JPH03274862A - Black decision system and area identifier - Google Patents

Abstract

PURPOSE:To reduce influence due to the erroneous detection of the edge of a halftone part by performing black decision by using image data and data in which the edge of the image data is emphasized by an edge emphasis means. CONSTITUTION:The edge of the image data is emphasized by the edge emphasis means 101. A black decision means 102 performs the black decision by using both the image data 104 outputted from the edge emphasis means 101 and original image data 103. The range of a black character is decided from an edge signal outputted from an isolation area edge detecting means, an edge detection signal outputted from an edge detecting means, and a black decision signal outputted from the black decision means. Therefore, it is possible to recognize a character of any size.

Description

DETAILED DESCRIPTION OF THE INVENTION Field of Industrial Application The present invention relates to a black determination method for determining black areas in color image data and an area identification device for identifying black character areas. Color manuscripts handled by facsimile machines often contain a mixture of text and photographs.1. %
If you apply the same image processing to the text and photos in such a document, the text may become blurry or the photo may become difficult to see. On the other hand, if you improve the gradation in order to make the midtones clearer, the resolution of the characters will drop.To solve this problem, identify the upper ζ area. It is better to separate the character area and halftone area and perform processing appropriate for each (for example, in the character area, perform simple binarization processing at 1.%, and in the halftone area, perform dither processing.) Also, color misalignment occurs in the printer. Surubamori The black letter is C (
When reproduced with cyan), M (magenta), and Y (yellow), the edges of black letters appear colored, making them difficult to read. It is better to print in color~1 By identifying areas in this way, it is possible to reproduce images that include photographs and text in an easy-to-read manner. There is a method of identifying based on the difference between the maximum and minimum gradation values within a window, or a method of identifying a focus value that is gradation value data of a pixel of interest and surrounding pixels as shown in Japanese Patent Laid-Open No. 58-220563. There is a new method of determining the absolute value of the difference between the defocus values, which is the average value, and comparing it with a predetermined threshold. 1210, G (green)
There is a method that uses the image data of 1211 and B (blue) 1212 as they are (Figure 12 will be explained in detail later). It is difficult to distinguish between large characters, especially in bold characters because there is no large difference in density, and edges in mid-tone areas are easily detected incorrectly, making it very difficult to read depending on the manuscript. In addition, the edges of black letters may be blurred (due to the effects of scanning with a scanner), the edges may take on a tint due to the background color surrounding the black letters, and the density of black letters may change due to bright light phenomena. In view of the above problems, the present invention has a black detection method that solves the problem of black detection, and a method that can identify black characters of any size and detect halftone areas. In order to solve the above-mentioned problems, the black determination method of the present invention uses image data and edge enhancement means to identify an area. Using the data with the edges of the data emphasized, a black determination means performs black determination of the image.

In addition, the area identification device ζ of the present invention includes a signal synthesizing means for synthesizing a plurality of image data, a black judging means using the above-mentioned black judging method for judging black of an image, and a synthesized signal outputted from the signal synthesizing means. an edge detection means for detecting an edge; an edge detection signal output from the edge detection means;
Isolated area edge removing means removes edges of isolated areas from the black judgment signal output from the black judgment means, and detects black characters from the edge signals output from the isolated area edge removing means, the edge detection signal, and the black judgment signal. The black character range determination method of the present invention has the above-described configuration. First, the edge emphasis means emphasizes the edges of the image, and the black character determination means uses the original image data and the edges. Determining the black area of the image from both the emphasized image data By applying edge emphasis to the 41111m data, the density of the edge portion of the character increases, making it easier to determine it as black, and improving the ability to identify black characters. However, edge enhancement processing also tends to emphasize noise, especially whitish noise that exists in thick characters (hereinafter referred to as "white noise").
