Color image processing device

A color image processing device including PA0 a reader for reading an original image for each area containing a predetermined number of pixels of the original image and color-separating the read area into red, green and blue components, PA0 a character area detector for detecting whether or not the area read by the reader is a character area constituting a part of a character in the original image for each of the red, green and blue components, and PA0 a black character area determinator adapted to determine the area read by the reader to be a black character area constituting a part of a black character in the original image if said area is detected to be the character area for all of the red, green and blue components by the character area detector.

BACKGROUND OF THE INVENTION 
1. Field of the Invention 
The present invention relates to a device for processing image signals of 
an original image to reproduce the original image, which is capable of 
clearly reproducing black characters in case the original image is 
composed of black characters and color pictures. The device of the present 
invention is particularly suitable for use in digital color reproduction 
machines and color facsimile equipment. 
2. Description of Background 
In color documents comprising therein pictures and characters, the 
characters are black in most cases. For reproducing black color in color 
reproduction machines, three color materials, i.e., yellow (Y), magenta 
(M) and cyan (C), are superimposed on each other. However, perfect black 
color cannot be obtained unless Y, M and C are perfectly balanced. Also, 
misalignment of those Y, M and C color materials results in quite 
indistinct images reproduced, especially, black characters. In order to 
cope with such a drawback, the prior art utilizes UCR (Under Color 
Removal) processing in which Y, M and C color materials are replaced by a 
single black color material in the areas where those three color materials 
are to be superimposed. Provided that an image reading scanner of color 
reproduction machines has ideal characteristics, black characters read by 
the scanner and subjected to color separation into red, green and blue 
components, could be printed on a paper with a black color material alone 
using the UCR processing because magnitudes of respective color components 
should be equal with respect to each other, i.e., R=G=B=O. However, 
characteristics of the actual scanner are different from those of the 
ideal one, so the magnitudes of the respective color components cannot be 
perfectly equal with respect to each other when reading black characters 
and subjecting them to color separation. An example of the prior art UCR 
discussed above is reflected by U.S. Pat. No. 4,700,399, wherein the edge 
intensity is detected by use of a Laplacian filter and the amount of UCR 
is increased in proportion to the edge intensity of the picture element 
(pixel). The purpose of this patent is to provide an improved 
reproducibility of black characters. It must be noted that in this prior 
art only the control of the UCR amount is performed. In this instance, 
when the gray balance of R, G and B is incomplete, the color components 
remain. Thus, the positional shear (slippage) appears between Y, M, C and 
black. As a consequence, blotting or blurring of color materials for color 
printing occurs around the black characters so that the image quality of 
the black picture is deteriorated. Therefore, in spite of using the UCR 
processing, the black characters are printed on a paper with mixture of 
black and other color materials. 
SUMMARY OF THE INVENTION 
The present invention has been accomplished in view of the foregoing, and 
its object is to provide a color image processing device in which an image 
signal is processed to clearly reproduce black characters. 
The object of the invention is attained by a color image processing device 
including: 
a reader for reading an original image for each area containing a 
predetermined number of pixels of the original image and color-separating 
the read area into red, green and blue components, 
a character area detector for detecting whether or not the area read by the 
reader is a character area constituting a part of a character in the 
original image for each of the red, green and blue components; and 
a black character area detector for characterizing the area read by the 
read means as a black character area constituting a part of a black 
character in the original image when said area is detected by the 
character area detector to be a character area for each and every one of 
the red, green and blue components. 
The object of the invention is also attained by a color image processing 
device including: 
a reader for reading an original image for each area containing a 
predetermined number of pixels of the original image and color-separating 
the read area into red, green and blue components; 
a black component extractor for extracting black component of the area read 
by the read means based on the red, green and blue components of the area 
separated by the read means; 
a character area detector for detecting whether or not the area read by the 
read means is a character area constituting a part of a character in the 
original image for each of red, green, blue and black components; and 
a black character area detector for characterizing the area read by the 
reader as a black character area constituting a part of a black character 
in the original image when said area is detected by the character area 
detector to be a character area for each and every one of the red, green, 
blue and black components. 
The above and other features and advantages of the present invention will 
be apparent from the following description of preferred embodiments shown 
in the accompanying drawings.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
An area determination circuit usable in the color image processing device 
of the present invention will be described with reference to FIGS. 1-14. 
The purpose of the area determination circuit is to determine whether the 
area comprised of the predetermined number of pixels is a picture area for 
representing a picture or a character area for representing a character. 
Whether the relevant area is a picture area or a character area can be 
determined by either the method of detecting the number of those pixels 
inside the area which have density not less than a background level, the 
method of detecting the number of so-called edge pixels inside the area 
which are abruptly changed in density, or the method of detecting whether 
or not the area is a dot area consisting of dots adapted to represent a 
half tone. 
FIG. 1 shows a circuit corresponding to the method of detecting the number 
of those pixels which have density not less than a background level 
(hereinafter referred to as algorithm 1). In the picture area, most of 
pixels inside the area are those pixels which have a density of not less 
than a background level (hereinafter referred to as colored pixels), while 
in the character area, the number of colored pixels is relatively small. 
Therefore, whether the relevant area is a picture area or a character area 
can be determined by comparing the number of colored pixels inside the 
area with a predetermined number (threshold). 
