JPH0638055A - Image processor - Google Patents

Abstract

PURPOSE:To satisfactorily reproduce black characters by emphasizing a black color for the constitutive picture elements of the edge part and fine line part of the black character, strongly emphasizing the fine line part and smoothly emphasizing the edge part excepting for the fine line part. CONSTITUTION:An edge/fine line detection part 4 detects the edge part of an image and the fine line part within prescribed width (such as three picture elements, for example.) A black picture element detection part 7 defines an uncolored high-density picture element as a black picture element candidate. When the picture element of the black picture element candidate is the constitutive picture element of the edge part or the fine line part at the same time, correction data from a color adjustment part 11 are selected. The color adjustment part 11 performs processing to emphasize the black color to Y, M, C and BK data. A correction coefficient Lt is impressed to the color adjustment part 11 for strongly emphasizing the black color for the picture element of the fine line part, and a correction coefficient Le is impressed for weakly emphasizing the black color for the picture element excepting for the fine line part.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus such as a color copying machine, and more particularly to an image processing apparatus capable of reproducing black characters well.

[0002]

2. Description of the Related Art Conventionally, a color original is optically read by a scanner composed of a CCD (charge coupled device) or the like and three primary colors of additive colors of red (R), green (G) and blue (B) are added. A color copying machine is used which is converted into an electric signal and a color image is formed based on the signal. The R, G, and B primary color signals output from the scanner are converted into complementary color data of cyan (C), magenta (M), and yellow (Y) subtractive primary color data. This C,
Appropriate correction is applied to the three primary color data of M and Y, and black (BK) data is generated based on the corrected three primary color data.

For example, the surface of the photoconductor is scanned by a laser beam modulated based on the C signal, and an electrostatic latent image corresponding to cyan is formed on the surface of the photoconductor. This electrostatic latent image is visualized as a toner image using cyan toner and then transferred to a copy sheet. Similarly, in response to the M signal, the Y signal, and the BK signal, magenta, yellow, and black toner images are transferred onto the copy sheet in an overlapping manner, and finally the toner is heat-fixed to achieve a color copy. C, M,
A color image can be reproduced with only the toners of the three primary colors of Y, but if black toner is used, a high density portion can be satisfactorily expressed using black toner, so that color toner can be saved. .

[0004]

In the color copying machine as described above, when a manuscript containing black characters is copied,
There is a problem that the edges of black characters are hard to see.
That is, since the image is expressed by the toners of four colors of cyan, magenta, yellow, and black, bleeding due to the chromatic color component inevitably occurs at the edge portion of the character, and the boundary between the character portion and the background portion is clearly defined. I can't. Therefore, there is a problem that a clear character image cannot be obtained.
Moreover, in a color copying machine, generally, so-called dither processing is applied to each of C, M, Y, and BK data in order to express an intermediate gradation, so that the above tendency is promoted.

SUMMARY OF THE INVENTION An object of the present invention is to solve the above technical problems and to provide an image processing apparatus which can reproduce black characters remarkably well.

[0006]

In order to achieve the above object, the image processing apparatus according to claim 1 optically reads a color image and converts it into three primary color data corresponding to respective densities of the three primary colors. Conversion means for converting and further creating black data corresponding to black density based on the three primary color data, and based on the image data, the target pixel is an achromatic pixel and the density is equal to or higher than a predetermined value. Occasionally, the density gradient in the vicinity of the target pixel is detected based on the black pixel detection unit that sets the target pixel as a black pixel candidate, and the image data of the target pixel and the image data of the pixel adjacent to the target pixel,
When the density gradient is equal to or greater than a predetermined value, the edge detection unit that determines the pixel of interest as a pixel of an edge portion, and whether or not the pixel of interest is a pixel forming a thin line portion that is an image portion having a width equal to or less than a predetermined width. Thin line detecting means for determining, and a first determining means for determining the pixel as a pixel forming an edge portion of a black character when the pixel of interest is determined to be a pixel of an edge portion and is a black pixel candidate. Then, when the pixel of interest is determined to be a pixel forming the thin line portion and the pixel is a black pixel candidate,
The density of the three primary colors is reduced with respect to the second determination unit that determines the pixel as a pixel forming the thin line portion of the black character and the pixel determined to be the pixel of the edge portion of the black character by the first determination unit. The first primary color data and the black data are corrected so as to increase the black density.
And the data determined by the second determination means as the constituent pixels of the thin line portion of the black character so as to decrease the density of the three primary colors and increase the density of black. A second data correction means for performing a stronger correction on the black data than the correction by the first data correction means.

According to the above arrangement, the achromatic pixels and the high density pixels are selected as the black pixel candidates based on the image data corresponding to the respective densities of the three primary colors created by the converting means. Further, when the density gradient in the vicinity of the pixel of interest is equal to or greater than a predetermined value, it is determined that such a pixel constitutes an edge portion of some image. Then, when the pixels determined to form the edge portion are simultaneously selected as the black pixel candidates by the black pixel detecting unit, the pixel is determined to be the pixel forming the edge portion of the black character.

In this way, the edge portion of the black character is detected by using the detection of the edge portion based on the density gradient and the identification of the black pixel together. For the pixels at the edge portion of the black character, the first data correction unit generates black data with increased black density and three primary color data. As a result, black is emphasized in the edge portion of the black character, so that image data clearly expressing the boundary portion of the black character can be obtained.

On the other hand, with respect to pixels forming a thin line portion which is an image portion having a predetermined width or less, when the constituent pixels of the thin line portion are black pixel candidates at the same time, the pixels forming the thin line portion of the black character are selected. It is determined that there is. The pixels determined in this way are subjected to data correction by the second data correction means. The correction of the data by the second data correction means is similar to the correction by the first data correction means in that black is emphasized, but a stronger correction is performed than the correction by the first data correction means. The difference is that black is strongly emphasized.

In this way, in the image of black characters, black is sufficiently emphasized in the constituent pixels of the thin line portion. On the other hand, the pixels in the edge portion other than the thin line portion are relatively weak and black is emphasized. For this reason, it is possible to prevent a problem that a border is formed in the black portion having a relatively large area. In this way, the characters contained in the color image can be reproduced well.

According to a second aspect of the present invention, there is provided the image processing apparatus according to the first aspect.
In place of the data correction means and the second data correction means, the first determination means determines that the pixel is an edge portion pixel of a black character, and the second determination means configures a pixel of a thin line portion of a black character. Third data correction means for correcting the three primary color data and black data so as to decrease the density of the three primary colors and increase the density of black with respect to the pixels that are not determined to be the above, and the first determination means. Is not determined to be a pixel at the edge of a black character, and
Regarding the pixels determined to be the constituent pixels of the thin line portion of the black character by the second determination means, the third primary color data and the black data are modified to reduce the density of the three primary colors and increase the density of black. Fourth data correction means for making stronger correction than the correction by the data correction means, and the first determination means determine the pixel at the edge portion of the black character, and the second determination means determines the black character For the pixels determined to be the constituent pixels of the thin line portion, the three primary color data and the black data are corrected more strongly than the correction by the fourth data correction means so that the density of the three primary colors is reduced and the density of black is increased. And a fifth data correction means for performing.

According to this structure, the emphasis of black on the edge portion and the thin line portion of the black character changes in three steps.
That is, in black characters, the edge portions other than the thin line portions are gently emphasized, the thin line portions other than the edge portions are slightly strongly emphasized, and the edge portions of the thin line portions are strongly emphasized. This makes it possible to reproduce the black character better. The image processing apparatus according to claim 3, wherein the thin line detection means detects a rising edge pixel whose density sharply increases when a predetermined detection line passing through the target pixel is traced in one direction, and the rising edge detection means. A predetermined number of pixels are provided between the falling edge detection means for detecting the falling edge pixels whose density is sharply reduced when tracing the detection line in the one direction and the rising edge pixels and the falling edge pixels. Means for determining an image portion between the pixel of the rising edge and the pixel of the falling edge as a thin line portion when the threshold value is equal to or less than the threshold value, and the target pixel when the target pixel is located in the thin line portion. Is included in the thin line portion as a constituent pixel.

With this configuration, the rising edge and the falling edge of the density are detected on the predetermined detection line passing through the pixel of interest. Then, the number of pixels between the rising edge and the falling edge is compared with a predetermined threshold value, and the line portion is detected based on the comparison result. When the pixel of interest is located in this thin line portion, this pixel of interest is determined as a constituent pixel of the thin line portion.