White spots may appear in bold characters. Therefore, the original image data also uses black judgment.In other words, in the case of thick characters, the edges are judged to be black by the edge-enhanced image data, and the inside is judged to be black by the original image data. The area identification device of the invention has the above configuration,
First, the signal synthesis means synthesizes multiple pieces of image data. For example, 4: A luminance signal is created from the U R, G, and B data to create a monochromatic color. The black judgment means uses the above black judgment method to determine the pixel of interest in the image data The edge detection means detects the edge portion of the composite signal synthesized by the signal synthesis means, but the isolated area edge removal means uses the edge detection signal output from the edge detection means and the edge detection signal output from the black determination means. For example, the edge information detected in the highlighted area of the noise a halftone dot is removed. Only the edges of black areas larger than a certain size are input to the next black character range determining means. The range of black characters is determined from the edge detection signal output from the edge detection signal and the black judgment signal output from the black determination means.The black character range determination means determines the range of black characters from the edge detection signal when the area between edges is black. Therefore, it is possible to identify characters of any size.Also, since black judgment is performed, edges in the midtone area are rarely mistakenly identified as characters, and even if they are incorrectly identified, they are Since the area is black and the contrast is strong, there are few problems1 Moreover, since the black determination method of the present invention is used, the detection ability for black characters is dramatically improved.The signal output from this black character range determining means is By applying processing suitable for each area using this signal, a high-quality image can be reproduced. For the sake of explanation, FIG. 1 shows a basic configuration diagram of a black determination method in an embodiment of the present invention. In FIG. 1, 101 is an edge emphasis means, which emphasizes the edges of image data. Then, black determination is performed using both the edge-enhanced image data 104 output from the edge-enhancing means 101 and the original image data 103.

C to apply edge enhancement to the original image data 103
There is a high possibility that the edges of the text will be blurred when read by the scanner, and as a result, the density will be low and the black of the edges may not be detected. The reason why image data 103 is also used is because if there is white noise inside a thick black character, applying edge enhancement will also emphasize that white noise, and there are parts of the black character that cannot be determined to be black if only the edge-enhanced image data is used. If you want to identify black letters with only thin lines without identifying uppercase letters, use only edge-enhanced image data (1 Figure 4 shows the edge-enhanced image data shown in Figure 1). In FIG. 4, which is a block diagram of an edge enhancement circuit which is an embodiment of the means,
401, 402 are line memories, 403.
404. 405. 406. 407 is latch, 408.409.411.412 is division method 4
10 is a multiplier 413 is an adder 414 is a subtracter 41
5 is a clip circuit, and FIG. 13 shows an edge emphasis operator employed in the embodiment of the edge emphasis circuit shown in FIG. 4. This operator is used to perform edge emphasis. The value of the pixel of interest is calculated by calculating the value of each element of this operator and the value of the image data. This calculation is performed by the divider 408.4 in FIG.
09.411°412 and multiplier 410. red
Edge enhancement operators other than those shown in Figure 13 may be used (
1 In FIG. 4, image data 420 is stored in line memory 4.
01 is delayed by one line. Furthermore, line memory 402 is delayed by one line. This allows three lines of image data 420, 421, and 422 to be processed simultaneously.
Each is for storing inno pixel data,
These latches make it possible to extract the pixel data corresponding to each element of the edge enhancement operator. The pixel data 424, 420, 422, and 431 of each element are divided by 4 by the dividers 408, 409, 411, and 412, respectively. In the multiplier 410, the target pixel data 427 is doubled.
The outputs 425, 426, 429.432 of the adder 413
The output 433 is added by the subtracter 414 and subtracted from the data 428 obtained by doubling the pixel of interest.
Confirm that the pixel data 434 after edge enhancement calculated above is less than the maximum value data 435 of the image data and greater than the minimum value data 436. If the maximum value (density data is 255) 2 if greater than
55, and if it is smaller than the minimum value (O in the density data), the edge emphasis signal 437 is generated. Before explaining Fig. 5, which is a block diagram of a black judgment circuit, a conventional black judgment circuit (block diagram of Fig. 12) will be described. In Fig. 12, 1201 is a maximum value minimum value detection circuit 1.