Referring to FIG. 1, there is shown an MTF (Modulation Transfer Function) 
correction unit 1, a comparator 2, a colored pixel density filter 3, a 
comparator 4, and preset thresholds thr 1, thr 2 
This algorithm (1) is likely to invite erroneous determination if edge 
portions of the character are blurry to a large extent. Therefore, it is 
desired to apply MTF correction (high-frequency enhancement) in the MTF 
correction unit 1. 
The comparator 2 determines those pixels, which have density equal to or 
higher than the preset threshold thr 1, to be colored pixels, and those 
pixels, which have density lower than the threshold thr 1, to be 
background level pixels. The colored pixel density filter 3 at the next 
stage has a scan window corresponding to the area of size as large as 
4.times.4-8.times.8 pixels. As mentioned above, since substantially all of 
pixels of the picture area within the scan window are colored pixels, the 
threshold thr 2 used for area determination may be set any value in a 
range of N to N-2, assuming that the number of pixels within the scan 
window is given by N. The comparator 4 determines that an area which has a 
number of pixels, which have beforehand been determined to be colored 
pixels, and which number is equal to or larger than the preset threshold 
thr 2 is a picture area, and any area other than as defined above is a 
character area. 
Although the scan window may have the size of 7.times.7 pixels as shown in 
FIG. 2(a), for example, it is not necessary to make determination for all 
of 49 pixels as to whether they are colored pictures or not. The 
configuration of hardware can be simplified by utilizing only a part of 
the pixels as illustrated in FIGS. 2(b), 2(c), 2(d), 2(e) and 2(f). 
FIG. 3 shows a circuit corresponding to the method of detecting the number 
of so-called edge pixels inside the relevant area which are abruptly 
changed in density (hereinafter referred to as algorithm 2). 
In the picture area, the portions where density is abruptly changing are 
few and hence the number of edge pixels is small. On the contrary, the 
number of edge pixels is large in the character area. Thus, whether the 
relevant area is a picture area or a character area can be determined by 
comparing the number of edge-pixels inside the area with a predetermined 
number (threshold). 
Referring to FIG. 3, there is shown a derivative value calculation unit 5, 
a comparator 6, an edge pixel density filter 7, a comparator 8, and 
thresholds thr 3, thr 4. 
The extraction of the edge picture elements can be accomplished by either 
primary differentiation filters or secondary differentiation filters. 
Either of these filters can be used as the unit 5 shown in FIG. 3. The 
following description provides the instance of using a primary 
differentiation filter wherein the term "density slope" corresponds to 
primary differentiation. 
The comparator 6 determines those pixels, which have a density slope equal 
to or higher than the preset threshold thr 3, to be edge pixels, and those 
pixels, which have a density slope lower than the threshold thr 3, to be 
non-edge pixels. The comparator 8 determines that an area which has a 
number of edge pixels, which have beforehand been determined to be edge 
pixels, and which number is equal to or larger than the preset threshold 
thr 4 is a character area, and any area other than as defined above is a 
picture area. The edge pixel extraction is generally performed by a method 
using the magnitude of the secondary derivative value (Laplacian) or 
primary derivative value (gradient). 
The density slope (derivative value) of a given pixel is dependent on 
densities of respective surrounding pixels. For example, the density slope 
of pixel (e) at the center of the area shown in FIG. 4 is defined by the 
following equation: 
##EQU1## 
where a through e represent gradation levels of the respective pixels. In 
place of the above maximum value, the mean value or sum of absolute level 
differences between the given pixel and the surrounding pixels may be 
defined as a density slope of the given pixel. 
The density slope (derivative value) can be calculated by making use of 
filters as shown in FIG. 5, these filters are used as the derivative value 
calculation unit 5 of FIG. 3. FIGS. 5(a)-5(d) show the filters for 
calculating the secondary derivative values, and FIGS. 5(e)-5(n) show the 
filters for calculating the primary derivative values. Since the filters 
for calculating the primary derivative values have directionality, it is 
preferable that the squared mean value, mean value, or maximum value of 
outputs from two filters, which have their directionalities orthogonal to 
each other, is used as the primary derivative value. 
The calculated density slope is compared with the threshold thr 3 in the 
comparator 6. The threshold thr 3 can be a fixed value. Alternatively, it 
may be varied depending on the background level of a document. The edge 
pixel density filter 7 has the size, such as 3.times.3-8.times.8 pixels, 
corresponding to the area to be processed. The comparator 8 compares the 
number of pixels inside the filter 7, which have beforehand been 
determined to be edge pixels, with the threshold thr 4 to detect whether 
or not the area is a character area. 
FIG. 6 shows a circuit corresponding to the method of detecting whether or 
not the relevant area is a dot area consisted of dots adapted to represent 
a half tone (hereinafter referred to as algorithm 3). Referring to FIG. 6, 
there is shown an MTF correction unit 9, a comparator 10, a dot detector 
11, an area determination unit 12, a determination correcting unit 13, and 
a threshold thr 5. Although the pattern matching technique is utilized in 
the circuit of FIG. 6, the dot size is changed depending on the gradation 
level, the dot pitch, or the like, and hence a plurality of templates 
should be employed. FIG. 7 shows example of such templates. In FIG. 7, 
respective pixels within the scan window are represented by Mij. Symbols 
o, x, .DELTA. indicate three different types of templates, respectively. 