According to another aspect of the image processing device of the present invention, the edge detecting means determines whether or not the pixel of interest is an edge pixel based on the data of one specific color among the three primary color data. The thin line detection means determines whether or not the pixel of interest is a constituent pixel of the thin line portion based on the data of the specific color.

As a result, the structures of the edge detecting means and the thin line detecting means can be simplified. Magenta is preferably applied to the specific color when, for example, the three primary color data correspond to yellow, magenta, and cyan. This is because the magenta component in the color image is the closest to the human visual characteristics.

An image processing apparatus according to a fifth aspect of the present invention further comprises smoothing means for creating data in which density gradients in the vicinity of the target pixel are smoothed based on image data of the target pixel and pixels adjacent to the target pixel. Including, the edge detection means,
Based on the image data that has been smoothed by the smoothing means, it is determined whether or not the pixel of interest is an edge pixel, and the thin line detecting means is smoothed by the smoothing means. It is characterized in that whether or not the pixel of interest is a constituent pixel of the thin line portion is determined based on the image data after being processed.

According to this structure, after the density gradient is smoothed by the smoothing means, the edge detection processing based on the density gradient is performed by the edge detection unit, so that the pixels in the area where the density gradient is relatively gentle are detected. Since it is prevented from being detected as a pixel of the edge portion, the edge portion of the image can be surely detected. That is, the influence of noise in the color image can be reliably prevented.

The same applies to the processing by the fine line detecting means, and it is possible to prevent noise or the like in the color image from being mistakenly recognized as the fine line portion. The image processing apparatus according to claim 6, wherein the smoothing unit is configured to perform the above-mentioned 3 in pixels adjacent to a pixel of interest.
Data for smoothing a density gradient in the vicinity of the pixel of interest is created based on data of any one specific color of the primary color data, and the edge detecting means is smoothed by the smoothing means. It is to determine whether the pixel of interest is the pixel of the edge portion based on the data of the specific color after the correction, and the thin line detecting unit detects the specific color after the smoothing by the smoothing unit. It is characterized by determining whether or not the pixel of interest is a pixel at the edge portion based on the data.

According to this configuration, the smoothing process, the edge detecting process, and the fine line portion detecting process are performed based on the data of one specific color. Therefore, the configurations of the smoothing unit, the edge detecting unit, and the fine line detecting unit are simple. Can be converted. Moreover, since the edge detection processing and the thin line portion detection processing are performed based on the data after the smoothing processing, the edge portion and the thin line portion of the image can be reliably detected.

[0020]

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. FIG. 1 is a block diagram showing an electrical configuration of a main part of a color copying machine which is an image processing apparatus according to an embodiment of the present invention. This image processing apparatus is read by a scanner or the like on the basis of three primary color data of yellow (Y), magenta (M), and cyan (C) and black (BK) data created from these three primary color data. Pixels constituting the edge portion of a black character existing in a read image are extracted, and the boundary between the black character portion and the background portion is made clear to reproduce the black character clearly.

A color original to be copied is optically read by a scanner (not shown) composed of a CCD (charge coupled device) or the like, and is subjected to the red (R), green (G), and blue (B) addition methods. It is photoelectrically converted into three primary color signals. 3 by this addition method
The primary color signals are converted into three primary color signals by the subtractive color method of yellow (Y), magenta (M), and cyan (C), which are complementary colors, and the signals are subjected to correction for color reproduction faithful to the original image. Then, Y, M, and C primary color image data is created. Further, BK data is created based on the three primary color data of Y, M and C. This BK data is data for compensating for the insufficient density in the high density portion with black toner, and for example, a predetermined correction coefficient α (for example, 0.5 to 1) is added to the minimum value of the three primary color data of Y, M, and C. It is created by removing the multiplied value from each of the three primary color data and using the removed value as the BK data. In the present embodiment, the conversion means is configured to include the above-mentioned scanner and the components for creating the Y, M, C and BK data.

Of the three primary color data of Y, M and C, M data corresponding to magenta is supplied to the smoothing unit 2M for smoothing the density gradient through the timing adjusting unit 1M. The data smoothed by the smoothing unit 2M is given to an edge / fine line detecting unit 4M for detecting an edge portion of an image such as a character through a timing adjusting unit 3M. The edge / thin line detection unit 4M detects whether or not each pixel is an edge pixel by detecting a density gradient between the pixel of interest and a pixel in the vicinity thereof, and for the pixel of the edge portion, Logic "1" for edge detection signal EDGE
And That is, a pixel for which the edge detection signal EDGE has a logic "1" is a pixel at the edge portion of any image.

The edge / fine line detector 4M also detects a fine line portion in the image and sets the fine line detection signal THIN to logic "1" for this fine line portion. In the present embodiment, the thin line portion is an image portion in which the width of the image read by the image scanner in the main scanning direction or the sub scanning direction is within 3 pixels. The definition of such a thin line portion may be arbitrarily selected as necessary, and for example, the image width in the diagonal direction which is an intermediate direction between the main scanning direction and the sub scanning direction is 3
An image portion within pixels may be defined as a thin line portion. Also,
The number of pixels of the image width for determining whether or not it is a thin line portion may be selected to any number of pixels other than 3 pixels.

As described above, the edge / fine line detection unit 4
The reason why the process in M is performed based on the M data corresponding to magenta is that the magenta component forming the color image is the closest to the human visual characteristics. on the other hand,
The three primary color data of Y, M and C are also stored in the timing adjustment unit 6
It is also given to the black pixel detecting portion 7 via Y, 6M and 6C. The black pixel detection unit 7 detects an achromatic pixel based on the mutual difference of the three primary color data of Y, M, and C, and when the density of the achromatic pixel is equal to or more than a predetermined value, the pixel concerned. Are black pixel candidates. The black pixel detection signal BLACK is set to logic “1” for the black pixel candidate, and this signal is input to one input terminal of the AND circuit 8.

At the other input terminal of the AND circuit 8, the output signals EDGE and TH of the edge / fine wire detecting section 4M are inputted.
IN is given. Therefore, the output of the logical product circuit 8 is output to the pixels determined by the edge / thin line detection unit 4M to be the pixels at the edge portion or the constituent pixels of the thin line portion, and the black pixel candidate determined by the black pixel detection unit 7. Only logical "1" is obtained. In this case, it can be said that the pixel is a pixel forming an edge portion of a black character or a pixel forming a thin line portion of a black character.

The output signal of the AND circuit 8 is given from the line 9 to the selector 10 described later as a selection control signal. Y, M, which have passed through the timing adjustment units 6Y, 6M, 6C
The C three primary color data is also given to the color adjusting unit 11. The BK data whose timing is adjusted by the timing adjusting unit 6BK is also input to the color adjusting unit 11. The color adjustment unit 11 emphasizes the BK data,
In other words, it generates a signal corresponding to a black-colored binary image. The output of this color adjustment unit 11 is
It is input to the selector 10.

The selector 10 also includes a color adjusting section 11
Timing adjustment section 6Y, 6M, 6C, 6BK
The three primary color data of Y, M, and C and BK data are given through the line 12 and further through the timing adjusting unit 13. The selector 10 responds to the selection control signal from the line 9 with Y,
M, C, BK data and Y from the timing adjustment unit 13,
One of Y, M, and M, C, and BK data
C and BK data will be selected.

That is, the data from the color adjusting unit 11 is selected for the pixels forming the edge portion of the black character and the pixels forming the thin line portion of the black character, and the timing adjusting unit is selected for the remaining pixels. The data from 13 will be selected. Youu output from this selector 10
BK corresponding to the three primary color data of t, Mout, Cout and black
Based on the out data, the laser beam that forms an electrostatic latent image corresponding to each color image on the photoconductor is modulated.

The degree of image enhancement in the color adjusting section 11 is determined by the correction coefficient L selectively derived from the selector 14.
Based on t and Le (collectively referred to as “correction coefficient L”, Lt <Le), there are two types.
The correction coefficient Lt is a correction coefficient for thin line pixels for emphasizing pixels in the thin line portion, and the correction coefficient Le is a correction coefficient for normal edge pixels for emphasizing normal edge pixels other than the thin line portion. The color adjustment unit 11 strongly emphasizes the BK data when the correction coefficient Lt for thin line pixels is given, and relatively weakly emphasizes the BK data when the correction coefficient Le for normal edge pixels is given.