202 is a difference image 1203.1204°1205, 12
06 is a comparator, 1207 is a 3-man AND element, 120
8 is a maximum value minimum value detection circuit 12 which is a two-manufactured AND element.
01&Friend Noticed pixel data R1210, G1211.
Although the largest value and the smallest value of B1212 are detected (the maximum value/minimum value detection circuit 1201 will be explained in detail later in FIG. 6), the differentiator 1202 converts the maximum value data 1213 and the minimum value data 1214 into Comparator 1203 calculates the difference between and outputs difference value data 1215.
Then, the difference value data 1215 is compared with a predetermined threshold value 1216, and if the II value is less than 1216, an achromatic color signal 1217 is output. Threshold 12
18 and checks whether the R, G, and B data are higher than the minimum density (threshold value 1218)4. When R1210 is higher than the minimum density, the signal line 1219 is set to high level in the same way as G1211. When B1212 is higher than the minimum density, signal lines 1220 and 1221 are at high level. When all signal lines 1219, 1220 and 1221 are at high level, AND element 1207 outputs a high level signal to signal line 1222. Achromatic color AND when both the signal 1217 and the lowest concentration signal 1222 are at high level
The element 1208 outputs a high level signal to the signal line 1223, and this signal becomes the black judgment signal 1223 (even if the pixel of interest is black when the level is high). Black judgment may not be possible due to blurred edges.Next, we will explain the black judgment circuit shown in Fig. 5.As you can see by comparing Fig. 5 and Fig. 12, the basic part of black judgment is Although they are the same, they are different in that the black determination circuit shown in FIG. 5 uses edge-enhanced image data as well as the original image data. In FIG. 505 is a differentiator 503゜506, 50
7.508.509.510.511.512 is comparison @
513.514.515° 517 is an OR element, 51
6 is a three-man power AND element, and 518 is a two-man power AND element.The maximum value minimum value detection circuit 501 is R520, G521.
．． Similarly, the maximum and minimum value detection circuit 504 calculates the maximum density and minimum density of the original image data of B522.
'529. The maximum and minimum concentrations of B' 530 are determined.The subtractors 502 and 505 determine the difference between their maximum and minimum values.Comparators 503 and 5
In 06, each difference value is a predetermined threshold value 526, 534
If the thresholds 526 and 534 are below, the comparators 503 and 506 send achromatic signals 527 and 534, respectively.
535 (signal lines 527 and 535 are set to high level), OR element 517 outputs at least one of the achromatic color signal 527 of the original image data or the achromatic color signal 535 of the edge-enhanced image data at a high level. A high level signal is output to the signal line 536 when R520 of the original image data is output to the comparator 5.
F
When the concentration of L and R520 is equal to or higher than the threshold value 537, the comparator 5
07 outputs a high level signal to the signal line 538.Similarly, when the R' signal 528 of the edge-enhanced image data is equal to or higher than a predetermined threshold value 537, the comparator 510 outputs a high level signal to the signal line 539&OR Element 513 sets signal line 544 to high level when at least one of input signals 538, 539 is at high level, LG521. G52
The same goes for 9, and if at least one of them is higher than the predetermined threshold value 537, the signal line 545 becomes high level &B522. The same goes for B' 530, and if at least one of them is equal to or higher than the predetermined threshold value 537, the signal line 546 goes to high level.
6 outputs a high level signal to the signal line 547 when all of the input signal lines 544, 545, and 546 are at high level.In other words, the AND element 516 outputs a high level signal to the signal line 547 when the image data is higher than the minimum density (threshold value 537). to a high level,
The L AND element 518 outputs the black determination signal 54 when the signal line 547 is at a high level and the signal line 536 is at a high level.
