Image processing apparatus for binarizing halftone image data by using an adaptive threshold

Abstract: A binary image processing apparatus (101) compris­ ing: a first level discriminating device (109) which has a first input terminal for receiving an image signal (S) and a second input terminal for receiving a signal indicative of a discrimination level (Sh) so as to discriminate level of the image signal into binary data; a differential device (n2) for obtaining a differential value (f′(x)) of the image signal (S); a second level discriminating device (n3) for discriminating level of the differential value (f′(x)) by a predetermined discrimination level (L-, L+); a calculating device (n2) for calculating, in response to image signals in the vicinity of the pixel, an average value (AVE(x)) of density levels in the vicinity of the pixel; and a discrimination level changing device (n4, n5) which supplies the average value (AVE(x)) to the second input terminal of the first level discriminating device (109) and retains the discrimination level (S1) inputted to the second input terminal of the first level discriminating device (109) when the differential value (f′(x)) exceeds and is not more than the predetermined discrimination level (L-, L+), respectively.

Description: BACKGROUND OF THE INVENTION The present invention relates to a binary image processing apparatus which is suitable for use in an image reader employed in a facsimile machine or the like so as to display with black and white pixels, image data read by the image reader. Conventionally, a facsimile machine or the like is provided with a binary image processing apparatus for outputting an image of an original document per predetermined pixel unit as binary signals representative of black and white pixels in accordance with the density of the pixel unit. In a known binary image processing apparatus, the image face of the original document is scanned by a reading sensor formed by, for example, a charge coupled device (CCD) and an image signal having a level corresponding to density of the image of the original document per predetermined pixel unit is generated from the image of the original document. Then, binary image processing is performed such that the level of the image signal is discriminated into binary data corresponding to black and white pixels, on the basis of a discrimination level set in accordance with density of the image of the original document. In typical known binary image processing, an average density slice method is employed as shown in Fig. 1. In this method, an average density AVE of pixels of a relatively wide area of, for example, 3 scanning lines x 16 pixels is calculated by disposing a specific target pixel at the center of the area. when the level of an image signal S of the target pixel is lower than the average density AVE by a predetermined value AVA or more, it is judged that the pixel is a black pixel. Otherwise, it is judged that the pixel is a white pixel. Namely, the image signal S obtained from the CCD or the like is based on quantity of light reflected from the face of the original document. Thus, as level of the image signal S becomes lower, the corresponding pixel is darker. On the contrary, as the level of the image signal S becomes higher, the corresponding pixel is lighter. As shown in Fig. 1, in the average density slice method, a boundary line ℓ1 is provided for discriminating an area of the black pixels and an area of the white pixels from each other. When the level of the image signal S is smaller than a minimum Smin, it is forcibly decided by the boundary line 11 that the pixels are black pixels regardless of the average density AVE. On the other hand, when the level of the image signal S is larger than a maximum Smax, it is forcibly decided by the boundary line ℓ1 that the pixels are white pixels. Furthermore, when the level of the image signal S is disposed between the maximum Smax and the minimum Smin and is smaller than the average density AVE, it is decided that the pixels are black pixels forming a portion of characters. In Fig. 1, the boundary line ℓ1 is set lower by the predetermined value AVA than a line ℓ2 which is proportional to the average density AVE and passes through an origin O. This is because in the case where an image of characters or signs recorded in black on, e.g., a grey background of the face of the original document is read, gradation of the binary data obtained by binary encoding is shifted to the white side such that noises are eliminated. In the above described average density slice method, in order to obtain the average density AVE having the target pixel as the center of the area, average operation of a relatively wide area of, for example, scanning of three lines x 16 pixels is required to be performed. Thus, a line buffer memory for temporarily storing the image signal needs a large capacity, thereby resulting in rise of its production cost. In Fig. 2(a), a solid line ℓ3 represents changes of the image signal S on the scanning line and a broken line 14 represents