The selector 14 includes an edge / fine line detecting section 4
The thin line detection signal THIN from M is given as a selection control signal. Then, when the thin line detection signal THIN is the logic "1" indicating that the pixel of interest is the pixel of the thin line portion, the thin line pixel correction coefficient Lt is selected and output. Further, when the thin line detection signal THIN is a logic “0” indicating that it is not a pixel in the thin line portion, the normal edge pixel correction coefficient Le is selected and given to the color adjusting unit 11.

As described above, in this embodiment, the first data correction means and the second data correction means including the AND circuit 8, the color adjusting section 11, the selector 10 and the selector 14 are included.
The data correction means is constructed. FIG. 2 is a block diagram showing a configuration example of the timing adjusting units 1M and 3M. The M data input according to the scanning order when the laser beam scans the photoconductor is first input to the smoothing unit 2M as the data D2 via the D (Delayed) type flip-flop (DFF) 15. Further, the data D2 is delayed by one line in a first-in first-out memory (hereinafter referred to as "FIFO") 16 and input to the smoothing unit 2M as data D1 via the flip-flop 17. This data D1 is FIF
Flip-flop 1 after being delayed by one line at O18
The data D0 is input to the smoothing unit 2M via 9. As a result, the data D0, D1, and D2 provided in parallel to the smoothing unit 2M are data corresponding to pixels that are adjacent in the sub-scanning direction when the laser beam scans the photoconductor.

The timing adjusting section 3M includes five FIFOs 111, 112, 1 for delaying the data by one line.
13, 114 and 115 and D-type flip-flops 116, 117, 1 for latching data from each FIFO.
18, 119 and 120 are alternately connected. Then, each D-type flip-flop 116-12
0 output data DL5, DL4, DL3, DL2, DL
1 and DL0 are input to the edge / fine line detection unit 4M. With this configuration, the edge / fine line detection unit 4M has
Data for 5 pixels arranged in the sub-scanning direction when the laser beam scans the photoconductor is input in parallel.

FIG. 3 is a diagram for explaining the smoothing processing in the smoothing section 2M. The smoothing process is a process of smoothing the concentration gradient. The smoothing process for the target pixel S0 is performed by the density Q0 of this pixel, the densities Q1 and Q4 of the pixels S1 and S4 adjacent in the sub-scanning direction 27, and the main scanning direction 28.
Is performed on the basis of the densities Q2 and Q3 of the pixels S2 and S3 adjacent to each other. That is, the weighting factors of the pixels S0 to S4 are C0, C1, C2, C3, C4 (where C0 + C1
+ C2 + C3 + C4 = 1) and C1 = C2 = C3 = C4 = C (constant) (1), the density Qs of the pixel S0 after the smoothing process is

[0034]

[Equation 1]

Is calculated as Here, C = 1 / K (3) (where K is an integer and K ≧ 5), and Q1 + Q2 + Q3 + Q4 = Qn (4) = (1-4 / K) Q0 + (Q1 + Q2 + Q3 + Q4) / K = Q0-4Q0 / K + Qn / K ... (5) is obtained.

A concrete structure of the smoothing unit 2M for realizing such smoothing processing is shown in FIG. The data D1 (see FIG. 2) from the timing adjustment unit 1M is
The D-type flip-flops 31, 32, and 33 delay the signal by 3 clocks (clock signal is represented by CLK) and input to the adder 34. In addition, 1 in the flip-flop 31
The data delayed by the clock is also given to the adder 34. The output data of the flip-flop 32 is the target pixel S0.
Suppose that the density Q0 corresponding to the above is represented, the outputs of the flip-flops 31 and 33 represent the density Q3 and Q2 corresponding to the pixels S3 and S2, respectively.

On the other hand, the data D0 from the timing adjusting section 1M is delayed by 2 clocks by the flip-flops 35 and 36 and given to the adder 34. The output data of the flip-flop 36 represents the density Q1 of the pixel S1. Further, the data D2 is the flip-flop 3
The data is delayed by 2 clocks by 7, 38 and input to the adder 34 as data representing the density Q4 of the pixel Q4. Input data is added in the adder 34, and data corresponding to the above value Qn is created.

The output data of the flip-flop 32 representing the density Q0 is multiplied by 4 by the integrator 39 to generate 4Q0. Further, in the divider 40 that divides the input data by the constant K, 4Q0 / K is created, and this data is given to the subtractor 41. Data representing the density Q0 is also input to the subtractor 41 from the line 42, and the result (Q0-4Q0 / K) of the subtraction is given to the adder 44 from the line 43.

The adder 44 also outputs the output Q of the adder 34.
A value Qn / K obtained by dividing n by a constant K in the divider 45 is input, and the addition result of the adder 44 is
The density Qs after the smoothing process shown by the equation (5) is obtained. The data corresponding to this density Qs is the timing adjustment unit 3M.
(See FIG. 2). FIG. 5 is a diagram for explaining the processing in the edge / fine line detection unit 4M.
The edge / thin line detection unit 4M performs edge detection processing and thin line portion detection processing. The edge detection process is a process of detecting a pixel in a portion having a steep density gradient as an edge of an image, and the fine line part detection process is a process of detecting a constituent pixel of a fine line part having an image width of 3 pixels or less. Is.

Such processing is performed by the pixels s00 to 04, s of 5 × 5 arranged in matrix including the target pixel s11.
10 to s14, s20 to s24, s30 to s34, s4
Each concentration of 0 to s44 q00 to q04, q10 to q14,
It is performed based on q20 to 24, q30 to q34, q40 to q44. In the edge detection process, it is detected whether the pixel of interest s11 is a rising edge pixel or a falling edge pixel. This edge detection processing is performed in the main scanning direction RM and the sub scanning direction RS.

Specifically, in order to detect the edge in the main scanning direction RM, q11-q10> t (6) q11-q12> t (7) is established. Can be checked respectively. t is a predetermined threshold value. When the expression (6) is satisfied, when the pixel density is checked along the main scanning direction RM, the target pixel s1
This is the case where the concentration rapidly increases toward 1. Therefore, the target pixel s11 is determined to be a pixel having a rising edge.

When the expression (7) is satisfied, the density is sharply reduced from the target pixel s11 to the pixel s12 on the downstream side in the main scanning direction RM. Therefore, at this time, the target pixel s11 is determined to be the pixel of the falling edge. Similarly, with respect to the sub-scanning direction RS, whether or not q11-q01> t ... (8) q11-q21> t. The expression (8) is established when the pixel density is rapidly increased toward the target pixel s11 when the pixel density is examined along the sub-scanning direction RS. Therefore, the pixel of interest s11 is determined to be the pixel of the rising edge. On the contrary, if the expression (9) is satisfied, the pixel of interest s11 is determined to be the pixel of the falling edge.

Next, the thin line portion detection processing will be described.
In the thin line portion detection process, it is checked whether or not there is a falling edge pixel within the range of 3 pixels from the rising edge pixel in the main scanning direction RM or the sub scanning direction RM, and based on this, each pixel is detected. Is determined to be a constituent pixel of the thin line portion. Specifically, in order to determine the main scanning direction RM, when the target pixel s11 is a pixel having a rising edge, q11-q12> t ... (10) q12-q13> t. 11) q13-q14> t ················································································. That is, if any of these is satisfied, the pixel of interest s11 or the pixel s12 or s13 located downstream of the pixel of interest s11 in the main scanning direction RM is the pixel of the falling edge. It will be.

That is, if the expression (10) is satisfied, the target pixel s11 is a pixel forming an image having a width of 1 pixel in the main scanning direction RM. If the equation (11) is satisfied, the pixels s11 and s12 are determined to be the main scanning direction RM
Is a pixel forming an image having a width of 2 pixels. Further, if the expression (12) is established, the pixels s11, s12, s1
Reference numeral 3 is a pixel forming an image having a width of 3 pixels along the main scanning direction RM.

The same applies to the sub-scanning direction RS. Whether the following formula (13), formula (14) or formula (15) is satisfied at the same time when the target pixel s11 is a pixel having a rising edge. Based on the above, the constituent pixels of the thin line portion are detected. q11-q21> t ··· (13) q21-q31> t ··· (14) q31-q41> t ··· (15) FIG. 6 shows a specific configuration of the edge / fine line detection unit 4M. It is a block diagram which shows an example. Data DL0, DL for five lines that have been subjected to the smoothing process given from the timing adjustment unit 3M
1, DL2, DL3 and DL4 are input to D-type flip-flops F04, F14, F24, F34 and F44, respectively.

