JPH11196282A - Image discrimination device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To allow the device to discriminate with high accuracy whether an image is a color image or a monochromatic image. SOLUTION: Received color image data for each pixel are given to a difference calculation means 3, where a mutual difference is calculated and a maximum difference selection means selects an absolute maximum value. A pixel discrimination means 5 compares the maximum value with a threshold level to discriminate a color area pixel 6, a medium area pixel 7 or a monochromatic area pixel 8. A pixel generating means 10 increments the counts of a color pixel counter 11, a medium pixel counter 12 or a monochromatic pixel counter 11 depending on the area of a discriminated pixel. A mono-block recognition means 9 allows a monochromatic block counter 14 to count the number of pixels when monochromatic area pixels 8 are consecutive. A color noise elimination means 15 corrects color noise so as to eliminate its effect in the case that the count of the monochromatic block counter 14 exceeds a threashold level.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image discriminating apparatus for discriminating an image type in a digital color copying machine, a printing machine capable of multicolor printing, and the like. The present invention relates to an image discriminating apparatus for discriminating an area from an image.

[0002]

2. Description of the Related Art Conventionally, image data used for copying and printing in offices and the like is often a monochrome image called monochrome, and it can be said that it is not an exaggeration to say that it is almost monochrome. is there. However, in recent years,
With the spread of high-quality color copiers and printers, and the need for color printing in offices is also increasing, colorization of images handled in offices is gradually developing.

In such a color image copying machine, if a black and white image is to be copied by overlaying a plurality of color recording materials, a black character or a thin line may not be a halftone dot due to color misregistration and the spectral and distribution characteristics of ink. There is a disadvantage that it is difficult to see. Also, when considering the process of processing a color image, in addition to the problem of poor copy quality as described above, and similarly poor print quality, the color Processing as a plurality of decomposed components has the disadvantage that the processing takes a long time, and the cost is increased because an image is formed by a plurality of processes.

Here, the plurality of components are, for example, 3
There are three primary colors, R, G, and B, which are primary colors, and Y, M, and C, which are yellow, magenta, and cyan. In order to solve this drawback, it is necessary to determine whether the image is a color image containing color information or a monochrome image consisting only of monochrome information, and select an appropriate process according to the type of image. It is important to determine a color image to determine whether the image is an image or a monochrome image.

[0005] As a prior art for color image discrimination, for example, JP-A-3-270380 and JP-A-4-28.
2968. JP-A-3-270380 introduces a method of outputting a color image discrimination signal according to the number of times the color discrimination signal is output. In this prior art,
It is determined whether each pixel is a color pixel or a monochrome pixel, the number of color pixels in the image is counted, and if the count value occurs a certain number of times or more, the image is a color image. Otherwise, the image is determined to be a monochrome image.

Japanese Unexamined Patent Application Publication No. 4-282968 discloses a method of performing color image discrimination as a result based on the discrimination result for each line. In this prior art, it is determined whether each pixel is a color pixel or a monochrome pixel, and when the presence of a predetermined number or more of continuous color pixels in a given pixel order is detected, the continuous color pixels are color-blocked. If there are a predetermined number or more of color blocks in one line, the line is determined as a color line and counted. If there are a predetermined number or more of color lines in the pixel, this image is determined as a color image, otherwise, the image is determined as a monochrome image.

[0007]

Problems to be Solved by the Invention Japanese Patent Laid-Open No. 3-27038
In the prior art disclosed in Japanese Patent Application Laid-Open No. H08-282968 or Japanese Patent Application Laid-Open No. 4-282968, it is determined whether each image is a color image or a monochrome image by image determination.
Alternatively, the image is determined based on the ratio between the color area portion and the monochrome area portion. However, these methods do not consider erroneous determination at the time of pixel determination. Therefore, when erroneous determination occurs in pixel determination, the output result of pixel determination may be erroneously output.

