JPH0490676A - Color picture processor - Google Patents

Abstract

PURPOSE:To correctly decide the colored/colorless state of an input color signal by deciding the colored/colorless state of the input color signal and controlling a deciding reference corresponding to the number of picture elements having intermediate chroma included in the input color signal. CONSTITUTION:An automatic color/monochromatic original discriminating device is composed of a scanner 101, YIQ conversion part 102, picture element discrimination part 103, original discrimination part 104, picture processing part 106, display 107, facsimile transmission part 108, printer 109, intermediate chroma picture element counter part 110 and CPU 111. In this case, the colored/ colorless state of the input color signal is decided and corresponding to the number of picture elements at the intermediate chroma included in the input color signal, the deciding reference is controlled. Thus, the colored/colorless state of the input color signal can be correctly decided.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a color image processing apparatus such as a color copying machine, a color scanner, a color facsimile, and more particularly to a color image processing apparatus having a function of discriminating color from black and white. It is.

[Conventional technology]

In conventional systems for reading color originals, chromatic/achromatic is determined using the ratio of three components of the three primary colors (RGB, XYZ, etc.) of an input image signal. For example, if the input levels of the three primary colors are similar, it is determined that the color is achromatic, and if the levels vary, it is determined that the color is chromatic. A technique is known in which this pixel-by-pixel determination is repeated for all pixels of the document, and if a chromatic pixel exists, the document is colored, and conversely, if there is no pixel, the document is determined to be black and white.

[Problem that the invention is trying to solve]

However, in the above-mentioned conventional technology, when the reading accuracy of the color sensor for image input is poor, pixels around black characters in the input image are often incorrectly determined to be chromatic. For this reason, there is a problem in that even though the original is black and white, it is mistakenly determined to be a color original. In addition, there were cases where incorrect judgments were made when the background of the document had a light color.

There are also the following problems. For example, if we consider a document in which black characters are printed on a color background with a saturation distribution in the shaded area in FIG. 11, we would like to conclude that this is a white layer document. Furthermore, if there is a color document with low saturation that has a saturation distribution in the shaded area in FIG. 11, this document should be determined to be a color document. It is extremely difficult to distinguish between documents with such low saturation. If a black and white original is misidentified as a color original, the following problems will occur.

In the case of a color copying machine, when a black and white document is copied by overlapping color inks (CMY), characters, lines, and halftone dots become hard to see due to color shift and differences in the spectral characteristics of the inks. In the case of color facsimile, in addition to the above-mentioned drawback of poor print quality, there is also the drawback that, even though the original is black and white, sending three primary colors takes time to transmit and increases communication costs.

SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a color image processing device that eliminates the drawbacks of the prior art described above and can accurately determine whether an input color signal is chromatic or achromatic.

[Means and operations for solving the problems] In order to solve the above problems, the image processing device of the present invention includes means for determining whether an input color signal is chromatic or achromatic, and an intermediate color included in the input color signal. and a control means for controlling the determination criteria of the determination means in accordance with the number of pixels at a given time.

〔Example〕

(Principle of the present invention) A document is read from a color scanner and the data is transferred to the NT.
It is converted into SC RGB, and further converted into brightness data Y and chromaticity data ■ and Q. Figures 6 and 7 are graphs of IQ.

FIG. 6 shows the distribution when a monochrome original is read, and FIG. 7 shows the distribution when a color original is read. It can be seen that when a black and white document is read, the distribution is near the origin, and when a color document is read, the distribution is far from the origin. Therefore, the origin (■=0
. Documents can be identified based on this concept.

(Scanner Reading Accuracy) When reading black and white characters with a scanner, if the scanner accuracy is not good, the input image will be an image with color shift as shown in FIG. 8. In this case, a pixel with color shift is determined to be a color pixel, and as a result, there is a possibility that the document is erroneously determined to be a color document even though it is a black and white document. Therefore,
If a black pixel (a black and white pixel and a dark pixel) exists around the input pixel, it is determined that the input pixel is a pixel with color shift and is actually a black and white pixel. By doing so, errors in reading by the scanner can be reduced.