The data DL1 is the flip-flop F0.
4, F03, F02, F01, and F00 are delayed by one clock, and the output data of each flip-flop F00 to F04 is the density data q00 of the pixels s00 to s04 in FIG.
Is input to the edge / fine line determination processing unit 160 as q04. Similarly, the data DL2 is the flip-flop F1.
The output of each flip-flop F10-F14 is delayed by one clock in each of pixels 4-10.
The density data q10 to q14 of 14 are given to the edge / fine line determination processing unit 160. Similarly, data DL
2, DL3 and DL4 are flip-flops F2
4 to F20, F34 to F30, F44 to F40,
Pixels s20 to s24, s30 to s34, s40 to s44
Concentration data q20 to q24, q30 to q34, q4
It is given to the edge / thin line determination processing unit 160 as 0 to q44.

In this way, the density data of the 5 × 5 Matrices-arranged pixels shown in FIG. 5 are input in parallel to the edge / fine line determination processing unit 160. The edge / thin line determination processing unit 160 includes an edge / thin line determination processing circuit 160M that performs processing in the main scanning direction RM, an edge / thin line determination processing circuit 160S that performs processing in the sub-scanning direction RS, and these processing circuits 160M and 160S.
And an output circuit 210 for producing output signals EDGE and THIN from the signal from.

FIG. 7 is a block diagram showing the arrangement of an edge / fine line determination processing circuit 160M which performs processing in the main scanning direction RM. The edge / fine line determination processing circuit 160M is
A rising edge detection unit 161M that determines whether the target pixel s11 is a rising edge pixel, and a pixel s10 immediately before the target pixel s11, a target pixel s11, and pixels s12, s13, and s14 that follow the target pixel s11 have a falling edge, respectively. It has a falling edge detection unit 162M that detects whether or not it is a pixel, and a thin line detection unit 163M that determines whether or not the pixel of interest s11 is a pixel forming a thin line portion.

The rising edge detector 161M subtracts the density data of the pixel s10 adjacent to the target pixel s11 on the upstream side in the main scanning direction RM from the density data q11 of the target pixel s11 to obtain a difference in density (q11-q10). ) Has a difference calculator 170M. This difference calculator 1
The difference (q11-q10) between the concentrations calculated at 70M is
It is compared with the above-mentioned threshold value t in the comparator 180M.

The comparator 180M has a difference (q11-q1).
When 0) is larger than the threshold value t, a logic "1" signal is output, and otherwise a logic "0" signal is output. That is, if the comparator 180M outputs a signal of logic "1", the target pixel s11 is a pixel at the rising edge. The falling edge detection unit 162M calculates a difference (q10-q11) between the density data q10 of the pixel s10 located upstream of the pixel of interest s11 in the main scanning direction RM and the density data q11 of the pixel of interest s11. 171M. Furthermore, the density data q11 of the target pixel s11
From the density data q12 of the pixel s12 adjacent to the target pixel s11 on the downstream side in the main scanning direction RM (q
11-q12), a difference calculator 172M that subtracts the density data q12 of the pixel s13 from the density data q12, and a difference calculator 174M that subtracts the density data q14 of the pixel s14 from the density data q13.
have.

The outputs of the difference calculators 171M to 174M are compared with the threshold value t by comparators 181M to 184M, respectively. This comparator 181M is used for each difference calculator 171M.
When the difference calculated at ˜174 M is larger than the threshold value t, a signal of logic “1” is output. Either comparator 1
If a signal of logic "1" is output from 81M to 184M, the pixel s10, s11, s12, or s13 corresponding to the comparator that has output the signal of logic "1" is a pixel of the falling edge. Become.

The fine line detector 163M has a D-type flip-flop 191M to which the output signal of the comparator 180M of the rising edge detector 161M is applied to the data input terminal. Further, the output signals of the comparators 182M, 183M and 184M of the falling edge detector 162M are given to the logical sum circuit 192M. This OR circuit 192
The output signal of M is given to one input terminal of the AND circuit 193M, and the output of the comparator 180M of the rising edge detecting section 161M is given to the other input terminal of the AND circuit 193M. There is.

The output of the AND circuit 193M is input to the clock input terminal of the flip-flop 191M.
Furthermore, a signal obtained by inverting the output of the comparator 180M by the inverter 194M is applied to the clear input terminal of the flip-flop 191M. On the other hand, the rising edge detector 16
The output of the comparator 180M of 1M and the output of the comparator 182M of the falling edge detection unit are the edge detection processing unit 164M.
Is given to. The edge detection processing unit 164M is composed of a logical sum circuit 169M, and when a signal of logic "1" is given from at least one of the comparators 180M and 182M, its output signal MEDGE is set to logic "1". To do.

The signal of this logic "1" is the target pixel s11.
Indicates that the pixel is a rising edge or falling edge pixel in the main scanning direction RM. When the output signal MTHIN of the flip-flop 191M is logic "1", the target pixel s11 is a pixel forming a thin line portion having a width of 3 pixels or less along the main scanning direction RM. Details will be described later.

FIG. 8 is a block diagram showing the arrangement of an edge / fine line determination processing circuit 160S which performs processing in the sub-scanning direction RS. In FIG. 8, the edge / fine line determination processing circuit 1 that performs processing in the main scanning direction RM
For the parts corresponding to the respective parts of 60M, the same numerals as the numeral parts of the reference numerals shown in FIG. The edge / fine line detection processing in the sub-scanning direction RS is performed one line ahead of the edge detection processing in the main scanning direction RM. That is, for example, when the edge / thin line detection process in the main scanning direction RS is performed on the pixel of interest s11, the process in the sub-scanning direction RS is performed by focusing on the pixel s12. The signals SEDGE and STHIN, which are the detection results, are transferred to the FIFO 24.
The lines 1 and 2 are delayed by one line and output in synchronization with the edge / fine line detection processing in the main scanning direction RM.

The rising edge detector 161S calculates the difference (q11-q01), and the difference (q11-q01) is calculated.
01) exceeds the above threshold t, the comparator 180S
From this, a signal of logic "1" indicating that the pixel of interest s11 is a pixel with a rising edge is derived. On the other hand, in the falling edge detection unit 162S, the difference (q01-q11),
(Q11-q21), (q21-q31), (q31-
q41) is calculated, and each difference exceeds the threshold value t,
The signals of logic "1" indicating that the pixels s01, s11, s21, and s31 are falling edge pixels are output from the comparators 181S to 1814S, respectively.

In the thin line detector 163S, the output signal of the comparator 180S of the rising edge detector 161S and the output signal of the logical sum circuit 192S are given to the logical product circuit 193S. The output signal of the AND circuit 193S is OR
It is input to the FIFO 242 via the gate 195. The output signal of the FIFO 242 is also input to the OR gate 195 via the flip-flop 243.

In the FIFO 241, the clock signal CLK
The data is output at the rising edge of and the data is written at the falling edge of the clock signal. Therefore, after the data is given to the flip-flop 243, the OR
The signal from gate 195 is read. The output signal of the comparator 181S is applied to the clear input terminal of the flip-flop 243 through the inverter 194S.

The output signal of the comparator 182S and the output signal of the comparator 180S of the rising edge detecting section 161S constitute an OR circuit 169S constituting the edge detection processing section 164S.
Has been entered in. When the output signal SEDGE of the logical sum circuit 169S has the logic "1", the target pixel s1
1 is a pixel at the rising edge or the falling edge in the sub-scanning direction RS.

On the other hand, when the target pixel s11 is a pixel having a rising edge and at the same time the pixel s11, s21 or s31 is a pixel having a falling edge, the AND circuit 193S.
Output becomes "1". This signal is written from the OR gate 195 to the FIFO 242. 1 in FIFO242
The signal delayed by the line is again written into the FIFO 242 via the OR gate 195, so that in the end, the pixel s1
The signal STHIN becomes "1" for 1, s12, s13.

On the other hand, the output signal of the comparator 181S is "1".
Therefore, when the pixel s01 on the upstream side in the sub-scanning direction RS with respect to the pixel of interest s11 is a falling edge pixel,
The flip-flop 243 will be cleared. Therefore, the output of the flip-flop 243 is "0" even when the signal STHIN for the pixel one line before is "1".