(If the black determination signal 548 is at a high level, the pixel of interest is black.) FIG. In Fig. 6, which is a block diagram showing an embodiment of 504.1201, 601.603.605.606 are selectors, 602.604.607 are comparators, image data R608 (or R'), The density values of G609 (or G') are compared by the comparator 602, and the results are output to signal lines 611 and 612.
and G609, the larger MAX (R, G) is connected to signal line 6
13. On the other hand, the selector 603 outputs the signal line 612.
Based on the result, the smaller of R608 and G609 M
Comparator 604 outputs IN(R,G) to signal line 614
MAX (R,
G) Compare 613 and B610 (or B") and transmit the result to the selector 605 using the signal line 615. The selector 605 receives this signal 615 and selects the MA
X (R, G) The larger of 613 and B610 M
AX(R,G.

B) is output to the signal line 617. Conversely, the comparator 607 compares MIN (R, G) 614 and B610 and the result is transmitted to the selector 606 using the signal line 616. The selector 606 receives this signal 616. Accept, MIN
(R, G) The smaller of 614 and B610 MIN (
R, G, B) are output to the signal line 618. In this way, the maximum and minimum values of the image data are determined.As shown above, the original image data and the edge-enhanced image data are used for black determination. This makes it possible to perform black determination that is effective for area identification, and is particularly effective for determining black on edges and inside bold characters. Next, an area identification device according to an embodiment of the present invention will be described with reference to the drawings. FIG. 2 shows a basic configuration diagram of the area identification device in the embodiment of the present invention. In FIG.
A synthesized signal 211 (for example, a luminance signal) is generated from 10. 202 is an edge detection means Δ for detecting the edges of the synthesized signal 211. 203 is a black determination means, which detects the image data 21.
Although it is determined whether or not the pixel of interest of 0 is black, effective black determination can be made using the black determination method shown in FIG. As shown in the figure t-2
04 is an isolated area edge removal means type edge detection means 20
The edge detection signal 212 output from 2 and the black judgment signal 213 output from the black judgment means 203 are used to remove edge information detected due to the influence of board noise etc. 213, an edge detection signal 212, and an edge signal 214 output from the isolated area edge removal means 204. The figure is a block diagram showing an embodiment of an image processing device using the area identification device shown in FIG. 2. In FIG. The shading correction (correction of unevenness) etc. for the input image data are also performed here. 302 is the area identification device of the present invention as shown in FIG. 2. The signal 307 output from the area identification device 302 is Area identification signal (signal 215 in Figure 2)
The signal 308 is a composite signal (signal 211 in FIG.
) 303 is an image processing circuit that performs processing such as dark gamma correction and masking.This image processing device 30
In step 3, processing assuming a halftone image is performed. A selection circuit 304 selects either the composite signal 308 or the signal 309 output from the image processing device 303 depending on the value of the area identification signal 307.The composite signal 308 is selected when the pixel of interest is in a black text area. At this time, the composite signal 308 is used as K (black) data, hc (cyan), 2M (magenta), and Y (yellow) values are set to '0' (K signal is set to maximum density '255). ``Even if it's a chicken〉The signal 309 is selected when the pixel of interest is in the halftone area, and the signal 309 is selected when the pixel of interest is in the halftone area.
Even if K is output from the selection circuit 304 as it is, 305
are output devices, and C and M output from the selection circuit 304
.

If a printer device uses the Y and K signals 310 to reproduce and output an image, it is possible to reproduce the halftone area and character area with good quality by performing the image processing described above. In FIG. 7, which is a block diagram of a signal synthesis circuit that is an embodiment of the signal synthesis means 201 in FIG. 2, 701, 702, and 703 are dividers, and 704 is an adder. ,G706°B2O2
are respectively input to dividers 701, 702, and 703. In this example, the composite signal is L = (R + 2G + B) /
Therefore, the divider 701 divides the image data of R705 by 4 (just shift the image data by 2 bits), and the divider 702 divides G706 by 2 (shifts the image data by 1 bit). In the divider 703, B2
Divide O2 by 4 The data obtained in this way is 708.70
By adding 9.710 in the adder 704, a composite signal 711 can be generated. In Figure 8,
801, 802 are line memories, 803.