changes of the average density AVE. Meanwhile, a one-dot chain line ℓ5 represents changes of a threshold level Sh obtained by subtracting the predetermined value AVA from the average density AVE, i.e. Sh = AVE - AVA. Fig. 2(b) shows results of binary encoding of the prior art average density slice method. Meanwhile, Fig. 2(c) shows results of desirable binary encoding. As will be seen from Figs. 2(a) to 2(c), when an image of a thin line is subjected to binary encoding, the following problems will arise. Namely, in the case where the width of a line is smaller than the width of a single unitary reading pixel, or where density changes partially along the line with respect to the average density AVE calculated from the image signal S oriented in the direction along the line, the obtained level of the image signal S does not become sufficiently small. Meanwhile, when changes of level of the image signal S are greater than changes of the average density AVE, the thin continuous solid line is displayed as a broken line formed by a plurality of thin lines in the binary image obtained by binary encoding, so that a portion of the line is erased undesirably. Furthermore, Fig. 3 shows a prior art binary image processing apparatus. The image signal S is sequentially outputted for each pixel from the CCD or the like and is subjected to analog-digital conversion. Then, the image signal S is supplied to a line buffer 1 and the image signal S stored in the line buffer 1 is fed to another line buffer 2. The line buffers 1 and 2 have storage capacities corresponding to scanning lines of the image face of the original document, respectively. Based on the image signals stored in the line buffers 1 and 2 and the image signal S, binary data D is outputted for each pixel from a binary circuit 3. The binary data D is stored in a line buffer 4. Based on the binary data D and the binary data stored in the line buffer 4, a binary data correcting circuit 5 yields a binary output. Conventionally, when an image of intermediate gradation is subjected to binary encoding, error diffusion method is employed in which after an error E obtained from binary data of vertically and laterally neighboring pixels of a specific target pixel, for example, 4 peripheral pixels of the target pixel have been added to the image signal S of the target pixel, binary encoding is performed. Fig. 4 shows a known circuit for implementing error diffusion method. The image signal for each pixel is supplied to an adder 6. The adder 6 also receives an error signal E to be described below. An additive signal Se obtained by adding the error signal E to the image signal S is fed to a comparator 7. On the basis of a threshold value Sh from a threshold setting circuit 8, the comparator 7 discriminates the level of the additive signal Se so as to output the binary data D of the image signal S. Thereafter, the binary data D is supplied to an error calculator 9. The error calculator 9 also receives the image signal S so as to calculate an error e of the pixel corresponding to the image signal S. Namely, when the binary data from the comparator 7 is 1, the error calculator 9 sets the error e to S. On the other hand, when the binary data from the comparator 7 is 0, the error calculator 9 sets the error e to (S - R) where character R denotes a constant. The error e from the error calculator 9 not only is supplied, as an error eD, to a line buffer 11 through a delay of one pixel by a delay circuit 10 but is applied to a multiplier 12. The line buffer 11 has a storage capacity which is smaller than the number of pixels of one scanning line by two pixels. Assuming that each pixel has an error e as shown in Fig. 15(c), the error eD is supplied from the delay circuit 10 to the line buffer 11 and an error eA is outputted from the line buffer 11. The output eA from the line buffer 11 is changed to an error eB by a delay circuit 13 and the error eB is, in turn, changed to an error eC by a delay circuit 14. The errors eB and eC are applied to the multiplier 12. The multiplier 12 supplies to an adder 15 the values obtained by multiplying weighting factor k1, k2, k3 and k4 with the errors eA, eB, eC and eD, respectively. The adder 15 outputs, as an error signal E, the sum of these values. Namely, the error signal E is given by the following equation. E = k1·eA + k2·eB + k3·eC + k4·eD The circuit of Fig. 4 for implementing error diffusion method is usually obtained by adding the components to the circuit of Fig. 3. Therefore, in such known binary image processing apparatus, the line buffer 11 for storing the error e shown in Fig. 4 is required to be provided in addition to the line buffers 1 and 2 for temporarily storing the inputted image signal S and the line buffer 4 for storing the binary data D. SUMMARY OF THE INVENTION Accordingly, an essential object of the present invention is to provide a binary image processing apparatus which is capable of clearly and stably performing binary encoding of an image signal having levels corresponding to the density of each inputted