Therefore, for example, the pixels s11 and s2
If 1 and s31 are pixels forming the thin line portion, the signal STHIN output corresponding to them is logic "1", and the signal of logic "0" is output to the pixel s41. In this way, the output signal STHIN of the FIFO 242 is
Is a logic "1", the pixel of interest in the process related to the main scanning direction RS (the pixel one line before the pixel of interest in the sub scanning direction RS) is in the sub scanning direction RS. It is a constituent pixel of the thin line portion having a width of 3 pixels or less.

FIG. 9 is a block diagram showing the structure of the output circuit 210. In this output circuit 210, the OR circuit 21
The logical sum of the signals MEDGE and SEDGE is obtained by 1, and the output signal of the logical sum circuit 211 is used as the edge detection signal EDGE. Further, the logical sum circuit 212 logically sums the signals MTHIN and STHIN to obtain a thin line detection signal THIN. Then, the edge detection signal ED
The GE and the thin line detection signal THIN are input from the logical sum circuit 213 to the logical product circuit 8 in FIG. Further, the thin line detection signal THIN is given to the selector 14 as a selection control signal.

FIG. 10 is a diagram for explaining the operation of each of the edge / fine line determination processing circuits 160M and 160S shown in FIGS. 7 and 8. In FIG. 10, an example of the image data after the smoothing process and the output signals MEDGE, S of the edge detection processing units 164M, 164S accompanying the change of the target pixel are shown.
Changes in the output signals MTHIN and STHIN of the EDGE and the thin line detection units 163M and 163S are shown. Note that, in FIG. 10, the black pixel portion is shown by hatching.

For example, a case where the pixel of interest s11 moves along the line L1 along the main scanning direction RM will be described. When the pixel of interest s11 is the pixel P1 on the line L1, the difference (q11-q10) becomes large, and therefore the output of the comparator 180M becomes logic "1". Therefore, the output signal MEDGE of the edge detection processing unit 164M has the logic “1” as indicated by the reference numeral 200. On the other hand, when the target pixel s11 is the pixel P1, the pixel P on the line L1
3 corresponds to the pixel s13 in FIG. Therefore, the difference calculated by the difference calculator 174M (q13-q14)
Becomes a large value, and the output of the comparator 184M is logic "1".
Becomes

As a result, the output of the AND circuit 193M becomes logic "1", so that the signal of logic "1" given from the comparator 180M is latched to the data input terminal of the flip-flop 191 and the signal MTHIN becomes As indicated by reference numeral 201, the logical value is “1”. Pixel of interest s11
Is a pixel P2 on the line L1, this pixel P2
2 is a black pixel, and the main scanning direction R with respect to this pixel P2
Since the pixel P1 located on the upstream side of M is also a black pixel, the output of the rising edge detection unit 161M is logical "0".
Further, since the pixel P3 on the downstream side in the main scanning direction RM with respect to the pixel P2 which is the target pixel s11 is also a black pixel, the output of the comparator 182M in the falling edge detection unit 162M also becomes a logic “0”. Therefore, the signal MEDGE becomes logic "0".

On the other hand, since the pixel P3 corresponding to the pixel s12 is a black pixel and the pixel P4 corresponding to the pixel s13 is a white pixel, the output of the comparator 183M is logic "1".
However, since the output of the comparator 180M is logic "0", the output of the AND circuit 193 is logic "0". Therefore, the output signal MTHIN of the flip-flop 191 is
It is kept at logic "1".

When the pixel of interest s11 moves to the pixel P3,
The output of the comparator 182M becomes logic "1". For this reason,
The output signal MEDGE of the edge detection processing unit 164M has a logic "1". However, even in this case, the comparator 180M
The output signal of MHI is kept at logic "0", so the signal MTHI
N is held at logic "1". The pixel of interest s11 is the pixel P
When the value becomes 4, the pixel P3 corresponding to the pixel s10 located on the upstream side in the main scanning direction RM with respect to the target pixel s11 is the pixel having the falling edge, and therefore the output signal of the comparator 181M becomes the logic “1”. . Therefore, the flip-flop 19
1M is cleared and the signal M as indicated by reference numeral 202
THIN will fall.

In this way, the pixels P1 and P3 are determined to be the pixels of the edge portion based on the signal MEDGE. The pixels P1, P2, P3 are also based on the signal MTHIN.
Are determined to be pixels forming the thin line portion. Similarly,
When the pixels P5 and P6 become the target pixel s11, the signal MED
GE becomes a logic "1", and these pixels are determined to be edge pixels. However, when the target pixel s11 is located at the pixel P5 at the rising edge, 3 including this pixel P5
There are no falling edge pixels within the pixel. Therefore, the outputs of the comparators 182M, 183M and 184M are never logic "1", and the flip-flop 191 does not latch the signal of logic "1".

As a result, the signal MTHIN is the target pixel s1.
In the process in which 1 goes from the pixel P5 to the pixel P6, it is kept at the logic "0". Therefore, the pixels at positions P5 to P6 are not discriminated as the pixels forming the thin line portion. On the other hand, assume that the pixel of interest s11 is moved in the sub-scanning direction RS along the line L2. At this time, the edge / fine line determination processing circuit 160S corresponding to the sub-scanning direction RS having the configuration of FIG.
Operates almost similarly to the edge / thin line determination processing circuit 160M corresponding to the main scanning direction RM and outputs the signals SEDGE and STHIN having the waveforms shown in FIG.

However, as described above, the edge / fine line detection processing in the sub-scanning direction RS is performed one line ahead of the main scanning direction RM, and the signals SEDGE and STHIN having the waveforms shown in FIG. , 242
This is a signal waveform after being delayed by one line at. In addition, since the processing for each pixel is actually performed in the order of consecutive pixels along the main scanning direction RM, the signal SE in FIG.
DGE and STHIN are not continuous signal waveforms in time.

In the fine line portion detection processing in the edge / fine line determination processing circuit 160M corresponding to the main scanning direction RM, a detection line along the main scanning direction RM passing through the pixel of interest is assumed, and this detection line is set in the main scanning direction RM. Pixels at locations where the density increases sharply when traced along are detected as pixels at the rising edge, and pixels at the falling edge where the density sharply decreases along the main scanning direction RM within a range of 3 pixels from the pixel at the rising edge. Can be said to be a process for determining whether or not exists. When the falling edge exists within the range of 3 pixels from the rising edge, and when the pixel of interest is located in the range from the rising edge to the falling edge,
The signal STHIN is set to logic "1".

The same applies to the edge / fine line determination processing circuit 160S corresponding to the sub-scanning direction RS. In the present embodiment, whether or not the pixel of interest is a rising edge pixel is detected by the rising edge detection unit 161M of FIG. 7 and the rising edge detection unit 161S of FIG. Further, whether the pixel of interest is a falling edge pixel or not is determined by the difference calculator 172M and the comparator 1 in the falling edge detector 162M in FIG.
82M and the difference calculator 172S and the comparator 182S in the falling edge detector 162S of FIG. Therefore, each of these components and the OR circuits 169M and 169S and the OR circuit 211 of FIG.
It can be said that the edge detecting means is configured by the above.

On the other hand, the thin line detecting means includes rising edge detecting sections 161M and 161S, falling edge detecting sections 162M and 162M,
162S, the thin line detection units 163M and 163S, the logical sum circuit 212 of FIG. 9, and the like. FIG. 11 is a block diagram showing the configuration of the timing adjusting unit 6Y. The timing adjusting unit 6Y includes three FIFOs 6
1, 62, 63 and four flip-flops 64, 6
5, 66, 67 are alternately connected, and the Y data is synchronized with the edge detection signal derived from the edge detection unit 4M in consideration of the data delay time in the timing adjustment units 1M, 3M. Is given to the black pixel detecting section 7, the color adjusting section 11 and the like. The same applies to the configurations of the other timing adjusting units 6M, 6C, and 6BK.

FIG. 12 is a block diagram showing the basic structure of the black pixel detecting section 7. The black pixel detection unit determines an achromatic pixel having a high density as a black pixel candidate, and sets the black pixel detection signal BLACK to logic "1" for the black pixel candidate. Timing adjustment unit 6Y,
Subtractor 7 for Y, M, C three primary color data from 6M, 6C
0, and the difference between each data (Y−M), (M−
C) and (C-Y) are created. The differences (Y-M), (M-C), and (C-Y) between the data are calculated by the absolute value calculation unit 7.
1 is given to each absolute value | Y−M |, | M−C
|, | C−Y | is created, and the absolute value is given to the comparator 72. In the comparator 72, each absolute value | Y−M |, | M
−C |, | C−Y | and the threshold value T1 are compared, and all absolute values | Y−M |, | MC−, | C−Y |
In the following cases, the pixel of interest is determined to be a gray pixel which is an achromatic pixel, and a signal of logic “1” is derived on the line 73. Absolute values | Y-M |, | MC-, | C
When any one of -Y | exceeds the threshold value T1, it is determined that the pixel is a color pixel.