The pixels included in the diagonally shaded area in FIG. 11 (for originals having pixels with low and intermediate chroma saturation) are determined to be black and white pixels because their chroma is lower than the threshold value α. Therefore, if we consider a black text manuscript with a background of low saturation color (for example, recycled paper),
If the saturation of the background portion is smaller than α, the document is a black and white document, and if it is larger, the document is a color document. Next, for photographic originals with low saturation, the number of pixels distributed in the shaded area is relatively large. In this case, since it is smaller than the threshold value α, it is determined that the document is black and white. Therefore, we focused on the fact that in the case of originals with low chroma colors on the background, the number of pixels included in the shaded area is much larger than in the case of photographic originals. If the number is greater than a predetermined value β, the document is easily determined to be a black and white document, and if it is not, the document is determined to be a color document.

[First Example] FIG. 9 shows a flowchart of the process. The processing is thick (,
Pixel discrimination processing (Sl-S4) and pixel correction processing (85-5
ll), and document discrimination processing (812 to 515). The pixel discrimination process is a process for discriminating whether the pixel of interest is color or monochrome, and the document discrimination process is a process for discriminating whether the entire document is a color document or a monochrome document. The details of the algorithm will be explained below according to the flow.

Pixel judgment processing> First, color pixel determination processing will be explained.

Color pixel determination is processed in steps 81 to S4. It is determined for each pixel whether the input pixel is a color pixel or a monochrome pixel.

(2) Color space conversion processing In Sl, color space conversion processing is performed. That is, NTSC
- Convert the RGB normalized data into a luminance signal Y and chromaticity signals I and Q according to equation (1).

(2) Distance Calculation In steps S2 and 86, the distance calculation unit calculates the distance T in order to create saturation information from I and Q. This means that the target color is IQ
This shows how far away from the origin it is on the chromaticity diagram. If this value is large, the saturation is high, and it can be said that the probability that the pixel is a color pixel is high.

■Saturation comparison section In S3, the saturation of the pixel of interest is compared with a threshold value.

As shown in Figure 10 (A), the pixel C of interest is a character or background (
If the color saturation is low (limited to white), the saturation is low (and in order to satisfy the condition of < a at T, proceed to 84 and increase the number of black pixels BPIX by 1. Then, return to S2 again and select the next pixel. Load it and perform the same processing.

If the pixel of interest is located at a position that is considered to be a color pixel as shown in FIG. 10(E), the saturation is high (the condition of α is not satisfied) and the process proceeds to S5.

(2) Pixel correction processing 85 to Sll are pixel correction processing units. This is Flo
Even if the pixel is determined to be a color pixel by the w3 saturation comparison unit, there is a possibility that it will be mistakenly determined as a color pixel due to blurring of black characters caused by color shift of the sensor.
This is provided to correct this misjudgment. The pixel correction section will be explained below.

In S5, eight pixels S1 to S8 surrounding the pixel of interest C in FIG.
Input pixel by pixel. In S6, RG is created by color space conversion.
Perform B→YIQ conversion (same as Sl).

In S7, saturation information T is calculated (same as S2).

In S8, the saturation & and luminance Y of surrounding pixels are compared with a threshold value. For example, if the surrounding pixel S1 is a character portion, the saturation is low and the brightness is low, so that the conditions m<B and Y<γ are satisfied. As a result, the pixel C of interest is determined to be a color pixel in the pixel determination process, but it is actually determined to be due to color shift in the sensor and is originally a black pixel.The process proceeds to S9, and the number of black pixels BPIX is set by 1. increase. In the case of the surrounding pixel S6, it is 8 because the conditions of Tma〈β and Y〈γ are not satisfied.
It is determined that pixel 6 is not a black pixel and the process proceeds to FlowlO. S.I.
O is for checking whether all the surrounding 8 pixels have been input. In this way, it is checked whether the surrounding eight pixels include a black pixel by repeating the processing from 85 to S10 to the eight pixels 81 to S9 surrounding the pixel of interest. If even one black pixel is included in the surrounding eight pixels, the pixel C of interest is treated as a black pixel and the process proceeds to S9. Also, there is one black pixel among the surrounding eight pixels.
If no color pixel is included, the pixel C of interest is not a color pixel due to color shift, but is treated as a true color pixel and proceeds to Sll, and the number of color pixels CPIX is increased by one.