pixel even when difference in density between characters and background is small. The above object is, according to the invention, solved by a binary image processing apparatus comprising: a first level discriminating means which has a first input terminal for receiving an image signal having a level corresponding to the density of a target pixel of the image signal and a second input terminal for receiving a signal indicative of a discrimination level so as to discriminate level of the image signal by the discrimination level into binary data; a differential means for obtaining a differential value of the density of the image signal at the target pixel; a second level discriminating means for discriminating the level of the differential value by two, respectively predetermined positive and negative discrimination levels; a calculating means for calculating in response to image signal in the vicinity of the target pixel an average value of density levels in vicinity of the target pixel; and a discrimination level changing means which supplies said average value to the second input terminal of said first level discriminating means only if the associated differential value at the target pixel is discriminated to exceed the range defined by the positive and negative discrimination levels and otherwise retains for the actual target pixel the discrimination level of the previous target pixel (claim 1). Depending claims 2 and 3 are respectively specifying advantageous developments thereof. In accordance with the present invention, the image signal has for each pixel a level of density inputted to the first input terminal of the first level discriminating means such that the first level discriminating means discriminates, by using the signal inputted to the second input terminal and indicative of the discrimination level, the image signal into the binary data. The differential value of the inputted image signal is obtained by the differential means and is subjected to level discrimination in the second level discriminating means by using the predetermined discrimination levels. Meanwhile, the image signals in the vicinity of the pixel to be subjected to binary encoding by the first level discriminating means are supplied to the average value calculating means in which the average value of the density levels in the vicinity of the target pixel is obtained. This average value is supplied by the discrimination level changing means. Namely, when the differential value outputted from the second level discriminating means exceeds the predetermined discrimination level, the average value is supplied to the second input terminal of the first level discriminating means by the discrimination level changing means so as to be set as the discrimination level. On the other hand, when the differential value is not more than the predetermined discrimination level, the discrimination level which has been supplied from the average value calculating means to the discrimination level changing means up to an immediately prior time point is retained so as to be supplied, as the discrimination level, to the second input terminal of the first level discriminating means. As described above, the discrimination level which is supplied to the second input terminal of the first level discriminating means is changed to the average value of the density levels in the vicinity of the pixel only when the differential value of the image signal at the pixel exceeds the predetermined discrimination level. Therefore, only in the area in which density changes greatly as in the case of peripheral portions of characters and signs, the discrimination level of the first level discriminating means for performing binary encoding is changed. In this case, after the peripheral portions of the characters, etc. have been detected, the discrimination level of the first level discriminating means does not readily change. Accordingly, even when an image of an original document is a thin character in white background, a black character in gray background or a white character in black background, a boundary between the character and its background is clearly displayed through stable binary encoding of the character. BRIEF DESCRIPTION OF THE DRAWINGS These objects and features of the present invention will become apparent from the following description taken in conjunction with the preferred embodiments thereof with reference to the accompanying drawings, in which: Fig. 1 is a graph showing binary discrimination regions in prior art average density slice method (already referred to); Figs. 2(a) to 2(c) are graphs showing results of binary encoding in the prior art average density slice method of Fig. 1 (already referred to); Fig. 3 is a block diagram of a prior art binary image processing apparatus (already referred to); Fig. 4 is a block diagram of a prior art circuit for implementing error diffusion method (already referred to); Fig. 5 is a schematic block diagram of a binary image processing apparatus according to an embodiment of the present invention; Fig. 