That is, in an achromatic pixel, the difference between the three primary color data of Y, M, and C is basically zero, and a large difference does not occur even after various corrections. Therefore, B = Max {| Y−M |, | M−C |, | C−Y |} ... The maximum value B of the difference between the three primary color data given by (16) is a predetermined value. When there is a relationship of B ≦ T1 ... (17) with respect to T1, it can be determined that the pixel is a gray pixel which is an achromatic pixel, and there is a relationship of B> T1 ... (18). At times, the pixel can be determined to be a color pixel.

Such processing is performed by the difference between the three primary color data |
It is possible to replace with the above-described processing for determining whether or not any of Y-M |, | MC |, | C-Y | exceeds the predetermined value T1. Can be simplified. On the other hand, the three primary color data of Y, M, C from the timing adjustment units 6Y, 6M, 6C are
It is also provided to the comparator 74. The comparator 74 determines the yellow density level Y of the pixel of interest represented by each data.
d, the density level Md of magenta and the density level Cd of cyan are all equal to or greater than a predetermined threshold value T2,
A signal of logic "1" is derived from the line 75 as a high density pixel detection signal. When any of the density levels is lower than the threshold value T2, a signal of logic "0" is derived on the line 75 as the low density pixel detection signal.

The signals from the lines 73 and 75 are input to the AND circuit 76. In the logical product circuit 76, after all, the comparator 72 determines that the pixel of interest is a gray pixel, and the comparator 7
The signal of logic "1" is derived only when the pixel 4 determines that the pixel of interest is a high density pixel. This signal of logic “1” indicates that the pixel of interest is a black pixel candidate. Figure 1
3 is a block diagram showing a basic configuration of the color adjusting unit 11. In the color adjustment unit 11, the input Y,
The three primary color data of M and C and the BK data are corrected to the data of Y ', M', C ', and BK' shown in the equations (19) to (22) below.

Y '= Y-BK / L (19) M' = M-BK / L (20) C '= C-BK / L (21) BK' = BK + BK / L (22) However, in the above equations (19) to (22), L is a correction coefficient given from the selector 14 of FIG. 1, and L = Lt or L = Le is there. Since Lt <Le as described above, the BK data is strongly emphasized when the thin line pixel correction coefficient Lt is adopted, and the BK data is relatively weakly emphasized when the normal edge pixel correction coefficient Le is adopted.

It is preferable that this correction coefficient L satisfies 1 / L≤1 / α-1 (23) when the correction coefficient at the time of generating the BK data is α. The correction coefficient α at the time of generating the BK data is a ratio when the minimum data of the three primary color data of Y, M, and C is replaced with the BK data.

By the above correction, a set of correction data Y ', M', C ', BK' in which the BK data is emphasized can be obtained. The BK data from the timing adjustment unit 6BK is the divider 8 that divides the input data by the above correction coefficient L.
Input to 1. The output of the divider 81 becomes BK / L, and this data is added to BK by the adder 82 to produce BK '.
= BK + BK / L is generated. This correction data BK '
Are provided to the selector 10.

The output of the divider 81 is also given to the subtractor 83. In this subtractor 83, the three primary color data of Y, M, C from the timing adjustment units 6Y, 6M, 6C and the data BK / K from the divider 83 are subtracted, and the correction data Y '= Y-BK. / L, M '= M-BK / L,
C '= C-BK / L is generated. The correction data Y ′, M ′, C ′ are input to the selector 10.

In the selector 10, as described above, the three primary color data of Y, M, C from the timing adjusting unit 13 and BK
Data has been input, and based on the selection control signal from the line 9, either the data set of Y, M, C, BK or the data set of Y ', M', C ', BK' is set to the pixel. Output data Yout, Mout, C selected for each
out, BKout.

The selection control signal derived from the AND circuit 8 to the line 9 is the output signal EDGE when the edge detection circuit 4M detects an edge pixel or a pixel constituting the thin line portion.
Alternatively, the logic "1" is obtained only when THIN becomes the logic "1" and the output signal BLACK of the black pixel detection unit 7 becomes the logic "1" indicating that the target pixel is the black pixel candidate.
Becomes At this time, the selector 10 has Y ', M', C ', B
The data set of K'is selected and output. In this way, the selector 10 outputs Y ', M', C ', and BK' in which the BK data is emphasized only for the pixels constituting the edge portion of the black character and the pixels constituting the thin line portion of the black character. You will be selecting a dataset.

In this way, in the data Yout, Mout, Cout, BKout output from the selector 10, the BK data is emphasized only for the constituent pixels of the edge part of the black character and the pixels composing the thin line part of the black character. ing. Therefore, in the images of single colors of yellow, magenta, cyan, and black which are formed based on the signal from the selector 10, yellow, magenta, and cyan are added to the constituent pixels of the edge portion and the thin line portion of the black character. Has a lower density and black has a higher density. As a result, a binary image in which the edge portion and the thin line portion of the black character are almost black is formed. As a result, it is possible to form an image on the copy paper in which the boundary between the character portion and the background portion and the fine line portion are clearly reproduced. In this way, clear black characters can be reproduced.

Further, by the function of the selector 14 of FIG. 1, the correction coefficient L in the color adjusting unit 11 becomes the correction coefficient Lt for thin line pixels for the constituent pixels of the thin line portion, and for the edge pixels other than the thin line portion. Is a normal edge pixel correction coefficient Le. As a result, the BK data is strongly emphasized regardless of whether it is an edge pixel or not for the constituent pixels of the thin line portion, and the edge pixels other than the constituent pixels of the thin line portion are relatively gentle to the BK data. Is emphasized.

Therefore, for a black character composed of black pixels as shown in FIG. 14, for example, the correction coefficient Le for the normal edge pixels is set for the pixels in the area SE indicated by the diagonal line rising to the right. Applied. Further, the thin-line pixel correction coefficient Lt is applied to the pixels in the region ST indicated by the diagonal lines rising to the left. In this way, the thin line part B
Since the K data is emphasized sufficiently, the thin line portion is reproduced well. Further, for the relatively thick line portion, the BK data of the edge portion is gently emphasized, so that a large difference occurs between the pixel density of the edge portion and the pixel density of the area SI inside the character. Can be prevented. For this reason,
The problem that a clear border is formed at the edge portion does not occur. In addition, since the edge portion is gently emphasized in a wide black image, a clear border is formed even in a so-called black solid image in which black pixels do not exist over a relatively wide area. Can be prevented and a good reproduced image can be obtained.

FIG. 15 is a block diagram showing a part of the configuration of the second embodiment of the present invention. In the description of this embodiment, FIG. 1 and FIG. 6 described above will be referred to again. In the configuration shown in FIG. 15, the edge
It is used in place of the output circuit 210 and the selector 14 in the thin line determination processing unit 160. In FIG. 15, for comparison with the output circuit 210 shown in FIG. 9, portions corresponding to the respective portions shown in FIG. 9 are designated by the same reference numerals.

In the present embodiment, the correction coefficient L to be given to the color adjusting section 11 is selected from among three types of correction coefficient Lt for fine line pixels, correction coefficient Le for normal edge pixels and correction coefficient Lte for fine line edge pixels. It However, the correction coefficients Le and Lt are not necessarily equal to the correction coefficients Le and Lt used in the above-described first embodiment. The correction coefficient Lte for thin line edge pixels is applied to the pixels forming the edge portion of the thin line portion. Further, the correction coefficient Lt for thin line pixels is applied to the pixels other than the edge portion forming the thin line portion. Further, the correction coefficient L for the normal edge pixel
e is applied to pixels in the edge portion other than the thin line portion. There is the following magnitude relationship between these three types of correction coefficients Le, Lt, and LTE.

Le>Lt> Lte (24) Therefore, in the color adjusting unit 11, when the normal edge pixel correction coefficient Le is given, the BK data is subjected to a gentle emphasis process and a thin line. Pixel correction coefficient Lt
Is given to the BK data, and when the fine line edge pixel correction coefficient Lte is given, the BK data is strongly emphasized.