[0008] The erroneous determination at the time of pixel determination is that a pixel is actually determined as a monochrome pixel despite being a color pixel, and conversely, it is determined as a color pixel even though it is actually a monochrome pixel. There are cases. Such erroneous determination is mainly due to the influence of color noise occurring in the monochrome edge portion and whether the pixel is a color pixel only from the density value of one pixel which is problematic in the background portion of the document or in the so-called pastel region. This is due to the way in which pixels that cannot be distinguished as monochrome pixels are handled. The color noise that occurs in the monochrome edge portion is a color shift that occurs due to a reading shift or a reading degree of an image. When this occurs, a pixel that should actually belong to the monochrome area may be recognized as a color pixel that belongs to the color area.

SUMMARY OF THE INVENTION It is an object of the present invention to provide an image discriminating apparatus capable of accurately discriminating whether an image is a color image including color information or a monochrome image including only monochrome information.

[0010]

According to the present invention, there is provided an image input means for reading an image and decomposing the image into a plurality of color components, and a color area, an intermediate area or a pixel area for each pixel based on image data obtained from the image input means. A pixel area determining means for determining which of the black and white areas the pixel belongs to, a black and white area determining means for classifying the pixels determined to belong to the black and white area by the pixel area determining means into a monochrome area and a base area, Each time a pixel determined to belong to a color area, an intermediate area, or a monochrome area appears by the area determining means and the monochrome area determining means, the color pixel counter, the intermediate pixel counter, or the monochrome pixel counter is counted by the number of occurrences. A predetermined number or more of pixels determined to belong to the monochrome area by the pixel counting means and the monochrome area determination means are continuously generated. When there is a portion, a monochrome block recognizing means for recognizing a portion where pixels belonging to the monochrome area are continuously generated as a monochrome block, and positions at both ends of the monochrome block recognized by the monochrome block recognizing means. If the pixel to be included belongs to either the color area or the intermediate area, the count value of the color pixel counter or the intermediate pixel counter is decreased by the number of pixels that are considered to belong to the area. If the pixels located at both ends of the monochrome block are pixels belonging to the background area, a count value correction unit that does not change any of the count values of the color pixel counter, the intermediate pixel counter, and the monochrome pixel counter is included. An image discriminating apparatus characterized in that:

According to the present invention, based on the image data read by the image input means and decomposed into a plurality of color components, the pixel area determining means determines, for each pixel, the pixel belonging to the color area. It is determined whether the pixel belongs to a black-and-white region or a pixel belonging to an intermediate region that cannot be said to be either a color region or a black-and-white region. Further, the pixels determined to belong to the black-and-white area are separated into a base area and a monochrome area by the black-and-white area determination means. The count value correcting unit counts the count values of the color pixel counter and the monochrome pixel counter in which the number of pixels belonging to the color area, the intermediate area, or the monochrome area is counted by the pixel counting unit by the number of pixels located at both ends of the monochrome block. If the pixels located at both ends of the monochrome block belong to the background region, the count values of the color pixel counter, the intermediate pixel counter, and the monochrome pixel counter are not changed. Based on the count values of the color pixel counter, the intermediate pixel counter, and the monochrome pixel counter,
It is possible to determine whether the image is a color image or a monochrome image.

In the present invention, the pixel area determining means determines a mutual difference value between color components of input image data when determining whether a pixel belongs to a color area, an intermediate area, or a monochrome area. The combination whose absolute value is the largest among the combinations of is selected, and the absolute value is used as a criterion,
It is characterized by being classified into three areas: a color area, an intermediate area, and a black and white area.

According to the present invention, the image data is decomposed into a plurality of color components by the image input means, and the combination having the maximum absolute value among the combinations of the mutual difference values between the color components is selected as a criterion. Color area, intermediate area or black and white area
Since the images are classified into two regions, it is possible to appropriately determine the image. In the black-and-white area, each color component is almost the same, and even if the absolute value is the largest among the combinations of the mutual difference values, the value is small and the black-and-white area is easily identified. be able to. In the color area, since there is a mutual difference value whose absolute value is considerably large in any of the combinations, it can be easily determined. If it is difficult to determine the area only by combining the mutual difference values, the area is classified as an intermediate area, so that each pixel can be easily classified into any of a color area, an intermediate area, and a monochrome area.