(Color and monochrome original discrimination) The pixel discrimination described above (Sl-11) is applied to all pixels of the original, and the color pixel CPIX and monochrome pixel BP are
Find the ratio of IX. If the condition CPIX > δ is satisfied in S13, it is determined that the target document is a color document; otherwise, it is determined that it is a black and white document.

The above is a flowchart in which processing is performed by, for example, computer software, and the circuit configuration for performing the above processing will be described below with reference to FIG. 1.

When a document is placed on a scanner composed of 101 CODs and scanned, it is RG normalized to the NTSC standard.
Data of B is output. 1 in the YIQ conversion section of 102
The RGE data output from 01 is converted into a brightness (luminance) signal Y and chromaticity signals ■ and Q. A pixel determination unit 103 determines whether an input pixel is a black and white pixel (low saturation) or a color pixel. Reference numeral 104 denotes a document discrimination unit, which aggregates the discrimination results for each pixel, calculates the ratio of the number of color pixels to the total number of pixels, and determines whether the document is color or black and white according to the proportion. Output a signal. 10
6 is an image processing unit, 107 is a display for displaying images, 108 is a facsimile transmission unit for transmitting images, 109
Reference numeral 110 represents a printer that reproduces an image onto a recording medium, 110 represents an intermediate saturation pixel counting unit, and 3 represents a CPU. The image processing unit 106 performs different processing on a monochrome original and a color original in accordance with the original discrimination signal 105.

For example, regarding the image signal sent to the facsimile transmission unit 108, in the case of a color original, compression encoding is performed so that each of the R, G, and B signals can be stored, and in the case of a black and white original,
Convert to density (luminance) signal and use normal MH, MR, MMR
Performs compression encoding such as

Regarding the image signal sent to the printer 109, in the case of a color original, logarithmic conversion is performed on the R and GSB signals, and U
After performing predetermined processing such as CR and masking, Y, M, C,
The image is processed so that it becomes a frame-sequential signal, and in the case of a monochrome original, only a K (black) signal is generated to perform monochromatic black printing.

Note that the printer may be of any type as long as it is capable of color printing, such as a laser beam printer, an inkjet printer, a thermal transfer printer, or a dot printer.

FIG. 2 is a diagram showing a YIQ conversion section, which calculates equation (1). 201.202.203 are R and G, respectively.

This is the input signal of B. 204-212 are registers that set the coefficients of equation (1), 213-221 are multipliers that multiply input data and coefficients, 222.223.225.22
8 is an adder, and 226 and 229 are subtracters. and,
The result of the operation is Y at 224 and Q at 227 and 1.230.

For example, when calculating Y, register 204 is set to 0.3, register 207 is set to 0.59, register 210 is set to 0.11, and R data 201 and the contents of register 204 are multiplied by 213. Multiply by Similarly, G
The data and the contents of the register 207 are multiplied by a multiplier 216, and the B data and the contents of the register 210 are multiplied by a multiplier 219. Then, the three multiplication results are added by adders 222 and 223, and Y is finally obtained. Similarly, I and Q can be calculated.

FIG. 3 is a diagram showing a pixel discrimination section. 301 to Y130
I data is input to 2, and Q data is input to 303. (2) is squared by the multiplier 310. Further, Q is squared by a multiplier 311. (2) 2 and Q2 are added by an adder 312. Next is the calculation for T, which is done by referring to the table. For example, if the input of ROM313 is 2, the ROM
Address No. 2 is accessed and data 1.414 is output. Further, the output signals from the ROM 313 are input to comparators 305 and 306. A threshold value β is set in the register 308, and a threshold value α is set in the register 309. Then, a comparator 305 compares the threshold value β with the threshold value β, outputs 1 when β is equal to the threshold value, and outputs 0 otherwise. Further, the comparator 306 compares the threshold value α and t=ma, and outputs 1 when α<ts, and outputs 0 otherwise. The output result of this comparator 306 is called the first determination result.