These three types of correction coefficients Le, Lt and L
te is given to the selector 14A used in place of the selector 14 of FIG. This selector 14A has
A 2-bit selection control signal is input in order to output one correction coefficient selected from the three types of correction coefficients L. That is, the output signal THIN of the OR circuit 212
And the output signal of the AND circuit 221 becomes a selection control signal.

The logical product circuit 221 includes a logical sum circuit 212.
Output signal THIN and the output signal E of the OR circuit 211
DGE is given. That is, the AND circuit 22
The output signal of 1 becomes a logic "1" for the edge pixel in the thin line portion. When the signal THIN from the logical sum circuit 212 has a logic "0", the pixel of interest is not a constituent pixel of the thin line portion. Therefore, the selector 14A selects and outputs the normal edge pixel correction coefficient Le.

Also, the output signal THI of the OR circuit 212
When N is a logic “1” and the output signal of the AND circuit 221 is a logic “0”, the pixel of interest is a pixel other than the edge portion although it is a constituent pixel of the thin line portion. For this reason,
The selector 14A selects and outputs the correction coefficient Lt for thin line pixels. Further, when the output signal of the logical product circuit 221 is logical “1”, the pixel of interest is the edge pixel of the thin line portion. At this time, the selector 14A selects and outputs the thin line edge pixel correction coefficient Lte.

In this way, the three types of correction coefficients Le,
As a result of Lt and Lte being selectively given to the color adjusting unit 11 according to the feature of the pixel of interest, the pixels of the edge portion other than the thin line portion are subjected to the gentle enhancement processing on the BK data, and the edge portion of the thin line portion is processed. Pixels other than the above have slightly strong emphasis B
This is applied to the K data, and the edge pixels in the thin line portion are strongly emphasized to the BK data.

As a result, for example, for a black character as shown in FIG. 16, a region SE1 (FIG.
6 is shown with a diagonal line rising to the right. ) Is gently emphasized based on the correction coefficient Le. Then, the pixels in the region ST1 (indicated by a diagonal line rising to the left in FIG. 16) other than the edge portion of the thin line portion are slightly emphasized corresponding to the correction coefficient Lt. Further, the pixels in the area STE (shown with double diagonal lines in FIG. 16) at the edge portion of the thin line portion are strongly emphasized based on the correction coefficient Lte. Since the selector 10 of FIG. 1 selects the image data from the timing adjustment unit 13, the emphasis processing is not performed on the area SI other than the edge portion of the thick line portion.

As described above, according to the present embodiment, different emphasis processing can be applied to edge pixels other than the thin line portion, pixels other than the edge portion of the thin line portion, and edge pixels of the thin line portion, whereby black color is obtained. Characters can be reproduced better. As described above, in the present embodiment, the AND circuit 2
21, AND circuit 8, color adjustment unit 11, selector 10
The third data correction means, the fourth data correction means, and the fifth data correction means are configured by including the selector 14A and the like.

Note that, for example, when the strong emphasis processing is performed only on the edge pixels of the thin line portion and the gentle emphasis processing is performed on the pixels other than the edge portion of the thin line portion and the edge pixels other than the thin line portion, the correction coefficient The logical product circuit 2 is used as a selection control signal of the selector 14A by using Le and Lte.
Only the output signal of 21 should be input. That is, the output signal of the logical product circuit 221 becomes the logic "1" only for the pixel at the edge portion of the thin line portion. Therefore, when the output signal of the logical product circuit 221 is the logic "1". Only the fine line edge pixel correction coefficient Lte may be selected, and the correction coefficient Le may be selected in the case of residual.

The embodiments of the present invention have been described above, but the present invention is not limited to the above embodiments. For example, in the above embodiment, the detection of the edge detection pixel and the detection of the thin line portion are commonly performed by the edge / thin line detection unit 4M, but the edge detection processing and the thin line portion detection processing may be performed separately. You may In this case, for example, the configuration shown in FIG. 17 can be applied to the edge detection processing.

The edge detection processing with the configuration of FIG. 17 is performed based on the density data after the smoothing processing of the pixels in the matrix array of 3 × 3 as shown in FIG. That is, the density data q0 after the smoothing process of the target pixel s0
And the respective density data q1 to q of the pixels s1 to s8 around it.
8 and the edge portion of the image is detected. More specifically, three lines of data DL0, DL1, D obtained by adjusting the timing of the smoothed data are adjusted.
L2 is a D-type flip-flop 163, 16 respectively.
5, 168. The data DL1 of the line including the target pixel s0 is the flip-flops 165, 160, 1
After being delayed by one clock at 64, the density data q4 of the pixel s4 is input to the subtractor 170. At this time, the output of the flip-flop 160 is the target pixel s0.
Corresponding to the density data q0, and the output of the flip-flop 165 corresponds to the density data q5 of the pixel s5. These density data q0 and q5 are also input to the subtractor 170.

Similarly, the data DL0 is sequentially delayed by one clock by the flip-flops 163, 162 and 161. Then, each flip-flop 163, 16
The outputs of 2 and 161 are given to the subtractor 170 as density data q3, q2 and q1 of the pixels s3, s2 and s1, respectively. Similarly, the data DL2 is delayed by one clock by the flip-flops 168, 167, 166 connected in series. Then, each flip-flop 16
The outputs of 8, 167 and 166 are given to the subtractor 170 as density data q8, q7 and q6 of the pixels s8, s7 and s6.

The subtractor 170 has values (q0-q1), (q0) obtained by subtracting the density data q1 to q8 of the target pixels s1 to s8 from the density data q0 of the target pixel s0.
-Q2), (q0-q3), (q0-q4), (q0-
q5), (q0-q6), (q0-q7), (q0-q
8) is calculated. This calculation result is the absolute value calculation unit 17
1 is input and positive values | q0-q1 |, | q0-q2
|, | Q0-q3 |, | q0-q4 |, | q0-q5
|, | Q0-q6 |, | q0-q7 |, | q0-q8 |
Is converted to.

The calculation result is input to the comparator 172 and compared with the threshold value t. Then, when any of the calculation results exceeds the threshold value t, a signal of logic "1" indicating that the target pixel s0 is a pixel at the edge portion is output. In summary, | q0-q1 | ≧ t ... (24) | q0-q2 | ≧ t ... (25) | q0-q3 | ≧ t ... (26) | q0-q4 | ≧ t ··· (27) ｜ q0-q5 ｜ ≧ t ··· (28) ｜ q0-q6 ｜ ≧ t ··· (29) ｜ q0-q7 ｜ ≧ t ··· (30 ) | Q0-q8 | ≧ t (31) is satisfied, the target pixel s0 is determined to be an edge pixel, and when neither is satisfied, the target pixel s0 is determined not to be an edge pixel. . By such a process, when a sharp change in density occurs in any direction around the pixel of interest s0, the pixel of interest s
0 will be detected as an edge pixel.

Further, the above embodiment can be modified as follows. That is, in the above embodiment, only the magenta density data is used for edge detection by utilizing the fact that the magenta component forming the color image approximates the human visual characteristics, but Y, M All data for C and C may be used. In this case, as shown in FIG. 19, Y data and C data are processed in the same manner as M data, and the edge / fine line detection units 4Y, 4M, and 4C are processed.
The output signal of is input to the AND circuit 5. Also, for the thin line detection signal THIN, the logical product of the thin line detection signals detected for the respective data of Y, C, and M is calculated by the AND circuit 230.
Take it. Then, the respective output signals of the logical product circuits 5 and 230 are inputted to the logical sum circuit 231, and the output signals EDGE and THIN of the logical sum circuit 231 are inputted to the selector 10 (see FIG. 1). . Further, the output signal THIN of the AND circuit 231 may be given to the selector 14.

As a result, when the densities of all the three primary colors are steep, it is determined that the pixel of interest is an edge pixel, and it is determined that all the three primary colors are pixels of the thin line portion. In addition, the thin-line pixel correction coefficient Lt is selected by the selector 14. In addition,
In FIG. 19, in each circuit that performs the same processing as the circuit for processing M data on Y data and C data, the symbols Y and C are attached to the same numerals as the reference numerals attached to the circuit for M data. And show it.