In the present invention, the black-and-white area discriminating means compares a minimum value of a color component in input image data with a predetermined threshold value for each pixel with respect to classification of a monochrome area and a background area. It is characterized in that it is classified based on the comparison result whether the pixel belongs to a monochrome area or a base area.

According to the present invention, the black-and-white area discriminating means includes:
The minimum value of the color component of the input image data is compared with a predetermined threshold value for each pixel. If the pixel belongs to the monochrome area, each color component should be larger than the predetermined threshold, and even if the minimum value of the color components is exceeded, the predetermined threshold will be exceeded. If the pixel belongs to the background area, each color component becomes smaller and the minimum value becomes smaller than a predetermined threshold, so that it is easy to classify the pixel as belonging to the monochrome area or the pixel belonging to the background area. can do.

[0016]

FIG. 1 shows a schematic configuration of an image discriminating apparatus according to an embodiment of the present invention. In this embodiment, it is assumed that the read color image data has three color components of Y (yellow), M (magenta), and C (cyan). The image input means 1 is, for example, a CCD
Is a color image pickup means using a color filter or the like as a light receiving element.
The three color components are given in the scanning direction. The pixel area determination means 2 includes a difference value calculation means 3, a maximum difference value selection means 4, and a pixel determination means 5. The difference value calculating means 3 calculates (YM, MC, CY) which are mutual difference values of Y, M, and C, which are color components constituting image data of each pixel, and calculates the absolute value. Take the value. The maximum difference value selecting means 4 selects three combinations of absolute values of the mutual difference values ｛| Y−M |, | M−
The combination that takes the maximum value among C |, | C−Y |} is selected as {| Y−M |, | M−C |, | C−Y |} max. The pixel discriminating means 5 determines predetermined threshold values α, β (α <β, α> 0, β> 0) and ｛| Y−M
|, | M−C |, | C−Y |｝ max, and
When ｛| Y−M |, | M−C |, | C−Y |｝ max <α, the pixel is determined to be a pixel belonging to the black-and-white region, and ｛| Y−M |, | M−C | , | C−Y |｝ max>
If β, the pixel is determined to be a pixel belonging to the color area. Α ≦ ｛| Y−M |, | M−C |, | C
If −Y |｝ max ≦ β, it is determined that the pixel belongs to an intermediate region that cannot be said to be either a monochrome region or a color pixel. The pixel discriminating means 5 discriminates a pixel belonging to the color area as the color area pixel 6, a pixel belonging to the intermediate area as the intermediate area pixel 7, and a pixel belonging to the monochrome area as the monochrome area pixel 8.

The monochrome block 8 is recognized by the monochrome block recognizing means 9 as a monochrome block in a continuously occurring portion. Color area pixel 6,
Each time one of the intermediate area pixel 7 and the monochrome area pixel 8 appears, the pixel counting means 10 counts the number of occurrences by the color pixel counter 11, the intermediate pixel counter 12, or the monochrome pixel counter 13. Pixels belonging to the monochrome block recognized by the monochrome block recognition means 9 are counted by the monochrome block counter 14.
The monochrome block recognizing means 9 recognizes an area to which the pixel at the start portion of the monochrome block and the pixel at the end portion of the monochrome block belong. The color noise removal unit 15 performs correction for removing color noise on the image of the start portion and the end portion of the monochrome block recognized by the monochrome block recognition unit 9. This correction will be described later. The color image determination means 16 determines whether or not the input image data is a color image based on the count values of the color pixel counter 11, the intermediate pixel counter 12, and the monochrome pixel counter 13, and outputs the final output means 17
And outputs a color original or a monochrome original according to the determination result. The pixel area discriminating means 2, the monochrome block recognizing means 9, the pixel counting means 10, the color noise removing means 15, and the color image discriminating means 16 are realized by a program operation of a computer device.

