JP2002027252A - Picture processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect and remove a texture with high precision without depending on periodicity. SOLUTION: An input picture is divided into a plurality of small areas (21), and the small area whose concentration diffusion and average is small is selected from among those small areas (22), and a concentration histogram is prepared by using pixels in the selected small area (23), and ground concentration is decided based on the concentration histogram (24), and the ground is removed from an input picture by using the ground concentration (25).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to an image processing apparatus for automatically determining a background removal density.

[0002]

2. Description of the Related Art Conventionally, as one of the background removal methods, a histogram of image density is created by sampling at predetermined intervals in the main scanning and sub-scanning directions, and the frequency of the histogram is searched from the high density side. There is a method of calculating the background removal density based on the density value that first exceeds the value (see Japanese Patent No. 2868693).

[0003]

In the above-mentioned method, since sampling is performed at a predetermined interval, there is a possibility that, for example, the cycle of a halftone image matches the predetermined interval. In such a case, since the density of the halftone image becomes the threshold value for background removal, the density less than the threshold value is removed, and the image quality of the halftone image is degraded.

[0004] The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to provide a method that does not depend on periodicity.
An object of the present invention is to provide an image processing device that detects and removes the background with high accuracy.

[0005]

According to the present invention, as in the conventional method, the frequency of the histogram is searched from the high density side, and the background removal density is obtained based on the density value that first exceeds a predetermined value. The method for obtaining the histogram is different from the conventional method. That is, instead of sampling at predetermined intervals, the image is divided into a plurality of small areas, and a density histogram is created using pixels in the small areas whose average and variance of the small areas are equal to or less than a predetermined value. .

[0006]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be specifically described below with reference to the drawings.

FIG. 2 is a diagram showing a configuration of an image processing apparatus provided with a background removal unit according to the present invention. The image input unit 1 inputs an image such as a document and divides the image into three components of RGB. The scanner gamma unit 2 converts the RGB depending on the scanner into the standard RGB. At this time, light / dark inversion is also performed. Therefore, (R, G, B) = (0, 0, 0) is white, and (R, G, B)
B) = (255, 255, 255) becomes black.

The background removing unit 3 removes background stains on the image. The color correction unit 4 converts the color system RGB into the print system Y
Convert to MCK. The printer gamma unit 5 uses the standard YM
CK is converted to YMCK depending on the printer. An image output unit 6 such as a printer outputs an image to paper or the like.

FIG. 1 shows a detailed configuration of the background removing unit.
The small area dividing unit 21 divides the RGB data into small areas for each of the RGB planes. The small area selection unit 22 determines whether or not the divided area is suitable for detecting the background density. The histogram creating unit 23 creates a density histogram using the pixels of the selected small area. The background density determination unit 24 determines the background density based on the created histogram. The background removal unit 25 using the background density uses the input RG based on the background density calculated in the previous stage.
The background of the B data is removed.

FIG. 3 shows a detailed configuration of the small area selecting section.
The small area selection unit includes a density average calculation unit 31 that calculates the average of the density for each small area, a density variance calculation unit 32 that calculates the variance of the density for each small area, and a histogram based on the density average and the density variance. The small area determination unit 33 determines whether the area is a small area to be used for creation.

The average and the variance of the density are calculated for each small area, and the small area determination unit 33 determines that the density average of the small area is smaller than the threshold th1 and the density variance is smaller than the threshold th2 in all of the RGB planes. The small area is selected so as to be used for the subsequent generation of the density histogram, and otherwise, the small area is selected so as not to be used for the subsequent density histogram. Then, the small area determination unit 33 passes selection information as to whether or not the area is a small area to the histogram creation unit 23.

FIG. 4 shows an example of a density histogram. The horizontal axis represents the density, and the vertical axis represents the number of pixels of the density. The density histogram can be created by using all the pixels in the selected small area, or by averaging the pixel density of the selected small area and creating a histogram of the density average in the small area. May be used. In the former case, the total number of pixels is the number of pixels in the selected small area, and in the latter case, the total number of pixels is the number of selected small areas.