Further, in the configuration of FIG. 19, instead of the edge / fine line detecting units 4Y, 4M, 4C and the selector 14,
The configuration shown in FIG. 15 described above may be applied. In this case, the output signal of the AND circuit 230 and the signal obtained by ANDing the output signals of the AND circuits 221 (see FIG. 15) in the edge / thin line detection units of the respective colors are selected as selection control signals. Input to 14A.

Further, although the above embodiment has been described by taking the color copying machine as an example, the present invention is a color facsimile or other color image processing in which an optically read color image is stored or reproduced as data. The present invention can be easily applied to various image processing devices such as an image reading device that optically reads an image and converts it into a color signal.

In addition, various design changes can be made without changing the gist of the present invention.

[0108]

As described above, according to the image processing apparatus of the present invention, the pixels determined to constitute the edge portion of the image are
At the same time, when the pixel is a black pixel candidate, the pixel is determined to be a pixel forming an edge portion of a black character.
Further, when the pixels that are determined to be the pixels that form the thin line portion are pixels that are also black pixel candidates at the same time, the pixel is determined to be a pixel that forms the thin line portion of the black character.

Further, each of the constituent pixels of the edge portion and the thin line portion of the black character is corrected so as to emphasize black. This makes it possible to obtain image data that clearly expresses the boundary between the black character and the background portion. Moreover, in the thin line portion of the black character, black is emphasized more strongly than in the edge portion other than the thin line portion. Therefore, the thin line portion is sufficiently emphasized, and the edge portions other than the thin line portion are gently emphasized. As a result, it is possible to prevent a problem that the fine line portion is clearly reproduced, but a clear border is formed on the edge portion other than the fine line portion. In this way
High quality black characters are reproduced.

[Brief description of drawings]

FIG. 1 is a block diagram showing an electrical configuration of a main part of a color copying machine that is a first embodiment of an image processing apparatus of the present invention.

FIG. 2 is a block diagram showing a configuration of timing adjustment units 1Y and 3Y.

FIG. 3 is a diagram for explaining a smoothing process.

FIG. 4 is a block diagram showing a configuration of a smoothing unit 2M.

FIG. 5 is a diagram for explaining edge detection processing.

FIG. 6 is a block diagram showing a configuration of an edge / fine line detection unit 4M.

FIG. 7 is a block diagram showing a configuration of an edge / fine line determination processing circuit 160M corresponding to a main scanning direction.

FIG. 8 is a block diagram showing a configuration of an edge / fine line determination processing circuit 160S corresponding to a sub-scanning direction.

9 is a block diagram showing a configuration of an output circuit 210. FIG.

FIG. 10: Edge / fine line determination processing circuit 160M / 160
It is a figure for demonstrating operation | movement of S.

FIG. 11 is a block diagram showing a configuration of a timing adjusting unit 6Y.

FIG. 12 is a block diagram showing a configuration of a black pixel detection unit 7.

FIG. 13 is a block diagram showing a configuration of a color adjusting unit 11.

FIG. 14 is a diagram for explaining emphasis processing of an edge portion and a thin line portion for a black character.

FIG. 15 is a block diagram showing a partial configuration of a second embodiment of the present invention.

FIG. 16 is a diagram for explaining an emphasis process of an edge portion and a thin line portion for a black character in the second embodiment.

FIG. 17 is a block diagram showing a configuration example for detecting an edge portion.

FIG. 18 is a diagram for explaining edge detection processing in the configuration shown in FIG. 17.

FIG. 19 is a block diagram showing a configuration of a modified example of each of the above embodiments.

[Explanation of symbols]

 2M smoothing unit 4M edge detection unit 7 black pixel detection unit 8 AND circuit 10 selector 11 color adjustment unit 14 selector 161M rising edge detection unit 162M falling edge detection unit 163M thin line detection unit 164M edge detection processing unit 161S rising edge detection unit 162S Falling edge detection unit 163S Fine line detection unit 164S Edge detection processing unit 14A Selector 2Y, 2C Smoothing unit 4Y, 4C Edge detection unit

Claims (6)

[Claims] 1. A conversion means for optically reading a color image, converting it into three primary color data corresponding to respective densities of three primary colors, and creating black data corresponding to black density based on the three primary color data. , Based on the image data, when the pixel of interest is an achromatic pixel and the density is equal to or more than a predetermined value, a black pixel detecting unit that makes this pixel of interest a black pixel candidate; An edge detecting unit that detects a density gradient in the vicinity of the pixel of interest based on image data of a pixel adjacent to the pixel and determines that the pixel of interest is a pixel of an edge portion when the density gradient is equal to or more than a predetermined value. A thin line detecting means for determining whether or not the pixel of interest is a pixel forming a thin line portion which is an image portion having a width equal to or less than a predetermined width; and the pixel of interest is determined to be a pixel of an edge portion and is also a black pixel candidate. When it is determined that the pixel is a pixel forming an edge portion of a black character, the target pixel is determined to be a pixel forming a thin line portion, and is a black pixel candidate, The density of the three primary colors is reduced with respect to the second determination unit that determines the pixel as a pixel forming the thin line portion of the black character and the pixel determined as the pixel of the edge portion of the black character by the first determination unit. With respect to the first data correction unit that corrects the three primary color data and the black data so as to increase the black density, and the pixels that are determined to be the constituent pixels of the thin line portion of the black character by the second determination unit. Second data correction for making stronger correction than the correction by the first data correction means to the three primary color data and the black data so as to decrease the density of the three primary colors and increase the density of black. The image processing apparatus characterized by comprising a stage. 2. In place of the first data correction means and the second data correction means, the first determination means determines that the pixel is an edge portion of a black character, and the second determination means determines. 3 for the pixels that are not determined to be the constituent pixels of the thin line part of the black character
Third data correction means for correcting the three primary color data and the black data so as to decrease the density of the primary color and increase the density of black, and the pixel of the edge portion of the black character by the first determination means. For the pixels which are not judged and which are judged by the second judging means to be the constituent pixels of the thin line portion of the black character, the three primary color data and the three primary color data are set so as to decrease the density of the three primary colors and increase the density of black. Fourth data correction means for performing a stronger correction on the black data than the correction by the third data correction means, and the first determination means are determined to be pixels at the edge portion of the black character, and the second data correction means is used. Regarding the pixels which are determined by the determination means to be the constituent pixels of the thin line portion of the black character, the three primary color data are set so as to decrease the density of the three primary colors and increase the density of black. The image processing apparatus according to claim 1, characterized in that a fifth data correction means to the fine black data subjected to stronger correction than the correction of the fourth data correcting means. 3. The thin line detection means detects a rising edge pixel whose density increases sharply when a predetermined detection line passing through a pixel of interest is traced in one direction, and the rising edge detection means detects the rising edge pixel on the detection line. When the number of pixels between the falling edge pixels and the falling edge detecting means for detecting the falling edge pixels whose density sharply decreases when tracing in the direction, and the number of pixels between the rising edge pixels and the falling edge pixels is less than or equal to a predetermined threshold value. A means for determining the image portion between the pixel of the rising edge and the pixel of the falling edge as a thin line portion; and, when the pixel of interest is located in the thin line portion, the pixel of interest is configured as a thin line portion. The image processing apparatus according to claim 1, further comprising: a unit that determines a pixel. 4. The edge detecting means determines whether or not the pixel of interest is a pixel of an edge portion based on data of any one specific color of the three primary color data, The thin line detecting means is based on the data of the specific color,
The image processing apparatus according to claim 1, wherein the pixel of interest is for determining whether or not the pixel of interest is a constituent pixel of the thin line portion. 5. The edge detecting means further includes smoothing means for creating data in which a density gradient in the vicinity of the target pixel is smoothed based on image data of the target pixel and a pixel adjacent to the target pixel. Based on the image data that has been smoothed by the smoothing means, it is determined whether or not the pixel of interest is an edge pixel, and the thin line detecting means is smoothed by the smoothing means. 5. The image processing apparatus according to claim 1, wherein it is determined whether or not the pixel of interest is a constituent pixel of the thin line portion based on the image data after the processing. 6. The smoothing means smoothes a density gradient in the vicinity of the target pixel based on data of any one specific color of the three primary color data in pixels adjacent to the target pixel. It is to create, the edge detection means, based on the data of the specific color after being smoothed by the smoothing means, for determining whether the pixel of interest is a pixel of the edge portion, The thin line detection means determines whether or not the pixel of interest is a pixel of an edge portion based on the data of the specific color that has been smoothed by the smoothing means. 5. The image processing device according to item 5.