6 is a flowchart showing sequences of binary encoding in the binary image processing apparatus of Fig. 5; Figs. 7(a) to 7(d) are graphs showing results of binary encoding of Fig. 6; Fig. 8 is a view showing a target pixel and its target region in a two-dimensional image in the binary image processing apparatus of Fig. 5; Fig. 9 is a flowchart showing operational sequences of an image processing circuit employed in the binary image processing apparatus of Fig. 5; Figs. 10(a) to 10(c) are graphs showing results of binary encoding of the image processing circuit of Fig. 9. Before the description of the present invention proceeds, it is to be noted that like parts are designated by like reference numerals throughout several views of the accompanying drawings. DETAILED DESCRIPTION OF THE INVENTION Referring now to the drawings, there is shown in Fig. 5, a binary image processing apparatus 101 according to an embodiment of the present invention. Light from a light source 103 such as a fluorescent lamp is irradiated onto an image of an original document 102. Then, reflected light from the original document 102 is read through a lens 105 by a solid pickup element 106 of a reading sensor 107 so as to be supplied, as an analog image signal corresponding to the image of the original document 102, to an analog-digital converter 108. The solid pickup element 106 is formed by, for example, a CCD (charge coupled device). The analog image signal is converted into a digital image signal S by the analog-digital converter 108 and the digital image signal S is fed to an image processing circuit 109. The image processing circuit 109 is formed by, for example, a microcomputer. After performing shading correction of characteristics of an optical system including the lens 105 or the pickup element 106, the image processing circuit 109 performs, based on the the digital image signal S, binary encoding corresponding to density of each pixel so as to output binary data. Hereinbelow, a fundamental configuration for implementing the present invention is described in the case of a one-dimensional linear image. It is assumed here that character x denotes a position of the linear image, characters f(x) denote the density of the linear image, characters f'(x) denote the linear differential of the density f(x) with respect to the position x and characters AVE(x) denote the average density of the linear image in the vicinity of the position x. Then, binary encoding from the density f(x) of the linear image to binary data D is performed by the following equation (1). In the equation (1), characters Sh denote a threshold level in binary encoding and the threshold level Sh is set by the following equation (2). In the equation (2), characters L + and L - are constants satisfying the following equation. L - < 0 < L + The constants L + and L - are properly set on the basis of the binary data obtained from binary encoding performed by the equations (1) and (2). Fig. 6 shows sequences of image processing of the binary image processing apparatus 101 in accordance with the above described fundamental configuration. When the digital image signal S representative of gradation data after analog-digital conversion has been inputted to the image processing circuit 109, the image processing circuit 109 stores the digital image signal S in a memory (not shown) at step n1. Then, at step n2, the density f(x), the change f'(x) of the density f(x) and the average density AVE(x) are calculated from the digital image signal S on the basis of predetermined operational equations, respectively. Subsequently, at step n3, it is judged whether or not the change f'(x) of the density f(x) is equal to the constant L - or L + or falls between the constants L - and L + . In the case of "YES" at step n3, the program flow proceeds to step n4 at which the threshold value Sh of binary encoding retains the threshold value Sh used in the immediately prior binary encoding. Step n4 is followed by step n6. On the other hand, in the case of "NO" at step n3, the average density AVE(x) of the target position x obtained at step n2 is set as the threshold value Sh at step n5 followed by step n6. At step n6, level of the density f(x) of the image is discriminated by the threshold value Sh set at step n4 or step n5. Namely, if the density f(x) of the image is not less than the threshold value Sh, program flow proceeds to step n7 at which the binary output D of 0 at the position x is outputted. Meanwhile, if the density f(x) of the image is smaller than the threshold value Sh, the binary output D of 1 is outputted at step n8. Figs. 7(a) to 7(d) show results of binary encoding of the density f'(x) of the one-dimensional linear image in the binary image processing apparatus 101, which binary encoding is based on the above equations (1) and (2). In this embodiment, by discriminating the change f'(x) of the density f(x) based on the constants L + and L - acting as the discrimination levels, the position x at which the density f(x) changes sharply is judged as a peripheral portion