804. 805. 806. 807 is a latch, 808.809.810.811.812 is a divider, 813 is an adder, 814 is a subtracter, 815 is an addition/subtraction method, and 816 is a comparator, which is the basic edge detection operator adopted in the embodiment of Anko's edge detection circuit. The force t is shown in Figure 14 (a). In this circuit, each element is further reduced to 1/2. This is to express the edge detected data in unsigned 8 bits, and the edge data is divided from ``O'' to ``2'' centering on the intermediate value ``128''.
55' (Actually, it has positive and negative values, so it cannot be expressed without a sign.) First, the composite signal 820 (Figure 8) output from the signal synthesis circuit 201 shown in Figure 2 is stored in the line memory. The signal 821 is stored in the line memory 801 and output from the line memory 801.
are stored in the line memory 802. With this configuration, it is possible to process pixel data for three lines at the same time.
．． 806 and 807 are for delaying the pixel data of each line.The pixel of interest to be calculated as the center of the edge detection operator is the signal 827 output from the latch 805.The four corners of the edge detection operator and the multiplication ( The signals for division) are connected to signal lines 820, 824, 822 .
The divider 808.809.831 in FIG.
810.811.812 (Friend) This is for multiplying the coefficient of the edge detection operator in Figure 14(b) by the density value of the pixel corresponding to that part without a sign (actually, it is division). If so, dividers 808, 809
, 811.812 divides the density value of the pixel by 8, and the divider 810 divides it by 2.Actually, ζ.To divide by 8, you only need to shift 3 bits, and to divide by 2, you only need to shift 1 bit, so the circuit The configuration is simple (just shift the upper bit part of the signal line to the lower part and use it). The signal 825 output from the divider 808, the signal 826 output from the divider 809, and the A signal 829 output from the divider 811 and a signal 83 output from the divider 812
2 is added in the adder 813 and the result is in the subtracter 814.
The subtracter 814 converts the value 828 output from the divider 810 to the value 83 output from the adder 813.
The calculation by the edge detection operator in Fig. 14 (b) is completed a Next addition/subtraction unit 8
15, the signal 834 output from the subtractor 814
In other words, adding '12B' to the value of signal 11834 (since there are negative values in signal 834 output from subtractor 814, Not only addition but also subtraction is performed. 〉If the signal 836 output from the adder/subtractor 815 is an edge signal, the comparator 816 compares this edge signal 836 with a predetermined threshold 837. If the edge signal 836 is higher than the threshold 837, then If it is larger, the comparator 816 outputs the edge detection signal 8
FIG. 9 shows the isolated area edge removing means 204 shown in FIG.
In FIG. 9, which is a block diagram of an isolated area edge removal circuit that is an embodiment of the present invention, 901.902.903 are line memories (only line memories for Ll bit data), 9
04.905.906.907.9'88.909,9
10, 911, 912, and 913 are latches, 914 is a 6-person OR element, and 915 is a 2-person AND element. In the matrix shown in Figure 15, the center is the pixel of interest, and each square represents the positional relationship from the pixel of interest.Isolated areas such as noise are isolated with different density values from the surrounding areas. There are many areas where it cannot be determined that the pixel of interest is isolated.The surrounding pixels to be examined are the pixels shown with diagonal lines in Figure 15. All judgment values are ′
0' (that is, not black), it is determined that the edge of the pixel of interest is isolated.
The power to investigate the shaded area in Figure 5 You can also investigate other areas L ~ The further away the nearest shaded area is from the pixel of interest, the easier it is to remove edges, making it easier to see the isolated area larger. Line memories 902 and 903 in the figure are for delaying the black judgment signal 921 by one line or two lines, and with this configuration, it is possible to handle three lines of black judgment signals at the same time. The latch 904.9 is for timing the pixel 928 of the black determination signal and the pixel of interest 928.