When any one of the following conditions (1), (2) or (3) is satisfied, the 
pixel M44 is regarded as a black dot: 
(1) M44=black and all pixels at symbol o=white 
(2) M44=black and all pixels at symbol x=white 
(3) M44=black and all pixels at symbol .DELTA.=white. 
When any one of the following conditions (4), (5) and (6) is satisfied, the 
pixel M44 is regarded as a white dot: 
(4) M44=white and all pixels at symbol o=black 
(5) M44=white and all pixels at symbol x=black 
(6) M44=white and all pixels at symbol .DELTA.=black. 
Then, the image is divided into blocks of size as large as 
8.times.8-16.times.16 pixels, and those blocks in which at least one dot 
have been found are determined to be dot areas. To prevent erroneous 
determination due to noises or the like, the determination is corrected at 
the next stage. For example, as shown in FIG. 8, if three blocks, i.e., 
block 1, block 2 and block 3, are all determined to be dot areas, the 
remaining one block (block 4) is also regarded as a dot area. To the 
contrary, if two or less among the four blocks have been determined to be 
dot areas, all of the four blocks are regarded as non-dot areas. 
The device for implementing the algorithm 1, shown in FIG. 1, will now be 
described in more detail. 
The image data read by a scanner (not shown) is required to compensate for 
deterioration in the high-frequency range through the MTF correction unit 
1. The MTF correction unit 1 comprises a digital filter with 
high-frequency enhancing characteristics. 
FIGS. 9(a), 9(b) and 9(c) show examples of the two-dimensional 
high-frequency range enhancing filter suitable for MTF correction. 
The Modulation Transfer Function (MTF) is an amplitude transmission 
characteristic with regard to the spatial frequency. The MTF of the input 
system differs in accordance with the shape and other characteristics of 
the lens or the aperture which is used. In general, the transmission 
characteristics are not as good when high-frequency components are used. 
For this reason, gradation (shading off) is included in the input image. 
In order to correct the gradation, the deteriorated high-frequency 
component must be restored to its former condition. That is, the 
high-frequency components must be emphasized. The treatment of this 
high-frequency component in order to provide compensation of the MTF is 
called "MTF compensation". Because a high-frequency area emphasizing 
filter is used to perform the MTF compensation, the technical terms; "MTF 
compensation" and "high-frequency area emphasizing (enhancing) treatment", 
are used synonymously. 
The compensation of the gradation which is performed by means of the 
high-frequency area enhancing filter which is used and exemplified in 
FIGS. 9(a)-9(c) is described in detail in "A. Rosenfeld, A. C. KAK; 
Digital Picture Processing; Academic Press, 1976". Furthermore, the 
exemplary embodiment of applying the MTF compensation technology to 
facsimile or the like is described in Japanese laid-open patent 
application JOP57-53179/1982. 
Respective factors of each filter should be selected in accordance with 
frequency characteristics of the input system. Although the filters of 
3.times.3 size are illustrated in FIGS. 9(a)-9(c) other filters of larger 
sizes such as 5.times.3 or 5.times.5 pixels can also be used for better 
correction. Alternatively, the factors may have different values in main 
scan and sub-scan directions for matching with frequency characteristics 
of the actual input system. Further, use of the filters having pixels in 
four directions only, as shown in FIGS. 9(b) and 9(c), makes it possible 
to simplify the configuration of hardware. 
The filter coefficients shown in FIGS. 9(a)-9(c) are exponents of the 
number "2". When constructed in terms of hardware, multiplication is 
realized by shifting bits without using the multiplier so the device can 
be constructed at low cost. The value is determined in accordance with the 
value obtained by measuring the MTF characteristic value of the input 
system. The FIGS. 9(a)-9(c) show coefficients for embodiments frequently 
used as high-frequency area emphasizing (enhancing) filters. 
FIG. 10 is a circuit diagram of the two-dimensional high-frequency range 
enhancing filter of 3.times.3 size. For implementing the arithmetic 
operation of 3.times.3 matrix, this circuit has two line buffers and 
3.times.3=9 latches. In FIG. 10, designated at 14, 15 are line buffers, at 
16-24 latches, at 25-32 adders, and at 33 is a multiplier. 
The data of 9 latched pixels are processed with the adders 25-32 and the 
multiplier 33. As an alternative, the circuit may use ROMs (Read Only 
Memory) in place of the adders 25-32 and the multiplier 33, for simpler 
matrix operation with optional factors. 
The optional factors referred to factors which exclude the filter 
coefficients shown in FIGS. 5(a)-5(n) and 9. These coefficients shown in 
the FIGS. 5(a)-5(n) and FIGS. 9(a)-9(c) are representative examples, but 
various modifications are possible. 
FIG. 11 shows a circuit diagram of the colored pixel density filter 3 and 
the comparator 4. In FIG. 11, there is shown a shift register 34, a 
counter 35, line buffers 36-39, latches 40-44, adders 45-48, and a 
comparator 49. 
The colored pixel density filter 3 shown here counts the number of colored 
pixels within the scan window of 5.times.5 size. More specifically, each 
pixel data of 1 bit having been binary-coded by the comparator 2 is 
inputted to the shift register 34. The shift register 34 outputs the 
binary data of 5 pixels (5 bits in total) in the main scan direction. The 
counter 35 at the next stage counts the number of colored pixels per 5 
pixels in the main scan direction. 