FIG. 2 shows the principle of the concept of discriminating a color area, an intermediate area or a black and white area based on a combination of mutual difference values of color components. This principle is based on the additive color theorem,
If Y≡M≡C, it is based on the fact that the pixel can be predicted to be achromatic. Actually, in order to adjust the color balance, weighting is performed on each color component using the positive constants k1, k2, and k3 as Y ′ = k1Y, M ′ = k2M, and C ′ = k3C, and the weighted color Pixel determination is performed using the components Y ′, M ′, and C ′.
Here, for convenience of explanation, a case without weighting will be described. For example, threshold values α and β for pixel determination are α = 2
0, β = 30, and Y =
Assuming that 30, M = 10 and C = 45, ｛|
Y−M |, | M−C |, | C−Y |｝ max is ｛| 3
0-10 |, | 10-45 |, | 45-30 |｝ max
→ 35, and the pixel can be determined as a pixel belonging to the color area by comparing with the threshold values α and β. Similarly, threshold values α and β for pixel determination are set to α = 20 and β = 30,
As input image data, Y = 30, M = 40, C
= 15, similarly, ｛| 30-40
|, | 40−15 |, | 15−30 |｝ max → 25, and by comparing with the threshold values α and β, it is possible to determine that the pixel belongs to the intermediate region.

For pixels determined to belong to the black and white area, the minimum value of each of the Y, M, and C color components ｛Y, M,
C｝ min is compared with a predetermined image background threshold value ω, and when ｛Y, M, C｝ min ≧ ω, the pixel is determined to be a pixel belonging to a black area which is a monochrome area,
When ｛Y, M, C｝ min <ω, it is determined that the pixel is a pixel belonging to the white area which is the background area.

The pixel counting means 10 shown in FIG. 1 is provided with a color pixel counter 11 and an intermediate color pixel counter 11 each time a pixel identified as a color area pixel 6, an intermediate area pixel 7 or a monochrome area pixel 8 by the pixel identification means 5 is generated. The pixel counter 12 or the monochrome pixel counter 13 is increased by the number of occurrences. This makes it possible to calculate the number of occurrences of color pixels, intermediate pixels, and monochrome pixels in the image other than the pixels belonging to the background region.

FIG. 3 shows a concept of removing the influence of color noise, which is likely to occur on a monochrome edge portion, performed by the color noise removing means 15. As a method of removing color noise, when a continuous monochrome block 20 having a predetermined length or more is detected in the order of pixels, both ends 21, 21 corresponding to a boundary between the monochrome block 20 and a color pixel, an intermediate pixel, or an image base pixel, Since there is a possibility that color noise has occurred in the pixel 22, pixels at both ends of the pixel 22 are excluded from the subject of pixel determination.

As shown in FIG. 3A, the threshold value BORDER of the block is set as a predetermined positive integer, and the number x of pixels belonging to the continuous monochrome area 23 is x ≧ BORD.
At the time of ER, it is determined that the continuous portion is the monochrome block 20. Since the pixels belonging to the boundary portions 21 and 22 of the continuous monochrome region 23 have a high possibility of erroneous determination of the region, the color noise removing unit 15 sets the pixel of the region as shown in FIG. It is excluded from the determination target, and it is determined whether or not the remaining pixels are color images.

FIG. 4 shows an overall processing procedure of the image discriminating apparatus shown in FIG. Here, for simplicity, the width of the pixel to be removed in both ends 21 and 22 of the monochrome block 20 is set to 1, and a total of two pixels are removed at both ends.

The main procedure is started from step a1,
In step a2, initial settings such as the count value of the counter are performed. At step a3, the current flag is cleared. In step a4, image data of one pixel is input. In step a5, the area to which the input pixel belongs is determined. At step a6, a color noise removal process is performed. In step a7, it is determined whether or not all the pixels have been determined. If not, the process returns to step a3. If it is determined in step a7 that all pixels have been determined, an intermediate determination process is performed in step a8, and an image is determined based on the counter value in step a9. At step a10, the main procedure ends.