05.906, 907.908.909.910.91
1°912.913 is for delaying pixel data, but the signal line 92 corresponds to the surrounding pixels of the pixel of interest.
4.926.922.930.931゜933 demo
When at least one of these signal lines is ° 1' (indicating black), the 6-power OR element makes signal line 935 high, and all are '0' (indicating not black).
When the signal line 935 is at a low level, the edge detection signal 934 is removed by the AND element 915. In other words, the AND element 915 outputs a high level signal to the signal line 936. 1
When the signal line 935 is black, the signal line 935 becomes high level, so the edge detection signal 934 is transmitted as is to the signal line 936. With the above configuration, the edge detection signal in the isolated area is removed. In FIG. 10, which is a block diagram of a black character range determining circuit which is an embodiment of the black character range determining means 205 in FIG. 10, 1001 is a latch, 1002 is an OR element, 1003.
4 is a flip florus, 1005 is a NOT element, 10
06 is a line memory, 1008 is a halftone part removal circuit (
However, the edge signal 1009 (FIG. 10) output from the isolated area edge removal means 204 in FIG. 2 is input to the latch 1001.
1 is for storing the edge signal 1009 for one pixel. It serves to prevent timing deviation between the edge signal and the black judgment signal 1012. In other words, (L latch 1001 stores the signal for one pixel before) Therefore, if the area where the edge is detected is determined to be not black because the density is low, and the L next pixel is determined to be black, then the edge of a black character can be detected.OR
The element 1002 has the pixel of interest 1009 and the signal 10 of the previous pixel.
10, the AND element 1003 functions to increase the edge detection ability of black characters by ORing with the output 1011 of the OR element 1002 and the black judgment signal 101.
In other words, the element for detecting the black edge is the flip-flop 10044.
It is set when element 1003 outputs a high level signal, and outputs a high level signal to signal line 1015. This flip-flop is reset by black determination signal 10.
12 becomes low level, at this time the NOT element 1005 outputs a high level signal to the signal line 1014. This is input to the flip-flop and reset is started. The detection signal 1016 is input to the line memory 1006, and the output 1017 of the line memory 1006 is delayed by -line to determine the timing of the pixel of interest.
The output 1014 of the NOT element 1005 is the AND element 10.
07 is ANDed, and the result is output to the signal line 1018.In other words, 4f, the output of the AND element 1007 becomes high level when a non-black edge exists.The output signal 1015 of the flip-flop 1004 and
The output signal 1018 of the AND element 1007 is input to the halftone part removal circuit 1008, where the halftone part is removed and the black character area identification signal 1019 is obtained. 1008
110 is a block diagram of an embodiment of the present invention.
1.110? , 1112.1115 is a switch 11
02 is the switching signal generating stock 1103, 1104, 1105
, 1106°1113.1114 is L I F O (l
ast in fast.

ut) line memory (1-bit data line memory), 1108 is a flip-flop, 1109 is OR
1110 is an AND element, 1111 is a NOT element. Signal 1116 (1015 in FIG. 10) output from the flip-flop 1004 in FIG. 10, and AN
The signal 1117 (1018 in FIG. 10) output from the D element 1007 may be input to the switch 1101.
Figure 16 shows the signal lines 1116 and 1117. In Figure 16, figure (a) shows the signal line 1116 (first
16(a), the black text area is 1.
The range shown in 601 and the range shown in 41602 are halftone regions. (To be exact, the range 1602 is a halftone region that was incorrectly identified as a black text region.) The difference between the black text region and the halftone region is the signal line 1117. (Equivalent to signal line 1018 in FIG. 10) The signal on signal line 1117 is shown in FIG. 16(b). As you can see from Figure 16(b), in the case of a black text area, there is an edge at the end of the area, but the edge signal is 16 as shown in Figure 16(b).