The numbers of colored pixels per 5 pixels in the main scan direction for 5 
lines are held in each of the latches 40-44 and then added by the adders 
45-48, so that the number of colored pixels per 5.times.5=25 pixels is 
calculated. The thus-calculated number of colored pixels is compared with 
the predetermined threshold thr 2 (approximately 25-23). As a result of 
the comparison, if that number is equal to or larger than the threshold 
thr 2, the area determination signal of "0" (indicative of a picture area) 
is delivered, and if it is smaller than the threshold thr 2, the area 
determination signal of "1" (indicative of a character area) is delivered. 
The device for implementing the algorithm 2 shown in FIG. 3 will now be 
described in more detail. The derivative value calculation unit 5 can be 
realized by a circuit similar to the circuit shown in FIG. 10. In this 
case, the filter factors shown in FIGS. 5(a)-5(n) may be used. 
In order to perform filtering by means of a general filter coefficient in 
FIGS. 5(a)-5(n) and in FIG. 9, a multiplier must be connected between the 
latches 16-24 and the adders 25-28 of FIG. 10. This multiplier multiplies 
the picture element data respectively latched in the latches 16-24 by the 
filter coefficients corresponding to the respective picture elements. 
Subsequently, the respective multiplication results are input into the 
adders 25-28. 
In the embodiment of FIG. 10, all of the filter coefficients of the 
circumferential eight picture elements (the picture elements of the 
positions a, b, c, d, f, g, h and i) shown in FIG. 4 are equal to "1". The 
filter coefficients of the picture element which is to be recognized (the 
picture element of the position e shown in FIG. 4) is not disclosed in 
FIG. 10. However, assuming that the coefficient of the multiplier 33 is 
equal to -8, the filter coefficient is equal to a calculated differential 
(derivative) value shown in FIG. 5(d). 
The examples of the edge extracting filter are shown in FIGS. 5(a)-5(n) and 
the size of the filter is not limited to a 3.times.3 and 2.times.2. Other 
filters may be used such as 5.times.5, 5.times.3, or others. Furthermore, 
with respect to the filter coefficient, the FIGS. 5(a)-5(d) show the 
representative examples of secondary differentiation while FIGS. 5(e)-5(n) 
show the representative examples of primary differentiation. 
For the edge pixel density filter 7 and the comparator 8, a circuit similar 
to the circuit shown in FIG. 11 can be employed. If the number of edge 
pixels is equal to or larger than the predetermined threshold thr 4, the 
signal of "1" (indicative of a character area) is delivered, and if it is 
smaller than the threshold thr 4, the signal of "0" (indicative of a 
picture area) is delivered from the comparator 8. 
The device for implementing the algorithm 3 shown in FIG. 6 will now be 
described in more detail. 
FIGS. 12(a)-12(e) shows examples of the dot detector 11. Shown in FIG. 
12(a) is a circuit adapted to prepare the data of 49 pixels within the 
scan window of 7.times.7 size, the circuit comprising line memories 50-55 
for 6 full lines and latches 56-63 for 7.times.7=49 bits. The binary data 
M11-M77 for 49 pixels can be taken out from the group of latches 56-63 
simultaneously. 
FIGS. 12(b), 12(c) and 12(d) show circuits for implementing the three types 
of templates (o, x, .DELTA.), respectively. The signals no, nx and 
n.DELTA. are inputted to a gate shown in FIG. 12(e) which in turn delivers 
the logical sum of the inputs as a dot detection signal n. 
The output signal no is equal to 0 when the condition (1) or (4) are 
realized. In a similar manner the output signal nx is 0 when the condition 
(2) or (5) is realized and lastly, the output signal n.DELTA. is 0 when 
the condition (3) or (6) are met. These conditions refer to the previously 
discussed conditions for the pixel M44. The detail previously discussed 
wherein when the value of black is given this signifies the value equal to 
"1" whereas white signifies "0". 
Stated in another manner, the respective outputs no, nx, n.DELTA. are 0 
when the net points fitted for the respective templates are detected The 
signal n="1" when at least one of no, nx and n.DELTA. is equal to "1". 
That is, signal n turns out to be equal to 1 when at least one of the 
output signals no, nx and n.DELTA. is fitted for one of the respective 
three kinds of templates. When the net point is detected, the signal n 
turns out to be equal to "1". 
FIG. 13 shows one example of the area determination unit 12. In FIG. 13, 
designated at 64 is a 8 bit serial-to-parallel converter, at 65 first OR 
gate, at 66 first latch, at 67 second OR gate, at 68 second latch, at 69 
third latch, and at 70 is a line memory. 
This circuit functions to detect the presence or absence of dot per block 
of 8.times.8 size and then output a dot area determination signal P. More 
specifically, if at least one dot is detected within the block of 
8.times.8 size, the output of P=1 is issued. Otherwise, the output of P=0 
is issued. The dot detection signals n for every 8 pixels in the main scan 
direction are inputted to the 8 bit serial-to-parallel converter 64. 
The first OR gate 65 at the next stage issues an output signal set to 
logical 1 when any one of 8 bits (8 pixels) exhibits logical 1. The signal 
indicative of the presence or absence of dot from the first OR gate 65 is 
passed through the first latch 66 and the second OR gate 67 for storage 
into the line memory 70. 