of a character in the image. At this time, only when the change f'(x) of the density f(x) is so large as to exceed the constant L + or is so small as to be smaller than the constant L - , the threshold level Sh in binary encoding is set at the average density AVE(x) of periphery of the position x corresponding to the specific target pixel selected for binary encoding. Meanwhile, when the change f'(x) of the density f(x) falls within a region ranging from the constant L - to the constant L + , the threshold level Sh is set at an average density AVE(xin) at a boundary position xin located immediately prior to entry of the position x into the above mentioned region along the scanning direction. Meanwhile, an initial value of the threshold level Sh may be properly set at, for example, an intermediate value between a maximum and a minimum of the density f(x). As described above, if absolute value of the change f'(x) of the density f(x) falls within the range bounded by the constants L + and L - , the threshold level Sh is maintained at the fixed value without being changed. Accordingly, even if the image of the original document 102 is a white light character, a black character in grey background or a white character in black background, the binary data obtained after binary encoding is capable of displaying boundary between the character and background vividly. Meanwhile, even if density of the image changes along a direction of a thin line, the image is not judged as periphery of the character so far as the change f'(x) of the density f(x) falls within the range bounded by the constants L + and L - , so that it becomes possible to stably perform binary image processing and thus, a high-quality image can be obtained in the binary image processing apparatus 101. Hereinbelow, two-dimensional binary encoding in which the image of the sheetlike original document 102 as shown in Fig. 5 is read by scanning the face of the original document 102 is described in place of the above described binary encoding of the density of the one-dimensional image. At this time, an x-y coordinate system is set on the face of the original document 102 as shown in Fig. 5 and a linear differential fxy(x, y) of a function f(x, y) of density of the image of the original document is given by the following equation (3). fxy (x, y) = df x, y /dx 2 + df x, y /dy 2 However, it is difficult to obtain the linear differential f'(x) in the case of the above described one-dimensional image by the image signal from the pickup element 106 of the reading sensor 107, for example, the CCD. Furthermore, calculation of the linear differential fxy(x, y) in the case of the two-dimensional image from the above equation (3) is not only difficult but offers problems such as drop of processing speed and rise of the production cost in, especially, an image scanner or the like. Thus, as shown in Fig. 8, a target region 110 of neighboring 3x3 pixels having a target pixel disposed at its center is set. From image signals SA to SH of the pixels forming the target region 110, the linear differentials df/dx and df/dy which are changes of density of the image in the directions of the x-axis and the y-axis, respectively are approximated by using the image signals SD and SH adjoining the target pixel laterally and the image signals SB and SF adjoining the target pixel vertically, respectively as shown in the following equation (4). Regarding the density changes fx and fy given by the equation (4), the threshold level Sh in binary encoding is set by the following equation (5). If fx < L - or fy < L - or L + < fx or L + < fy, then: Sh = AVE(x, y) If L - ≤ fx ≤ L + and L - ≤ fy ≤ L + , then: Sh = immediately prior value In the equation (5), characters L + and L - are constants satisfying the following equation. L - > 0 > L + Furthermore, in the equation (5), characters AVE(x, y) denotes average density of periphery of the target pixel and is given by the following equation (6). AVE(x, y) = (SA + SB + SC + SD + SE + SF + SG + SH)/8 Assuming that character D denotes a binary output, binary encoding of the digital image signal S corresponding to the target pixel is performed as follows by using the threshold value Sh determined by the equation (5). Fig. 9 shows sequences of binary encoding of the above described two-dimensional image in the binary image processing apparatus 101. Initially, at step ml, the digital image signal S is inputted. At step m2, the density f(x, y) of the pixel corresponding to the coordinates (x, y), the changes fx and fy of the density of the target region 110 including the pixel having the coordinates (x, y) and the average density AVE(x, y) of the target region 10 are calculated based on the inputted digital image signal S, the equation (4) and the equation (6), respectively. At step m3, it is judged whether or not the changes fx and fy of the density of the target region 110, which were calculated at step m2, satisfy the equation (5). In the case of "YES" at step m3, the program flow proceeds to step m4 at which the threshold value Sh in