In other words, even if it is a signal of 03, the halftone area (16
02 range), there is no edge signal at 1604 in Figure (b).The signal that is ultimately desired to be output from the halftone removal circuit 1008 is the signal shown in Figure 16(d). This signal is equal to the signal obtained by removing the range 1602, which is the range of the halftone region in (a).This signal is the area identification signal for the black text area. In Figure 11, signals 1116 and 1117 are stored in LIFO line memories 1103 and 1104, respectively. At the same time, output begins to signal lines 1125 and 1126 (signal lines 1129 and 1130 through switch 1107).
Even if data is stored in line memories 1105 and 1106, these two line memories store one line of data.Similarly, signals are output to signal lines 1127 and 1128 (through switch 1107 to 1129 and 1130) to start. Signal 1116.1117 to line memory 1103.1104
Even if this is repeated, the switching is performed by the switching devices 1101 and 1107, and the switching timing is output from the switching signal generator 1102.The switching signal is the number of pixels for one line, 1122, and the pixel clock 1123. It can be easily generated from line memory 1103, 1104.
, 1105 and 1106 are LIF○, so the data flows in the opposite direction.If we explain this using Figure 16, the signal that was flowing from left to right will now flow from right to left.As a result, as shown in Figure ( Halftone area 16 using the signal of b)
02 can be removed, but the signal line 1129 has the first
The data of Figure 6 (a) flowing from the right is not transmitted.The signal line 1130 receives the data of Figure 16 (b) flowing from the right. Edge data 1 of 41607, which describes the state of signal transmission at timing 1607 in FIG. 16(C).
130 is input to the flip-flop 1108, the flip-flop 1108 sends a high level signal to the signal line 11.
At this timing, as shown in FIG. 16(a), the signal line 1129 is at a low level, so the AND element 1110 outputs a low level signal to the signal line 113.
Therefore, the signal obtained as shown in FIG. 16(d) becomes low level & when the output of AND element 1110 is low level, the output of NOT element 1111 (
Since the signal line 1133) is at a high level, the OR element 1109 outputs a high level signal to the signal line 1134.
When this signal resets the flip-flop, the next case is the range 1602 in Figure 16(a).At this time, the range 1609 of the edge signal is low level.
Since the flip-flop 1131 is not set (by the edge signal 1130), even if it outputs a low level, the AND element 111O outputs a low level. In this case, the flip-flop 1108 is set by the edge signal 1608 in FIG. 16(C) (signal line 1130 in FIG. 11 becomes high level), and the high level signal is sent to the signal line Even if the signal line 1129 outputs a high level signal within the range 1601 in FIG. Level signal signal line 1133
The switching signal 1124 is output to the switching signal generator 110.
Unless the signal is output from 2, the OR element 1109 outputs a low level signal, so the flip-flop remains set.
The ND element 1110 outputs a high-level signal to the signal line 1132.Although a signal flowing from the right in FIG. 16(d) is obtained, this signal 1132 passes through the switch 1112 to
This signal is stored in the line memory 1113 of IF○, but if the line memory 1113 stores one line, this signal is output in the opposite direction through the switch 1115. At the same time, the next line's signal is stored in the line memory 1114. When the line memory 1114 stores the signal 1132 for one line, the data is output in the opposite direction to the signal line 1139 through the switch. At this time, the line memory 1113 stores the signal 1132. . The signal outputted from the signal line 1139 is the signal flowing from the left in FIG. 16(d), and is the area identification signal in black letters. The black determination method ζ of the present invention The black determination method ζ configured as described above produces the effects described below. Since the black area of the image is determined from both edge-enhanced image data, the density of the edge part of the character increases, making it easier to judge it as black, improving the ability to identify black characters. Since the original image data is also used for black judgment, there is less influence from white noise.By using this black judgment method, black judgment suitable for black characters can be achieved. Since the area identification device of the present invention is configured as described above, it can achieve the effects described below. If it is black, that section is identified as a black text area.