Therefore, the signal indicative of the presence or absence of dot for 
every 8 pixels on the first line is stored in the line memory 70. When the 
dot detection signal n for 8 pixels on the second line are inputted, the 
first OR gate 65 outputs the signal indicative of the presence or absence 
of dot for 8 pixels on the second line. At the same time, the signal 
indicative of the presence or absence of dot for 8 pixels on the first 
line is outputted from the line memory 70. When, the second OR gate 67 
outputs a signal indicative of whether at least one dot is present or 
absent in the block of 8.times.2 size. In a like manner, when the dot 
detection signal n for 8 pixels on the eighth line is inputted, the second 
OR gate 67 now outputs the dot area determination signal P indicative of 
whether at least one dot is present or absent in the block of 8.times.8 
size. The dot area determination signal P is held in the third latch 69, 
while the first latch 66, second latch 67 and line memory 70 are cleared 
and readied for dot area determination of the subsequent block on the 
9th-15th lines. 
FIG. 14 shows one example of a circuit of the determination correcting unit 
13 for correcting the result of area determination obtained from the area 
determination unit 12. In FIG. 14, designated at 71 is a first line 
memory, at 72 second line memory, at 73-76 latches, at 77-80 are NAND 
gates, and at 81 is an AND gate. 
The area determination signals P for every block of 8.times.8 size 
sequentially issued from the area determination unit 12 are inputted to 
the first line memory 71 and the second line memory 72 in order. As a 
result, the area determination signals P for every block of 8.times.8 size 
on the 1st-8th lines are stored in the second line memory 72, and the area 
determination signals P for every block of 8.times.8 size on the 9th-15th 
lines are stored in the first line memory 71. Then, the area determination 
signals P in the first line memory 71 are sequentially delivered therefrom 
to the latches 73, 75, and at the same time the area determination signals 
P in the second line memory 72 are sequentially delivered therefrom to the 
latches 74, 76. As a result, the four latches 73-76 hold the area 
determination signals P for four blocks adjacent to each other, as shown 
in FIG. 8. The NAND gates 77-80 and the AND gate 81 jointly function to 
correct the area determination. More specifically, if at least three among 
the adjacent four blocks are determined to be dot areas, the particular 
block of interest is regarded as dot area and a signal q is set to logical 
0. If two or less blocks are determined to be dot areas, the particular 
block of interest is regarded as non-dot area and the signal q is set to 
logical 1. 
The method of detecting whether or not the area consisted of the 
predetermined number of pixels is a black character area representing a 
black character will be described below with reference to FIGS. 15 and 16. 
When a black image is read and separated into three primary colors; R 
(red), G (green) and B (blue), these three color components have the same 
magnitude. Therefore, in case a black character has been printed on the 
white background, when the area is determined to be a character area for 
all of color components R, G and B, it can be regarded as a black 
character area (This will be referred to as algorithm A hereinafter). FIG. 
15 shows a circuit for implementing the algorithm A. In FIG. 15, 
designated at 82 is an area determination circuit for determining whether 
or not the relevant area is a character area. 
Another method of detecting a black character area will now be described. 
The minimum value of magnitudes of respective color components min (R, G, 
B) (=max(R,G,B)) in the area represents the magnitudes of black component 
in that area. Therefore, if the area is determined to be a character area 
with respect to the component max(R, G, B), it can be regarded as a black 
character area (This will be referred to as algorithm B hereinafter). FIG. 
16 shows a circuit for implementing the algorithm B. In FIG. 16, 
designated at 83 is a max(R, G, B) calculation circuit and at 84 is an 
area determination circuit. 
Assuming that the respective color components have a magnitude represented 
by 8-bit data, those data can take the values in the area from 0-255 
respectively. The symbols max(R,G,B) and min(R,G,B) respectively represent 
the maximum value and the minimum value with the symbol R representing R32 
R max-R if the probable maximum value taken by R is equal to R max. In the 
case where the symbol R is represented by the 8-bit data, because the 
symbol R max takes the value of 255, when A=100, A32 255 - 100=155. 
In a similar manner max(R,G,B)=255-max(R,G,B). 
However, in the case where the symbols are represented by 6-bit data, since 
the probably maximum value taken by R, G and B is equal to 63, the 
following equation is realized: 
EQU max(R,G,B)=63-max(R,G,B). 
The unit 84 of FIG. 16 is an area determination circuit on the basis of the 
edge picture element density shown in FIG. 3. 
Color correction necessary for the color image processing device of the 
present invention will be described below. 
When reproducing an image in full color, three types color materials, i.e., 
Y (yellow), M (magenta) and C (cyan), or four types color materials 
including Bk (black) in addition to the above are usually employed This 
equally applies to silver salt prints as well as general prints using 
process ink. Ideal characteristics of Y, M and C color materials are such 
that they absorb 100% of R, G and B light beams, respectively, but reflect 
or transmit 100% of light beams in other colors. In actually, excepting Y, 
both M and C color materials are far from the ideal characteristics. The 
following Table 1 indicates the optical density of Y, M and C color 
materials in case of usual process ink with respect to R, G and B light 
beams (Yule, "Theory of Color Reproduction", p32, issued on Feb. 5, 1971). 
