioration in the quality of the picture due to jaggedness caused at the edge at re-binarization when the binary picture is subject to geometrical conversion is prevented.

Description

[Detailed Description of the Invention] [Industrial Field of Application] The present invention performs geometric transformation processing on a binary image by interpolation, and transforms the image data in the column direction and line direction after the geometric transformation processing. This relates to an image processing method that performs re-binarization processing by converting edges other than 2-valued images, especially when re-binarizing a binary image by geometrically converting it, jaggies that occur at the edge portions of the re-binarized image. The present invention relates to an image processing method that can eliminate deterioration in image quality caused by.

[Prior Art] Currently, in the field of plate making, layout scanner systems have been developed and put into practical use when making plates of manuscripts such as color photographs. This layout scanner system has an editing function that can output one or more images in a desired layout on one film. This type of layout scanner system is sold by many manufacturers.
This is an extremely innovative plate-making system.

Its common uses include, for example, special processing such as erasing acne, wrinkles, etc. from human images, and plate making (block collection). On the other hand, color photo printing is generally treated as a temporary process, or catalogs, pamphlets, leaflets, etc. are printed using image processing such as enlarging, reducing, rotating, etc. Or reuse by changing the crop.

Often reused. For this reason, layout scanner systems have recently been used that have an image database function in which image data is registered in advance as a database in a storage medium such as a destination disk.

By the way, in this type of layout scanner system, in addition to the original image data, cropping mask data is also registered in the storage medium as a database, and when the image data is reused or reused, the image data is cropped using the cropping mask data. processing is being carried out. When image data is subjected to processing such as enlargement, reduction, rotation, etc., such as geometric transformation processing using bilinear interpolation, etc., it is necessary to simultaneously perform similar processing on the cutout mask data. In this case, geometric transformation processing is performed on the cutout mask data by bilinear interpolation, and re-binarization processing is performed on each pixel after the geometric transformation processing using a specific threshold.

[Problem to be solved by the invention] However, the cutout mask data is a binary image,
When this binary image is subjected to scaling processing using bilinear interpolation, as shown in FIG. 4, for example, density values other than 0.255 occur at the edge portions of the image. Therefore, after scaling processing, re-binarization processing is performed using a specific threshold, but in this case, if the threshold value is not appropriate, jaggies may occur at the edges of the re-binarized image (cropped image). Put it away.

To explain this point specifically, as shown in Figure 5, when the threshold value is high, the edge line passes along the upper left trajectory, and conversely, when the threshold value is low, the edge line passes along the lower right trajectory. . As shown in Figure 6, when a 5x5 binary image is enlarged, if the threshold value is high, an edge line will appear as shown in Figure 7, and the area of 0 density will exceed the ideal edge line. This results in a shape that protrudes into the area with a density of 255.

As a result, the protruding portion (hatched area in FIG. 7) appears to be jaggy. On the other hand, if the threshold value is low, an edge line as shown in Figure 8 will result,
The area with density 255 crosses the ideal edge line and protrudes into the area with density ○. As a result, the protruding portion (hatched portion in FIG. 8) appears to be jaggy.

As mentioned above, if the threshold value when performing re-binarization processing is not appropriate, jaggies will occur at the edge portions of the re-binarized image, degrading the image quality. It is necessary to appropriately determine this, but the reality is that no concrete method has been proposed.

The present invention has been made in order to solve the above-mentioned problems, and the threshold value for re-binarization processing is appropriately determined in advance, and the An object of the present invention is to provide an image processing method capable of eliminating deterioration in image quality due to jaggies that occur in edge portions of a re-binarized image during re-binarization.

[Means for Solving the Problems] In order to achieve the above object, the present invention performs a geometric transformation process on a binary image using an interpolation method, and reproduces the image data after the geometric transformation process. In an image processing method that performs binarization processing, a certain arbitrary edge portion is identified, and the density value of the edge portion is approximately determined to draw a line closest to the diagonal and most similar to a straight line,
Using the obtained density value as a threshold, the image data after the geometric conversion process is re-binarized.

[Action] Therefore, in the image processing method of the present invention, the column direction of the image data after the geometric transformation process.

and an arbitrary edge part that is next to an edge other than the line direction, and for the density value of this edge part, find the density value that allows you to draw a line that is closest to the diagonal and most similar to a straight line,
is determined in advance as a suitable threshold,
After geometrically transforming the binary image, the image data is re-binarized. As a result, it is possible to obtain a smooth re-binarized image in which jaggies are not noticeable in edge portions.

[Embodiment] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a block diagram showing a configuration example of an image database system to which an image processing method according to the present invention is applied.

The image database system of this embodiment includes a color scanner 1, a magnetic disk 2, an optical disk 3, a graphic display 4, a magnetic disk 5, an optical disk 3, a computer 4, and an output device 5. There is.

Here, the color scanner 1 inputs a color photograph, which is a document, after color separation. Further, the magnetic disk 2 is used to store image data input from the color scanner 1.