FIG. 5 shows the processing when the initial setting of step a2 in FIG. 4 is performed as a subroutine. Step b
Initial setting is started from 1 and the count value CO-CNTR of the color pixel counter 11 is set to 0 in step b2. In step b3, the count value MI-CNTR of the intermediate pixel counter 12 is set to 0. In step b4,
The count value BL-CNTR of the monochrome pixel counter 13 is set to 0
Set to. In step b5, a front color flag FC-FLAG which is normally off is set to off as a flag for a color pixel at a position facing the current determination target position with the monochrome block 20 interposed therebetween.
In step b6, a front intermediate flag FM-F which is normally off is set as an intermediate pixel flag at a position facing the current determination target position across the monochrome block 20.
LAG is set to off. In step b7, a front background flag FG-FLAG, which is normally off, is set to off as a flag for background pixels at a position facing the current determination target position and the monochrome block 20 therebetween. In step b8, when a pixel that is determined to belong to the monochrome area occurs continuously in the reading order, the count value MO-PLK of the monochrome block counter 14 representing the number of continuous pixels is set to 0. The process ends at step b9.

FIG. 6 shows a process in which the current flag clear performed in step a3 of FIG. 4 is performed as a subroutine. The current flag clearing process is started from step c1. In step c2, the current color flag (CC-CC) which is used as a flag for a color pixel at the current determination target position, is normally off, and is turned on when it is determined that the current determination target pixel belongs to the color area. F
LAG) is set to off. In step c3,
A current intermediate flag C which is normally off as an intermediate pixel flag at the current determination target position, and which is turned on when it is determined that the current determination target pixel belongs to the intermediate region.
M-FLAG is set to off. In step c4, a current background flag CG-FLAG which is a flag for a background pixel at the current determination target position, which is normally off, and which is turned on when it is determined that the current determination target pixel belongs to the background region. Is set to off. In step c5, the current flag clearing process ends.

FIG. 7 shows a process when the pixel determination in step a5 in FIG. 1 is performed as a subroutine. Step d
The process of pixel discrimination starts from 1. In step d2,
It is determined whether or not the absolute value of the mutual difference value between the color components is smaller than a first threshold α. When it is determined that the combination of the difference values is not smaller than α, it is determined in step d3 whether the maximum value of the mutual difference value is larger than the second threshold value β. If it is determined that the value is larger than the threshold value β, the count value CO-CNTR of the color pixel is increased by 1 in step d4, and the current color flag CC is increased in step d5.
-Set FLAG on. If it is determined in step d3 that the value is not larger than the threshold value β, the count value MI-CNTR of the intermediate pixel is increased by one, and step d7
Sets the current intermediate flag CM-FLAG to ON. When it is determined in step d2 that the maximum value of the mutual difference value is smaller than α, it is determined in step d8 whether the minimum value of each color component Y, M, C is smaller than the third threshold value ω. If it is determined to be smaller, step d
In step 9, the current background flag CG-FLAG is set to ON. When it is determined in step d8 that the value is not smaller than the threshold value ω, in step d10, the monochrome pixel count value BL-CNTR is increased by one, and in step d11.
Increases the count value MO-BLK of the monochrome block by one. When Step d5, Step d7, Step d9, or Step d11 ends, the process of pixel determination ends in Step d12.

In the pixel discrimination in FIG. 7, Y-M-Cmax = {| Y-M |, | M-, which is a combination that is the maximum value of the absolute value of the mutual difference between Y, M, and C as input data. C |,
| C−Y |｝ max and two pixel discrimination thresholds α,
The value is compared with β to determine whether the pixel belongs to a color area, an intermediate area, or a monochrome area. For pixels that belong to the black and white area,
By comparing with the background threshold value ω, it is determined whether the pixel belongs to the white background region or the black monochrome region. When a pixel belonging to the color area or the intermediate area occurs, the corresponding color pixel counter 11 or intermediate pixel counter 12 is incremented by 1, and the current color flag CC-FLAG or the current intermediate flag CM-FLAG is turned on. . When a pixel is determined to belong to the monochrome area, the monochrome pixel counter 13 is incremented by one and the monochrome block counter 14 is incremented by one. When a pixel belonging to the background area occurs, the current background flag C
Turn on G-FLAG.