TABLE 1 
______________________________________ 
R G B 
______________________________________ 
C 1.30 0.41 0.15 
M 0.11 1.05 0.57 
Y 0.01 0.07 1.00 
______________________________________ 
Table 1 represents, respectively, the optical densities of the coloring 
materials C, M and Y for the light rays R, G and B. According to the 
embodiment of Table 1, the cyan-colored ink (C) has optical densities 
1.30, 0.41 and 0.15, respectively, for the light rays R, G and B. The 
relationship between the optical density D and the reflection coefficient 
Ref is expressed by the equation: 
EQU D=log(1/Ref). 
The reflection coefficients of C, M and Y for R, G and B converted to the 
other values by use of the abovementioned equation are illustrated in 
Table 2. 
TABLE 2 
______________________________________ 
(unit: percentage (%)) 
Light Rays 
R G B 
Coloring Materials 
(Red) (Green) (Blue) 
______________________________________ 
C (Cyan) 5.0 38.9 70.8 
M (Magenta) 77.6 8.9 26.9 
Y (Yellow) 97.7 85.1 10.0 
______________________________________ 
Because C, M and Y are respectively, the complementary colors of R, G and 
B, the ideal characteristics of the coloring material C, M and Y is that 
the respective one of light rays R, G and B is completely absorbed (the 
reflection coefficient: 0%, the optical density: infinity), and the other 
respective two light rays are completely reflected (reflection 
coefficient: 100%, the optical density: 0). In the Table 2, as shown 
above, the reflection coefficient of the coloring material of cyan for the 
light rays G (green) is only 38.9%. This value is far from the ideal value 
of 100%. Because absorption of the light rays G is the role of the magenta 
coloring material, it follows that cyan has many of the characteristics as 
the coloring material of magenta 
In a similar manner, the reflection coefficient of the coloring material 
magenta for the light rays B (blue) is only 26.9% and therefore the 
coloring material has many characteristics of the Yellow absorbing the 
light rays B. Furthermore, the coloring material of yellow has a high 
reflection coefficient, 97.7% and 85.1%, respectively, for the light rays 
R and G. This means that it has a comparatively preferable characteristic. 
In other words, the yellow coloring material contains a low percentage of 
cyan-colored component and a low percentage of magenta-colored component. 
As will be seen from Tables 1 and 2, Y is relatively close to the ideal 
characteristics, while C and M contain substantial amounts of M and Y 
components, respectively. Meanwhile, when printing colored characters, 
necessary color materials out of Y, M and C are superimposed as 
appropriate. For example, the character in green is expressed by 
superimposing C and Y ink. Since C ink contains the substantial amount of 
M component as mentined above, ideal green color (100% reflection of only 
G light beam) cannot be attained But the resulting color belongs to the 
category of green in visual sense, and hence there is, practically 
speaking, no problem. 
However, when that green color made by superimposing C and Y ink is 
subjected to color separation into R, G and B, the relevant area may be 
determined to be a character area for not only R, B data but also G data 
as a result of area determination using the above-mentioned algorithm A 
since the C ink contains the substantial amount of M component. Thus, 
there is a fear, for example, that the algorithm A may determine the green 
character to be a black character. For the same reason, the blue character 
(C +M) may be determined to be a black character. In case of using the 
algorithm B too, the substantial amount of black component is extracted 
from the green character, for example, which leads to a possibility that 
the green character may also be determined to be a black character 
similarly to the algorithm A. 
As for process ink as described in connection with Table 1, there exists 
the following relationship between the transferred amounts C, M, Y of 
respective ink of C, M, Y color materials and their optical density R G B 
with respect to R, G, B light beams: 
##EQU2## 
Therefore, the transferred amounts C, M and Y of respective ink are given 
by the following equation from the inverse matrix of the matrix in the 
above Eq. 1. 
##EQU3## 
Thus, the accuracy of area determination can be improved by implementing 
the algorithms A, B based on C, M and Y components given by Eq. 2 in place 
of R, G and B color components directly ready by the scanner. 
Several embodiments of the color image processing device of the present 
invention will be described below. 
FIG. 17(a) shows an embodiment in which the black character area 
determination is made by the algorithm A which utilizes min(R, G, B) data 
as black data Bk. This embodiment is effective for the area determination 
in case black characters are printed on the white background In FIG. 
17(a), designated at 85 is an input system (scanner), at 86 shading 
correction circuit, at 87 MTF correction circuit, at 88 .gamma. correction 
circuit, at 89 color correction/UCR processing circuit, at 90 min(R, G, B) 
calculation circuit, at 91 area determination circuit, at 92 halftone 
processing circuit for picture areas, at 93 processing circuit for 
character areas, at 94 processing result selection circuit, at 95 output 
control circuit, and at 96 is an output system. 
In a digital color copier, each of the elements including the shading 
compensation, gamma compensation, color compensation, UCR, and dither 
processing are fundamental construction elements known individually in the 
art. 
The British Patent GB-2,141,001 discloses the contents of a digital color 
copier whose specification discusses and illustrates each of the 
above-mentioned construction elements. 
The data read by the input system (scanner) 85 and separated into R, G and 
B colors are subjected to shading correction, MTF correction, and .gamma. 
correction. After undergoing these correction steps, the R, G and B data 
are inputted to the color correction/UCR processing circuit 89, the min 
(R, G, B) calculation circuit 90, and the area determination circuit 91 
successively. 