FIG. 5 shows the structure of the background density determining section. The background density determination unit includes an initial value setting unit 41 and a density condition determination unit 42. First, the initial value setting unit 41 sets the background density to the initial value th3, and the density condition determination unit 42 sets the density as the background density if density <th3 and the number of pixels of the density> th4.

If the above conditions are not met, the concentration is set to 1
Reduce the density <th3 and the number of pixels of that density> th4
Check if it is. If this condition is not met, the density is decremented to 0, the number of pixels at that density is calculated, and the comparison between the number of pixels and the threshold th4 is repeated.

FIG. 6 shows the input / output characteristics of the background removal unit using the background density. Hereinafter, the density of pixels input to the background removal unit 25 is referred to as a background removal input density (hereinafter, in), and the density of pixels output from the background removal unit is referred to as a background removal output density (hereinafter, out). When the background removal input density is higher than th3 described in FIG. 5: background removal output density out = background removal input density in When the background removal input density is lower than the background density described in FIG. 5: background removal output density out = 0 When the background removal input density is equal to or higher than the background density and is equal to or less than th3: The background removal output density out = {th3 / (th3-background density)} (in-background density).

In the example of the background removing section shown in FIG.
A configuration is adopted in which a density histogram is created independently for each B, a background density is determined for each, and a background removal is performed using each of the background densities, but the present invention is not limited to this. For example, before the small area dividing unit, luminance is obtained from RGB (for example, Y = R + 2G + B), the luminance plane is divided into small areas, the small areas are selected, and a luminance histogram of the selected small areas is created. Alternatively, the background density may be determined from the histogram, and the background may be removed based on the background density.

[0017]

As described above, according to the present invention, only a small area determined to be a background part having a stable density is selected, and pixels are collected from those small areas to obtain a histogram of the pixel density. Is generated, and the background density level is detected on the basis thereof, so that the background density can be accurately detected.

Further, only the small regions determined to be the background portion having a stable density are selected, the average density of the small regions is obtained, a histogram of the average density is created, and the background density is determined based on the histogram. Since the level is detected, the background density can be detected accurately and at high speed.

[Brief description of the drawings]

FIG. 1 shows a configuration of a background removing unit of the present invention.

FIG. 2 shows an image processing apparatus provided with a background removal unit of the present invention.

FIG. 3 shows a configuration of a small area selection unit.

FIG. 4 shows an example of a density histogram.

FIG. 5 shows a configuration of a background density determination unit.

FIG. 6 shows input / output characteristics of a background removal unit using background density.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Image input part 2 Scanner gamma part 3 Background removal part 4 Color correction part 5 Printer gamma part 6 Image output part 21 Small area division part 22 Small area selection part 23 Histogram creation part 24 Background density determination part 25 Background using background density Removal unit

Continued on the front page F term (reference) 5B057 AA11 BA02 BA30 CA01 CA08 CA12 CA16 CB01 CB08 CB12 CB16 CC02 CE02 CE17 CE20 CH08 DA08 DA17 DB02 DB06 DB09 DC23 5C077 MP08 PP15 PP25 PP46 PP54 PP61 PP68 PQ08 PQ19 PQ20

Claims (4)

[Claims] A means for dividing an input image into a plurality of small areas; a means for selecting a small area having a stable density from the plurality of divided small areas; and each of the selected small areas Means for creating a density histogram using the middle pixels;
An image processing apparatus comprising: means for determining background density based on the histogram; and means for removing background from the input image based on the background density. 2. A means for dividing an input image into a plurality of small areas, a means for selecting a small area having a stable density from the plurality of divided small areas, and each of the selected small areas Means for generating a histogram of the average density, means for determining the background density based on the histogram, and means for removing the background from the input image based on the background density. An image processing apparatus characterized by the above-mentioned. 3. The image processing apparatus according to claim 1, wherein when selecting the small area in which the density is stable, the selection is performed based on the variance and average of the density in the small area. 4. The image processing apparatus according to claim 3, wherein a small area in which the variance of the density in the small area is small and the average of the density in the small area is small is selected.