FIG. 8 shows a process for removing the color noise in step a6 of FIG. 4 as a subroutine. The process of removing color noise is started from step e1. In step e2, the current color flag CC-FLAG, the current intermediate flag CM-FLAG, and the current base flag C
It is determined whether any of the G-FLAGs is on. If any of them is on, it is determined in step e3 whether the count value MO-BLK of the monochrome block counter 14 is greater than or equal to a preset monochrome block threshold value BORDER. When the condition is satisfied,
At step e4, a flag check is performed. After the flag check in step e4, or when the condition is not satisfied in step e4, the current color flag C is set in step e5.
Change the status of C-FLAG to the front color flag FC-FL
Set to AG. In step e6, the state of the current intermediate flag CM-FLAG is changed to the front intermediate flag FM-FLAG.
Set to FLAG. In step e7, the state of the current background flag CG-FLAG is changed to the front background flag F
Set to G-FLAG. In step e8, the count value MO-BLK of the monochrome block counter 14 is set to 0. After completion of step e8 or step e2
If the condition is not satisfied in step, the process of removing color noise is ended in step e9.

In the color noise removal shown in FIG. 8, the current color flag CC-FLAG and the current intermediate flag CM-FLAG are used.
When either the FLAG or the current background flag CC-FLAG is ON, the count value MO-BLK of the monochrome block counter 14 is compared with the monochrome block threshold value BORDER, and the count value MO-BLK of the monochrome block counter 14 is compared. Is the monochrome block threshold BO
If it is equal to or greater than RDER, it is determined that color noise may have occurred at both end portions 21 and 22 of the monochrome block 20, and color noise removal is performed. When the count value MO-BLK of the monochrome block counter 14 is smaller than the monochrome block threshold value BORDER, the color noise is not removed. This is because color noise removal is applied only to the monochrome block 20 having a certain size or more because a continuous monochrome region having no more than a certain size may be an isolated point or simply noise. is there. The color noise removal is performed by correcting each counter value based on the state of each current flag and each front flag.

FIG. 9 shows the processing when the flag check in step e4 in FIG. 8 is performed as a subroutine. The flag check is started from step f1. In step f2, it is determined whether or not the front color flag FC-FLAG is on. When it is on, the count value CO-CNTR of the color pixel counter 11 is decreased by one. After step f3 or when the condition is not satisfied in step f2, it is determined in step f4 whether the front intermediate flag FM-FLAG is on.
If it is ON, the count value MI-CNTR of the weekly pixel counter 12 is decreased by 1 in step f5. After step f5 or when the condition is not satisfied in step f4, in step f6, the current color flag CC-F
It is determined whether the LAG is on. If it is determined to be on, the count value CO-CNTR of the color pixel counter 11 is decreased by 1 in step f7. After step f7 or when the condition is not satisfied at step f6, the current intermediate flag CM-FL is determined at step f8.
It is determined whether the AG is on. If it is determined to be on, the intermediate pixel counter 12 is turned on in step f9.
Is decreased by one. After step f10, if the condition is not satisfied in step f8, f1
If the flag is set to 0, the flag check process ends. The current background flag CG-FLAG and the front background flag F
When G-FLAG is ON, color noise does not exist in the background of the image in principle, and is ignored.

The on / off state of each current flag at the current pixel discrimination target position 24 becomes the state of each front flag at the time of color noise removal at the next pixel discrimination target position. Step e5 to Step e of Step 8
In 7, the current state of the current flag is set in the corresponding front flag. In step e8, the count value MO-BLK of the monochrome block counter 14 is set to 0.
Set and clear.