Next, regarding the brightness (luminance) signal, a threshold value γ is set in the register 307, and a comparator 304 compares Y and γ. Outputs 1 when Y is γ, otherwise 0
Output. The outputs of comparators 304 and 305 are ANDed by AND gate 314. In other words, brightness (brightness)
is low and the saturation is low, the AND gate 314 outputs 1, and otherwise outputs O. The output result of this AND gate 314 is called a second determination result. The output of the AND gate 314 is a flip-flop (hereinafter referred to as FF) 31
8 and 315 line memories. Further, the output of the line memory 315 becomes the input of the line memory 316 and the FF 312.

Therefore, the FF321 has l-line delayed pixels.
A pixel delayed by two lines is input to the FF 324. FFs 318 to 326 hold the output result of AND gate 314 in synchronization with the pixel clock. Therefore, at a certain point, the secondary discrimination result of the pixel of interest is FF32.
If it is held at 2, then FF318.319.3
20.321.323.324.325.326 holds the secondary determination results of the surrounding eight pixels. The secondary determination results for these 8 pixels are OR gate 329.
A logical OR is performed on 330.331.332.

If there is even one pixel with a secondary discrimination result of 1 among the surrounding 8 pixels, the output of the OR gate 332 becomes 1. That is, if there is at least one black pixel in eight pixels around the pixel of interest, the 332 will output l. The output of this OR gate 322 is called a pixel correction result. Further, the output of the comparator 306 (first determination result) enters the line memory 317, is delayed by one line, and flows to the FF 327 and FF 328. That is, the FF 328 and the FF 322 respectively hold the first discrimination result and the second discrimination result of the same pixel.

Finally, NOR the pixel correction result and the first judgment result.
Judge by R gate. The color pixel determination signal 334 becomes 1 when the pixel is determined to be a color pixel, and becomes 0 when the pixel is determined to be black and white.

FIG. 4 is a diagram showing the document discriminating section.

406 is an up count, and as inputs 403 is initial count data DAT, 402 is a pixel clock, and 40
1 is a color pixel judgment signal. The counter 406 counts up from the initial count data in synchronization with the pixel clock, but during the period when count-up is enabled, the color pixel determination signal is only 1, and as a result, the color pixel determination signal is counted. It turns out.

Further, the 110 intermediate chroma pixel counting section in FIG. 1 counts the number of input pixels of intermediate chroma. That is, in FIG. 11, if a pixel with saturation T > ε and saturation α7 < a is input, it is counted. Original discrimination section 104
The number of color pixels and the threshold value δ are compared. CPU 11
1, if the number of color pixels>δ, it is determined to be a color document, and if the number of color pixels≦δ, it is determined to be a black and white document. Here, regarding the setting of the threshold value δ, CPU III is changed according to the count number of the intermediate chroma pixel count section.

In other words, if there are more pixels with intermediate saturation than the predetermined value β, the threshold value δ is increased to determine that the original is black and white, and if there are not many pixels with intermediate saturation, the threshold value δ is decreased. DAT4
Set to 03. In this way, a desired determination result can be obtained by changing the criterion for determining black and white/color of a document according to the number of pixels with intermediate saturation between chromatic colors and achromatic colors.

Through the above processing, it is possible to determine whether the document is in color or black and white.

[Second example] FIG. 5 is a diagram for explaining the second embodiment.

In the first embodiment, in order to realize the calculation of equation (1), the second
Although the configuration shown in the figure was used, in the second embodiment, the calculation of equation (1) is approximated using the configuration shown in FIG. If the coefficient of equation (1) is approximated by adding 1 to a power of 2, equation 2 is obtained. For example, the coefficient 0.3 in equation l is approximated to 0.25+0.0625. By doing so, it is possible to easily calculate 0.3*H by adding the input data shifted by 2 bits and shifted by 4 bits.

... (2) Next, Fig. 4 will be explained. 501, 502, and 503 are set with R, G, and B input data, respectively.
4 to 513, 519, and 520 are bit shift units that shift bits of input data. 514.515
．． 516.517.518.521.523.527 is an adder, and 524.525.526 is a subtracter. The final calculated data is Y in 528 and L in 529.
Q is output to 30.