binary encoding retains the threshold value Sh used in the immediately prior binary encoding of the image. Step m4 is followed by step m6. On the other hand, in the case of "NO" at step m3, the average density AVE(x, y) of the target region 110 given by the equation (6) is set as the threshold value Sh at step m5 followed by step m6. At step m6, the digital image signal S of the pixel corresponding to the density f(x, y) is discriminated by using the threshold value Sh as the discrimination levels set at steps m4 and m5. In the case of "YES" at step m6, the binary output D of 0 is generated at step m7. On the contrary, in the case of "NO" at step m6, the binary output D of 1 is generated at step m8. Figs. 10(a) to 10(c) show results of the above described binary encoding of the two-dimensional image having the density f(x) of Figs. 7(a) to 7(d) in the direction of the x-axis as one scanning line. In Fig. 10(a), changes of the density f(x) shown by a solid line ℓ11 represent gradation data of each pixel of the solid line ℓ6 indicative of changes of the density f(x) shown in Figs. 7(a) to 7(d). A broken line ℓ12 indicates gradation data of a one-dot chain line ℓ10 showing the threshold value Sh in Fig. 7(c). Meanwhile, in Fig. 10(b), a solid line ℓ13 indicates operational results of a solid line ℓ7 based on the above equation (4), which solid line ℓ7 represents the density change f'(x) in Fig. 7(b). Therefore, the binary output D shown in Fig. 10(c) corresponds to the binary output D shown in Fig. 6(d). As will be seen from comparison between Fig. 10(c) and Fig. 7(d), even if the threshold value Sh in binary encoding based on the equations (4) to (6) is set for the target region having the target pixel as its center as shown in Fig. 8, it is possible to sufficiently accurately detect the boundary area between white pixels and black pixels in the image. Meanwhile, for example, even if a character larger than the region for obtaining the average density exists, the portion of the character is judged as black pixels once the boundary area between background and the character has been detected and unless the density changes sharply subsequently. Thus, omission of the black portion does not take place. The same effects as described above can be achieved also in the case of a white character in black background. In the above described embodiment, the threshold value Sh in binary encoding is so set as to fall in a permissible range bounded by the upper and lower limits. Thus, when the density of the image is not less than the threshold value Sh, it is judged that the pixel is a white pixel. On the contrary, when the density of the image is smaller than the threshold value Sh, it is judged that the pixel is a black pixel. As a result, it becomes possible to eliminate unnecessary patterns of background of a character or noises. Meanwhile, as shown in the equation (4), deviation between the image signals of the pixels adjoining the target pixel laterally and deviation between the image signals of the pixels adjoining the target pixel vertically are, respectively, regarded as change of the density in the direction of the x-axis and change of the density in the direction of the y-axis. Therefore, identical binary encoding is performed when change of the density of the image ascends and descends symmetrically with respect to the scanning direction of the x-axis in the reading sensor 107. Since difference between the image signals of the neighboring pixels of the target pixel interposed therebetween in the direction of the x-axis and difference between the image signals of the neighboring pixels of the target pixel interposed therebetween in the direction of the y-axis are obtained as described above, changes of the density obtained from the equation (4) become large. Accordingly, such an effect can be achieved that the boundary area between the character and its background can be detected more easily. In the above embodiment, changes of the density in the directions of the x-axis and the y-axis are, respectively, obtained from the digital image signals SD and SH of the pixels adjoining the target pixel laterally and the digital image signals SB and SF of the pixels adjoining the target pixel vertically. However, to this end, the digital image signals SA and SE of the pixels adjoining the target pixel obliquely and the digital image signals SC and SG of the pixels adjoining the target pixel obliquely may also be employed in addition to the above mentioned image signals SB, SD, SF and SH. Meanwhile, in order to calculate the average density in this embodiment, the equation (6) is used in which arithmetical mean of the digital image signals SA to SH is taken simply. However, the present invention is not restricted to this procedure. Namely, it can also be so arranged that after the digital image signals SA to SH have been weighted, the mean of the weighted digital image signals SA to SH is taken. Furthermore, in place of the eight neighboring pixels of the target pixel, a wider target region than the 3x3 pixels may