FIG. 10 shows a concept of setting a flag for a pixel at a position facing the portions 21 and 22 at both ends of the continuous monochrome area 23. For the current pixel determination position 24, the current color flag CC-FLAG, the current intermediate flag CM-FLAG, or the current background flag CG
-If FLAG is set, the continuous monochrome area 23
Is determined to have ended. For the pixel at the start portion 21 of the continuous monochrome area 23, the front color flag FG
-FLAG, front intermediate flag FM-FLAG or front base flag FG-FLAG is set based on the current flag.

FIG. 11 shows the processing when the intermediate determination in step a8 in FIG. 4 is performed as a subroutine. Intermediate discrimination is processing for removing color noise from pixels still remaining as monochrome blocks. Step g1
From the terminal processing determination. At step g2, the count value MO-BL of the monochrome block counter 14 is obtained.
It is determined whether or not K is equal to or greater than the monochrome block threshold BORDER. When the condition is satisfied, a flag check as shown in FIG. 9 is performed in step g3. When step g3 is completed, or when the condition is not satisfied in step g2, the termination determination procedure ends in step g4.

FIG. 12 shows the concept of termination processing. If the processing of the image data ends with the pixels at the end 25 belonging to the monochrome region as they are after the continuous pixel monochrome region 23 continues, the pixels still remaining in the continuous monochrome region 23 In other words, it is not determined whether or not to remove color noise. The determination for this part is performed as the termination determination in FIG. This process compares the count value MO-BLK of the monochrome block counter 14 at the end point with the monochrome block threshold value BORDER, determines whether or not to remove color noise, and if so, based on the state of each front flag. To perform color noise removal processing. In this case, since it is the end, the state of each current flag can be ignored.

The image is determined based on the count values of the color pixel counter 11, the intermediate pixel counter 12, and the monochrome pixel counter 13 finally obtained as a result of the above-described determination. As a method of image determination, for example, a count value of the color pixel counter 11 is compared with a predetermined threshold value,
When the count value of the color pixel counter 11 exceeds the threshold value, the image is determined to be a color image, and when the condition is not satisfied, the count value of the monochrome image counter 14 is compared with a predetermined threshold value, When the count value of the monochrome pixel counter 14 exceeds the threshold, there is a method of determining the image as a monochrome image. If neither condition is satisfied, the above-described determination result is corrected in consideration of the count value of the intermediate pixel counter 12. For example, 1/2 or 1/3 obtained by weighting the count value of the color pixel counter 11
Is compared with a predetermined threshold value, and if the total value exceeds the threshold value, the image is determined to be a color image. If all three conditions are not satisfied, the image is determined to be a monochrome image.

In the present embodiment, Y,
Although the description has been made using three components of M and C, the same is true not only in practice but also using components such as R (red), G (green), and B (blue). In the present embodiment,
Although the target pixel width for color noise removal at both ends of the monochrome block is set to one pixel (two pixels at both ends), actually, it is predicted that color noise is generated over a wide range without being limited to only these pixels. In an image, it is possible to widen the target width of color noise removal to two pixels (four pixels at both ends). According to the image discrimination as in the present embodiment, it is possible to reduce the influence on the color noise occurring near the monochrome edge, which is a problem in performing the image discrimination, and the effect on the pixels in the area which is difficult to be discriminated from only the density value. Thus, image discrimination with less erroneous discrimination can be performed. At the same time, instead of using a buffer for storing image data when removing color noise, the determination can be made by increasing or decreasing the pixel counter, so that the processing circuit can be made compact and the image data can be accessed many times many times. Time is not required, so processing can be accelerated

[0038]

As described above, according to the present invention, the numbers of pixels existing in the color area, the intermediate area and the monochrome area in the image are made to correspond to the count values of the color pixel counter, the intermediate pixel counter and the monochrome pixel counter, respectively. This makes it possible to perform image discrimination without a buffer for storing image data at the time of region discrimination. This makes the circuit configuration for performing image discrimination compact,
Appropriate determination can be made quickly.