Next, the flow of data will be explained. The calculation method is the same for Y, I, and Q, so here we will use Y as an example, and (11) will be explained, and I and Q will be omitted.For calculation of the term of R, 504 A 2-bit shift is performed at 507, a 4-bit shift is performed at 507, the result is sent to an adder 517, the input G data is shifted 1 bit at 509, a 4-bit shift is performed at 510, and the result and the output of the adder 517 are sent to an adder 522. Add with . The output of adder 522 is the result of the addition of the R and G terms in the calculation of Y in Equation 2. Next, the input data 503 of B is shifted by 3 bits and input to the adder 523. As a result, the output 528 of the adder 523 becomes Y in Equation 2.

As described above, according to the embodiment of the present invention, means for separating each component signal of an input color signal into a brightness signal and a chromaticity signal;
means for generating a saturation signal from the chromaticity signal; means for comparing the saturation signal with a threshold value α; means for comparing the saturation signal with a threshold value β; and means for comparing the lightness signal with a threshold value γ. As a result of comparing the means for counting the number of input signals with intermediate saturation, the saturation signal of the pixel of interest, and the threshold value, the saturation signal <
If α, the method is to increase the number of black and white pixels by 1, and as a result of comparing the saturation signal and threshold value of the pixel of interest, and if the saturation signal ≧ α, the saturation signal and threshold value β are compared for surrounding pixels. As a result, as a result of comparing the saturation signal β and the brightness signal with the threshold value γ, the brightness signal <γ is determined, and if the surrounding pixels include a pixel that satisfies this condition, the number of black and white pixels is reduced to 1.
means for increasing the number of color pixels by 1 if the number of color pixels is not included; means for changing the threshold value δ according to the total number of input signals having intermediate saturation; and means for comparing the number of color pixels with the threshold value δ. By comparing the number of color pixels with the threshold value δ and determining that the number of color pixels>δ, the document is determined to be a color document.1. If the scanner accuracy is not good, or if the background of the document has a light color,
Even photographic originals with low saturation can be identified without misjudgment. As a result, it is possible to perform processing according to the type of document, and it is possible to improve print quality and reduce communication costs.

Note that the image input means is not limited to a scanner, and may be an interface of a host computer, a still video camera, a video camera, or the like.

Furthermore, the number of peripheral pixels to be referenced is not limited to eight pixels.

Moreover, instead of OR processing (majority processing may be performed).

In addition to separating into (Y, L Q), (L", al, b
'), (J, Uo, V''), (Y% us v), etc. for determination.

〔Effect of the invention〕

As described above, according to the present invention, it is possible to accurately determine whether an input color signal is chromatic or achromatic.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing an automatic color/black-and-white document discriminator according to a first embodiment of the present invention. FIG. 2 is a configuration diagram of the YIQ conversion section. FIG. 3 is a diagram showing the configuration of the pixel discrimination section, and FIG. 4 is a configuration diagram of the document discrimination section. FIG. 5 is a configuration diagram of the YIQ conversion section of the second embodiment. FIG. 6 is a diagram showing the distribution of I and Q when a monochrome original is read. FIG. 7 is a diagram showing the distribution of I and Q when a color original is read. FIG. 8 is a diagram showing the state of color shift. FIG. 9 is a diagram showing the overall flow of color/monochrome document discrimination. FIG. 10 is a diagram illustrating pixel correction processing. FIG. 11 is a diagram showing the distribution of medium saturation originals. 101... Scanner 102... YIQ conversion unit 103... Pixel discrimination unit 104... Original discrimination unit 105... Original discrimination signal = Iψ-V-K6-xQ \

Claims (3)

[Claims] (1) means for determining whether an input color signal is chromatic or achromatic;
A color image processing apparatus comprising: a control means for controlling a determination criterion of the determination means according to the number of intermediate chroma pixels included in the input color signal. (2) The color image processing apparatus according to claim 1, further comprising a correction means for correcting the determination result by the determination means by referring to surrounding pixels. 3. The color image processing apparatus according to claim 1, further comprising means for determining whether a document represented by an input color signal is black and white or color, using the determination result.