In the color correction/UCR processing circuit 89, color correction 
(masking) processing is performed in accordance with characteristics of 
the color materials used in the output system, and UCR processing is 
performed as required. Y, M, C and Bk data outputted from the color 
correction/UCR processing circuit 89 are inputted to each of the halftone 
processing circuit 92 for picture areas and the processing circuit 93 for 
character areas. The Bk data inputted to the processing circuit 93 for 
character areas is given by the min(R, G, B) data. 
The halftone processing circuit 92 for picture areas functions to carry out 
binary coding processing (or possibly multi-value coding processing such 
as three- and four-value) by making use of the systematic dither method, 
the error diffusion method, or the like which can provide the improved 
tone characteristics. The processing circuit 93 for character areas 
functions to carry out binary coding processing with much importance 
attached to resolution. As processing methods attaching importance to 
resolution, there have been practiced the dither processing using a 
diffusion type pattern such as Bayer type, or the binary coding processing 
with a fixed threshold. 
The produce image obtained by the difference of the Dither pattern by use 
of the systematic Dither processing method, the difference in the image 
quality, and the error spreading (diffusion) method are described in 
"Kodera; Digitalization of the Halftone Image; TV Academy Journal, volume 
40, no. 4 (1986)". The Bayer type pattern, the representative one of the 
Dots Dispersion (Divergence) type Dither pattern is disclosed in "B. E. 
Bayer; ICC Conference Record, 26, pages 11-15 (1973)". 
The error spreading method is disclosed in "R. W. Floyd and I. Steinberg; 
Proc. SID, 17, pages 75-77 (1976)". 
The systematic Dither method by use of the Dots Dispersion type Dither 
pattern is used for performing reproduction treatment of the character 
portion in the unit 93 shown in FIG. 17(a) because of its superior image 
resolution. 
It is further noted that U.S. Pat. No. 4,742,400 discloses a method of 
changing over the Dots Dispersion type Dither pattern and the Dots 
Concentration type Dither pattern in accordance with the characteristics 
of the input image (the character portion or the picture image portion). 
It must be noted that MTF compensation can be performed in the area 
determination circuit 91 or prior to that stage. In the embodiment shown 
in the FIGS. 17(a)-17(c) and 19, because the MFT compensation circuit is 
situated separate from the area determination circuit 91, it is not 
necessary to provide the MTF compensating portion in the area 
determination circuit 91. Furthermore, the FIGS. 1, 3 and 6 respectively 
show area determination circuits based on different algorithms. In the 
unit 91, the area discrimination is synthetically performed by use of 
these 3 types of circuits. That is, the circuits shown in FIGS. 1, 3 and 6 
are the construction elements of the unit 91 with the exception of course 
being that the MTF compensation circuit is provided separately as 
indicated by the number 87 in the FIGS. 17(a)-17(c) and 19. 
Following the result of area determination, the character portion 
processing result and the picture portion processing result are 
selectively applied to the character area and the picture area, 
respectively, by the processing result selection circuit 94. In addition, 
to reproduce black characters by a black material alone, the output 
control circuit 95 at the next stage functions so that Y, M and C data 
will not be outputted for those areas which have been determined to be 
black character areas 
In the area determination circuit 91, it first carries out area 
determination for each of R, G and B data using the algorithms 1, 2 or 3. 
Those area which have determined to be picture areas based on the 
algorithms 1, 2 or which have determined to be dot areas based on the 
algorithm 3, are regarded as picture areas, while the remaining areas are 
regarded as character areas. Further, those areas which have been 
determined to be character areas for all of R, G and B colors, are 
regarded as black character areas 
FIG. 17(b) shows an embodiment in which black character areas are detected 
based on the algorithm B. This embodiment is effective for the area 
determination in case black characters are printed on the colored 
background. The difference from the embodiment of FIG. 17(a) mentioned 
above is in that the area determination circuit 91 utilizes max(R, G, B) 
data resulted from a max(R, G, B) calculation circuit 97 as black data Bk. 
As an alternative, max(R, G, B) may be calculated in the area determination 
circuit 91 using the R, G and B data which are applied thereto The circuit 
91 makes determination as to whether the area is a picture area or a 
character area for black data based on the algorithm B using the max(R, G, 
B) data. It also makes determination as to whether the area is a picture 
area or a character area for R, G and B data based on a combination of the 
algorithms 1, 2 and 3. 
The algorithm A can make area determination for black character printed on 
the white background more correctly compared to the algorithm B. But the 
algorithm A cannot make area determination for black characters printed on 
the colored background. For example, in case black characters are present 
on the yellow background, character areas cannot be detected by any way 
for the B data. Thus, even if the relevant area is determined to be a 
character area for both the R and G data, that area will not be determined 
to be a black character area because it cannot be determined to be a 
character area for the B data. On the other hand, even in such a case of 
black characters printed on the colored background, the algorithm B using 
the black component data makes it possible to correctly detect black 
character areas, because the background (e.g., yellow) contains no black 
component. Therefore, black character areas can be extracted more 
correctly by utilizing both of the algorithm A and B. 
FIG. 17(c) shows an embodiment in which area determination is made using 
the algorithm A based on Y, M and C data which have been subjected to 
color correction in view of spectroscopic characteristics of ink, in place 
of the R, G and B data. The circuit diagram of this embodiment is 
different from that of FIG. 17(a) in a color correction circuit 89' and a 
max(Y, M, C) calculation circuit 97. 