On the other hand, the optical disc 3 is used to register image data and its cutout mask data as a database. In addition, the computer 4 has functions for performing geometric transformation processing on image data and cropping mask data by enlarging, reducing, rotating, and translating the data, that is, by bilinear interpolation, and for cropping after the geometric transformation processing. A function to re-binarize each pixel of the mask data using a specific threshold, and a function to mask the image data after the geometric transformation process using the cutout mask data after the re-binarization process. , identify any edge part that is next to the edges in the column direction and line direction of the cropping mask data after the geometric transformation process, and calculate the density at which a line closest to the diagonal line and most similar to a straight line can be drawn for the density value of this edge part. It has a function of calculating a value as the above-mentioned threshold. Further, the output device 5 includes, for example, a plotter, and the computer 4
The processed data is output as film for plate making.

Next, the operation of the image database system configured as above will be explained.

In FIG. 1, an image of a color photograph, which is a document, is manually generated by a color scanner 1, and the image data is separated into colors and temporarily stored on a magnetic disk 2.

The image stored on the magnetic disk 2 is
It is registered in the optical disc 3 as a database together with the cutout mask data. On the other hand, on computer 4,
Image data and cutout mask data are subjected to scaling processing, such as enlargement processing, that is, geometrical transformation processing by bilinear interpolation. In addition, re-binarization processing is performed on each pixel of the cropping mask data after geometric conversion processing using an appropriate threshold, and the image data after geometric conversion processing is Mask processing is performed using the cutout mask data. The cutout image data, which is data processed by the computer 4, is outputted from the output device 5 as a plate-making film.

In this case, an appropriate threshold for re-binarization processing is determined, for example, as follows. In other words, any edge part that is next to the edges in the column direction and the line direction of the cropping mask data after the geometric conversion process is identified, and the line closest to the diagonal line and most similar to a straight line is determined for the density value of this edge part. Drawable concentration 1
Directly or calculated as a threshold. This point will be specifically explained using FIGS. 2 and 3.

For example, in the case of a 2x2 matrix, the shape pattern of the edge portion in the cutout mask data in the 4-neighborhood is 4 as shown in FIGS. 2(a) to d).
Two patterns are possible (density value...255
・O). Next, when each of these shape patterns is subjected to scaling (enlargement) processing, the shape pattern (1, 1, X 11 matrix) becomes as shown in FIGS. 3(a) to 3d).

Next, among these shape patterns, the column direction.

and patterns other than the line direction, that is, Fig. 3 (a
) and (d), specify a certain arbitrary edge part, and calculate the density value V such that a line closest to the diagonal line and most similar to a straight line can be drawn for the density value of this edge part, for example, in Fig. 3 (d). ), V, -207 is experimentally calculated as a suitable threshold.

As described above, the image database system of this embodiment includes a color scanner 1 for color-separating and inputting a color photograph as an original, a magnetic disk 2 for storing image data manually inputted from the color scanner 1, and a magnetic disk 2 for storing image data manually inputted from the color scanner 1. , and its cropping mask data are registered as a database on the optical disk 3, and the image data and cropping mask data copied from the optical disk 3 onto the magnetic disk 2 are subjected to enlargement, reduction, rotation, and parallel movement processing, that is, bidirectional processing. A function to perform geometric conversion processing using linear interpolation, a function to perform re-binarization processing using a specific threshold for each pixel of the cutout mask data after geometric conversion processing, and a function to perform re-binarization processing using a specific threshold. image data,
A function to perform mask processing using the cutout mask data after the re-binarization process, to identify any edge part that is next to the edge in the column direction 2 and line direction of the cutout mask data after the geometric conversion process, and to calculate this edge part. A computer 4 has a function of calculating, as the threshold, the density value at which a line that is closest to the diagonal line and most similar to a straight line can be drawn for the density value of It is composed of

Therefore, it is possible to appropriately determine the threshold value when re-binarizing the cropped mask data after geometric transformation using the bilinear interpolation method.
To generate a smooth cutout image with inconspicuous jaggies by preventing jaggies from occurring in edge parts of a rebinarized image during rebinarization when geometrically converting cutout mask data that is a value image. becomes possible. This results in
Deterioration in the quality of image data due to jaggies after masking the image data can be eliminated, and an image database system of extremely high quality can be achieved.

In the above embodiment, the present invention is applied to an image database system, but the present invention is not limited to this.

〔Effect of the invention〕

As explained above, according to the present invention, the threshold value for re-binarization processing is determined in advance, and the threshold value for re-binarization is determined appropriately. It is possible to provide an image processing method that can eliminate deterioration in image quality due to jaggies occurring at the edge portions of a valued image.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing an embodiment of an image database system to which the image processing method according to the present invention is applied, FIGS. 2 and 3 are diagrams for explaining the operation of the embodiment, and FIG. FIGS. 5 to 8 are flowcharts for performing scaling processing and re-binarization processing on a value image, and are diagrams for explaining the relationship between the threshold value and the occurrence of jaggies. ]...Color scanner 2...Magnetic disk, 3
...Optical disc, 4...Computer, 5...Output device.

Claims (1)

[Scope of Claim] An image processing method in which a binary image is subjected to a geometric conversion process using an interpolation method, and the image data after the geometric conversion process is re-binarized, comprising: The part is identified, and the density value at which a line that is closest to the diagonal line and most similar to a straight line can be drawn is determined in advance for the density value of the edge part, and the geometric transformation process is performed using the determined density value as an appropriate threshold. An image processing method characterized in that image data is subsequently re-binarized.