Further, according to the present invention, a combination in which the absolute value of the mutual difference value of a plurality of color components is maximized is selected, and a classification in a color area, an intermediate area, or a black and white area is performed by comparison with a predetermined threshold value. It can be carried out.

Further, according to the present invention, pixels determined to belong to a black-and-white area are further classified into a white area which can be considered as a base of an image and a monochrome area which is a main area where color noise actually occurs. Since only the monochrome area is subjected to color noise removal, the reliability of the color noise removal processing can be improved.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a schematic electrical configuration of an embodiment of the present invention.

FIG. 2 is a diagram illustrating a concept when pixels are classified into a color area, an intermediate area, and a black and white area.

FIG. 3 is a diagram illustrating a concept of color noise removal.

FIG. 4 is a flowchart showing main processing in the embodiment of FIG. 1;

FIG. 5 is a flowchart showing an initialization process in step a2 of FIG. 4;

FIG. 6 is a flowchart showing a current flag clear process in step a3 of FIG. 4;

FIG. 7 is a flowchart showing a pixel determination process in step a5 of FIG. 4;

FIG. 8 is a flowchart showing a process of removing color noise in step a6 of FIG. 4;

FIG. 9 is a flowchart showing a flag check process in step e4 of FIG. 8;

FIG. 10 is a diagram showing flag setting states before and after a continuous monochrome area.

FIG. 11 is a flowchart showing a termination determination process in step a8 of FIG. 4;

FIG. 12 is a diagram illustrating the concept of termination processing.

[Explanation of symbols]

 Reference Signs List 1 image input means 2 pixel area discriminating means 3 difference value calculating means 4 maximum difference value selecting means 5 pixel discriminating means 9 monochrome block recognizing means 10 pixel counting means 11 color pixel counter 12 intermediate pixel counter 13 monochrome pixel counter 15 color noise removing means 16 Color image discriminating means 20 Monochrome blocks 21, 22 Both end portions 23 Continuous monochrome area 24 Pixel discrimination target position 25 End

Claims (3)

[Claims] An image input unit that reads an image and separates the image into a plurality of color components; and, based on image data obtained from the image input unit, belongs to any of a color area, an intermediate area, and a black and white area for each pixel. Pixel area determining means for determining whether a pixel belongs to a black and white area by the pixel area determining means; and a black and white area determining means for classifying pixels determined to belong to a monochrome area into a monochrome area and a background area. Pixel counting means for counting a color pixel counter, an intermediate pixel counter, or a monochrome pixel counter by the number of occurrences each time a pixel determined to belong to a color area, an intermediate area, or a monochrome area appears; If there is a portion where pixels determined to belong to the monochrome area by means continuously occur for a predetermined number or more, A monochrome block recognizing means for recognizing a portion in which pixels belonging to the monochrome area are continuously generated as a monochrome block; and pixels located at both ends of the monochrome block recognized by the monochrome block recognizing means. If the pixel belongs to any one of the intermediate areas, the count value of the color pixel counter or the intermediate pixel counter is decreased by the number of pixels that are considered to belong to that area, and the pixels are positioned at both ends of the monochrome block. The pixel to be processed is a pixel belonging to the background area, and includes a count value correction unit that does not change any count value of the color pixel counter, the intermediate pixel counter, and the monochrome pixel counter. apparatus. 2. The image processing apparatus according to claim 1, wherein the pixel area determining means determines a set of mutual difference values between color components of input image data when determining whether the pixel belongs to a color area, an intermediate area, or a monochrome area. 2. The image discrimination method according to claim 1, wherein a combination having the largest absolute value is selected during the combination, and the combination is classified into three areas of a color area, an intermediate area, and a black and white area based on the absolute value. apparatus. 3. The black-and-white area discriminating means compares a minimum value of a color component of input image data with a predetermined threshold value for each pixel with respect to classification of a monochrome area and a background area. 3. The image discriminating apparatus according to claim 1, wherein the pixel is classified as to whether the pixel belongs to a monochrome area or a background area based on the following.