Therefore, even if characters of any size are distinguishable,
In addition, because black detection is performed, edges in half-tone areas are rarely mistakenly identified as characters, and even if they are misidentified, there is little problem because the edges are black and the contrast is strong.1. s L or L Since the black determination method of the present invention is used, the ability to detect black characters is dramatically improved.Also, since the edges of isolated areas are removed, it is less susceptible to the effects of noise. The area identification signal output from the area identification device can be used to perform processing appropriate for each area, making it possible to reproduce high-quality images.

[Brief explanation of drawings]

FIG. 1 shows the basic configuration of the black determination system in the embodiment of the present invention. FIG. 2 shows the basic configuration of the area identification device in the embodiment of the invention. The blocks showing one embodiment of the image processing device are as follows: FIG. 4 is a block diagram of an edge emphasis circuit which is an embodiment of the edge emphasis means shown in FIG. A block of the black determination circuit which is an embodiment @ Fig. 6 is a block showing an embodiment of the maximum value/minimum value detection circuit shown in Figs. 5 and 12. Fig. 7 is a block showing the signal synthesis means in Fig. 2. FIG. 8 shows a block of the signal synthesis circuit which is an embodiment of the signal synthesis circuit. FIG. 9 shows a block of the edge detection circuit which is an embodiment of the edge detection means shown in FIG. 2. FIG. 9 shows the isolated area edge removal means shown in FIG. The blocks of the isolated area edge removal circuit which is one embodiment are as follows: Figure 10 is a block of the black character range determining circuit which is an embodiment of the black character range determining means in Figure 2; FIG. 12 shows a block diagram of an embodiment of the edge removal circuit. 15 is an explanation for explaining the algorithm of the isolated area edge removal circuit shown in FIG. The timing chart diagram showing the situation is 101...
・Edge emphasis hand 102...Black judgment hand north 2
01...Signal synthesis means 202...Edge detection method 203...Black judgment method in the area identification device 204...Isolated area edge removal ratio 205 ...Black character range determination circuit 301.
...Input wave [302... Area identification bag [3
-03... Image processing device L 304...
・・Select same area 305・・・・・・Output bag [401,4
02,801,802,901゜902,903100
6...Line memory, 403, 404, 40
5.406.407.803゜804, 805.806
．． 807.904.905, 906.907.908.
909.910°911, 912.913.1011・
...Latch, 408, 409. 411. 4
12. 701. 702, 703808. 809
．． 810. 811. 812...4 for division
10... Multiplication! 413,704.813...
...Addition @ 414.814...Subtraction method
415... Clip times li & 501.50
4゜1201... Maximum value minimum value detection times [502
, 505, 1202 - Difference @ 503.5
06.507, 508.509.510.511.51
2゜602, 604.607.816.1203.12
04, 1205.1206... Comparator 513
゜514, 515.517.914.1002.110
9...OR element, 516, 518, 915°1
003, 1007.1110.120? , 1208
...AND element, 601, 603, 605°6
06...Select Kyu 815...Addition/subtraction method 1004.1108...Flip-flop, 1005.1111...NOT element, 1
008... Halftone part removal port! 1101.1
107.1112゜1115...Switching method 11
02...Switching signal generation 1103. 11
04. 1105. 1106°1113.1114・
...FIF○ line memory, 1601, 160
6... Black text area 1602... Halftone headboard incorrectly identified as black text area 1603, 1605
．． 1608.1607... Edge signal that is not black.

Claims (2)

[Claims] (1) A black determination method characterized in that the blackness of an image is determined using image data and data in which the edges of the image data are emphasized. (2) a signal synthesizing means for synthesizing a plurality of image data, a black judging means for judging the blackness of an image, an edge detecting means for detecting an edge of a composite signal output from the signal synthesizing means, and the edge detecting means an isolated area edge removing means for removing an edge of an isolated area from an edge detection signal output from the black determining means and a black determining signal output from the black determining means; and an edge signal output from the isolated area edge removing means; An area identification device comprising: black character range determining means for determining a black character range from the edge detection signal and the black determination signal.