FIG. 18(a) and 18(b) show block diagrams of color correction circuits. In 
FIG. 18(a), designated at 97-99 are latches, at 100-108 ROMs, at 109-111 
adders, and at 112-114 are latches. 
The color correction equation is given as follows: 
##EQU4## 
From the above Eq. 3, C, M and Y values after correction are given by the 
following Eqs. 3-(1) to (3): 
EQU C=all * R+a21 * G+a31 * B Eq. 3- (1) 
EQU M=a12 * R+a22 * G+a32 * B Eq. 3- (2) 
EQU Y=a13 * R+a23 * G+a33 * B Eq. 3- (3). 
In the embodiment of FIG. 18(a), multiplications of Eqs. 3-(1) to (3) are 
carried out by the table reference technique using ROMs. For example, the 
result of calculating a22*G is stored in the address G (or possibly G) of 
the ROM 104. The adders 109-110 carry out additions of Eqs. 3-(1)-(3), 
respectively. As a result, the adders 109-110 output the values of C, M 
and Y, respectively. 
Referring to FIG. 18(b), designated at 115-117 are latches, at 118-120 
ROMs, at 121 adder, at 122-127 latches, and at 128-130 are delay circuits. 
In this embodiment, arithmetic operations of the above Eqs. 3-(1) to (3) 
are carried out in a time sharing manner to decrease the number of ROMs 
and adders used. 
Operation of the circuit shown in FIG. 18(b) will be described below with 
reference to a time chart shown in FIG. 18(c). R G and B data prior to 
color correction are held in the latches 115-117 in synchronization with 
pixel clocks, respectively. Inputted to the ROMs 118-120 are a color 
selection signal (S1, S0) of 2 bits and the R G and B data as address 
signals. The color selection signal (S1, S0) periodically repeats its 
logical values (0, 0), (0, 1) and (1, 0) per 1/3 clock period. The ROM 118 
outputs the values of a11*R a12*R and a13*R successively upon the color 
selection signal having logical values (0, 0), (0, 1) and (1, 0), 
respectively. At the same time, the ROMs 119 and 120 output successively 
the values of a21*G a22*G a23*G and a31*B a32*B a33*B in a like manner, 
respectively. 
The adder 121 outputs the sum of output values of the ROMs 118-120. In 
other words, C, M and Y data having been subjected to color correction are 
outputted successively in response to logical values (0, 0), (0, 1) and 
(1, 0) of the color selection signal from the adder 121. The latches 
122-124 respectively hold the values of C, M and Y data which are 
outputted from the adder 121 in synchronization with clocks out of phase 
by 1/3 pixel clock period with respect to each other. The latches 125-127 
respectively latch the C, M and Y data outputted from the latches 122-124 
in phase. This permits the C, M and Y data of the same pixel to be 
referred simultaneously from the latches 125-127. 
FIG. 19 shows an embodiment in which black character areas are detected 
based on the algorithm B which utilizes the Y, M and C data having been 
subjected to color correction. The difference from the circuit diagram 
shown in FIG. 17(a) is in a color correction circuit 89' and a min(Y, M, 
C) calculation circuit 97'. Alternatively, if the color correction/UCR 
processing circuit 89 is configured to carry out 100% UCR, the Bk data 
outputted from the color correction/UCR processing circuit 89 could be 
used as black component data. 
FIG. 20(a) shows the output control circuit 95 in detail for use in each of 
the embodiments of the present invention shown in FIGS. 17(a)-17(c) and 
FIG. 19. 
The processing result selection circuit 94 transfers the output of the 
character area processing circuit 93 to the control circuit 95 when the 
image read by the scanner has been determined to be a character area, and 
transfers the output of the picture area processing circuit 92 to the 
control circuit 95 when it has been determined to be picture area. When 
the read image has been determined to be a black character area, the 
output control circuit 95 will not output any Y, M and C data. 
FIG. 20(b) shows an example in which the output control circuit 95 will not 
output any Y, M and C data when the read image has been determined to be a 
black character printed on the white background. 
FIG. 20(c) shows an example in which the output control circuit 95 will not 
output any Y, M and C data when the read image has been determined to be a 
black character printed on the white background, and min(R, G, B) or 
max(Y, M, C) is used as the black component data Bk' for the character 
area processing circuit 93 in case of black characters printed on the 
white background, or max(R, G, B) or min(Y, M, C) is used as the black 
component data Bk" for the same circuit 93 in case of black characters 
printed on the colored background. This example can prevent the occurrence 
of blur and notches of the black characters printed. 
FIGS. 21(a) and 21(b) show circuits for implementing the above-mentioned 
algorithms A and B, respectively. In these figures, LRS is a signal 
indicative of character area and NRS is a signal indicative of a dot area. 
FIG. 21(c) shows a circuit for implementing the algorithm A and outputting 
characters area signals for the respective color components. 
FIG. 21(d) shows a circuit for outputting the logical sum of algorithms A 
and B. 
The present invention has been described in connection with the preferred 
embodiments. But the present invention is not limited to the foregoing 
embodiments, and various modifications and changes can be made by those 
skilled in the art without departing the scope of the present invention.