be set such that the average density of the target region is taken. As will be seen from the foregoing, in this embodiment, the average density at the target pixel is obtained from a relatively narrow target region of the neighboring pixels of the target pixel. Thus, the line buffer memory used for obtaining the average density of the target pixel may have a small storage capacity, thereby resulting in reduction of the production cost. Meanwhile, in this embodiment, the threshold value in binary encoding is so set as to vary in accordance with the average density in only the region where the density changes greatly. Therefore, even in the cases of a white thin character or a black character in gray background or a white character in black background, an undesirable phenomenon is prevented according to which when the difference in density between the character and its background is small, the thin line forming the character is broken. Accordingly, binary encoding of the image can be performed clearly in accordance with the image and stably. In the above embodiment, the binary image processing apparatus 101 based on the image signal from the reading sensor 107 for the original document 102 has been described. However, the present invention can also be widely applied to a binary image processing apparatus based on video signals. Furthermore, binary encoding in the image processing circuit 109 may be performed by hardware such as an electric circuit in place of programming in the microcomputer or the like, thus resulting in rise of processing speed. In accordance with the embodiment of the present invention, in the first level discriminating means for performing level discrimination in binary encoding, the discrimination level is set to the average value of the density levels of the image signals of the pixels adjoining the target pixel for binary encoding when the differential value of the inputted image signal exceeds the predetermined discrimination level. Therefore, even if the image of the original document has small difference in density between a character and its background, for example, a white thin character, a black character in gray background or a white character in black background, the peripheral portion of the character can be detected clearly and stably for binary encoding. Consequently, performance of the binary image processing apparatus is improved and thus, quality of obtained image data is upgraded.

Claims: A binary image processing apparatus (101) comprising: a first level discriminating means (109) which has a first input terminal for receiving an image signal (S) having a level corresponding to the density (f(x)) of a target pixel of the image signal (S) and a second input terminal for receiving a signal indicative of a discrimination level (Sh) so as to discriminate level of the image signal (S) by the discrimination level (Sh) into binary data; a differential means (steps n2; m2) for obtaining a differential value (f'(x), f(x,y)/dx, f(x,y)/dy) of the density of the image signal (S) at the target pixel; a second level discriminating means (steps n3; m3) for discriminating the level of the differential value by two, respectively predetermined positive and negative discrimination levels (L + , L - ); a calculating means (steps n2; m2) for calculating in response to image signal in the vicinity of the target pixel an average value (AVE(x); AVE(x,y)) of density levels in vicinity of the target pixel; and a discrimination level changing means (steps n4; n5; m4; m5) which supplies said average value (AVE(x)); AVE(x,y)) to the second input terminal of said first level discriminating means (109) only if the associated differential value at the target pixel is discriminated to exceed the range defined by the positive and negative discrimination levels (L + , L - ) and otherwise retains for the actual target pixel the discrimination level (Sh) of the previous target pixel. The binary image processing apparatus according to claim 1, wherein for a two-dimensional binary image processing said differential means (step m2) is obtaining linear differential values (df(x,y)/dx, df(x,y)/dy) of the density of the image in a target image region (110) of k by k pixels having the target pixel disposed at its centre by using image signals of pixels respectively adjoining the target pixel, and said calculating means is calculating said average value of density levels on the basis of a mean value of the density values of pixels surrounding the target pixel. The binary image processing apparatus in accordance with claim 2, wherein k equals 3, said differential means is obtaining said linear differential values by using pixels adjoining said target pixel along mutually orthogonal axes and said calculating means is calculating said average value on the basis of an arithmetic mean value of the density values of all eight pixels surrounding the target pixel.

Inventors: TANAKA YUJI, TANAKA, YUJI
Applicants: SHARP KK, SHARP KABUSHIKI KAISHA
Application year: 1990
Main classification: H04N1
IPC codes: H04N1