JP2011166776A - Apparatus and method for processing image - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus for achieving image processing more suitably than before. <P>SOLUTION: The image processing apparatus includes an image read part, a monochromating processing part, an edge determination part, an edge inside determination part, a density determination processing part, an inside pixel width determination part, and an edge classification processing part. The image read part converts an original to image data of electronic data, and the monochromating processing part converts the image data to monochromatic data. The edge determination part determines whether a pixel of the image data is an edge of a drawn line. The edge inside determination part determines whether the pixel of the image data is inside the edge of the drawn line. The density determination processing part determines whether a density value of a pixel of monochromatic image data is dense. The internal pixel width determination part determines a type of line width. The edge classification processing part further classifies the pixel determined as an edge according to a line type. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The embodiment described in this specification relates to a technique for performing image area discrimination on input image data and performing appropriate image processing based on the result.

  Image processing based on the results of image area discrimination for image data, such as detecting character edges from image data output from image readers and performing edge enhancement, and detecting halftone dots and smoothing. Is a general image processing technique conventionally performed. By performing such image processing, even if the input image signal such as a thin line is low, character reproduction is improved by performing edge enhancement.

  If the emphasis is too strong, the edges will be overemphasized, and in the case of low-density halftone characters and designs, the contrast between the inside of the characters and designs and the edges will be emphasized, and the characters and designs will be outlined There is a problem that becomes.

  In general, when black characters are reproduced, toners of C (cyan), M (magenta), Y (yellow), and K (black) are superimposed and reproduced. In addition, since the reproduction of the black thin line is remarkably deteriorated, measures are taken such as increasing the K signal (black amount) or reproducing it with one black color. In this way, the black thin line reproduction is effective against color misregistration, but the difference between the edge of the character inside reproduction and the edge of the halftone character edge or pattern edge becomes significant. Therefore, the edge trimming described above is further promoted.

  The present embodiment has been made to solve the above-described problems, and an object thereof is to provide a technique for detecting by classifying the types of edges more finely.

  The image processing apparatus includes an image reading unit, a monochrome processing unit, an edge determination unit, an edge internal determination unit, a density determination processing unit, an internal pixel width determination unit, and an edge classification processing unit. The image reading unit scans a document and converts the document into image data of electronic data. The monochrome processing unit converts the image data converted by the image reading unit into monochrome data. The edge determination unit determines whether the pixel of the image data monochromeized by the monochrome processing unit is an edge of a line drawn in the image data or a non-edge. The edge inside determination unit determines whether or not the pixel of the image data monochromeized by the monochrome processing unit is inside the edge of the line drawn in the image data. The density determination processing unit determines whether or not the pixel density value of the image data monochromeized by the monochrome processing unit is dark by comparing with a threshold value. The internal pixel width determination unit determines the type of the line width when the pixel is inside the line edge based on the determination result of the edge determination unit and the determination result of the edge internal determination unit. The edge classification processing unit further classifies the pixels determined to be edges by the determination result by the edge determination unit based on the determination result of the internal pixel width determination unit and the determination result of the density determination unit, according to the line type.

It is sectional drawing which shows an example of an image processing apparatus. It is a block diagram which shows the structural example of a thin line determination part. It is a flowchart which shows the operation example of a thin line determination part. It is a figure explaining the process in an internal pixel width determination part. It is a figure which shows an example of the combination table which an edge classification | category process part uses. It is a block diagram which shows the structural example of an image area identification part. It is a figure which shows an example of the combination table which a character determination part uses. It is a figure which shows an example of the combination table which a comprehensive determination part uses. It is a block diagram which shows the structural example of an image process part. It is a figure which shows an example of the frequency characteristic of a filter. It is a figure which shows the example at the time of reading the pattern with a narrow space | interval of a line with a scanner.

  Before going into the detailed description of the present embodiment, the outline of the present embodiment will be described here.

  In general, a thin line or the like tends to have a lower signal read by an image reading unit such as a scanner than a thick line. Therefore, in order to improve the reproduction of the thin line, it is necessary to enhance the edge strongly. On the other hand, since the signal read by the scanner is high at the thick line, strong edge enhancement is not required. However, it is impossible to distinguish between the edge of the thin line and the edge of the thick line simply by detecting the edge. Therefore, if priority is given to reproduction of the thin line, the edge of the thick line is overemphasized, as described above. In particular, the halftone character and the edge of the pattern are reproduced with an outline.

  The present embodiment has been made in view of this problem, and the image processing apparatus according to the present embodiment applies a “thin line”, “thick line”, and “intermediate width line” that are equal to or smaller than the target line width in advance by the thin line determination process. Detect and classify edges, and perform processing according to the line width in filter processing and inking processing, etc., to improve the reproduction of fine lines and intermediate width lines and suppress halftone characters and pattern borders With the goal. It is another object of the present invention to improve fine line reproduction by detecting a character region and detecting a “fine line” as a grouped region even in the case of a character or pattern having a narrow line-to-line interval.

  Hereinafter, embodiments will be described with reference to the drawings.

  FIG. 1 is a longitudinal sectional view showing a schematic configuration of an image processing apparatus (MFP: Multi Function Peripheral) in the present embodiment. As shown in FIG. 1, the image processing apparatus 100 according to the present embodiment includes an image reading unit R and an image forming unit P.

  The image reading unit R has a function of scanning and reading images of a sheet document and a book document. The image reading unit R includes an automatic document feeder (ADF) 109 capable of automatically conveying a document to a predetermined image reading position, and a document tray (predetermined by the automatic document feeder 109). The scanning optical system 110 reads an image of the original placed on the original placement table Rt or an original placed on the original table (not shown).

  The image forming unit P has a function of forming a developer image on a sheet based on an image read from an original by the image reading unit R, image data transmitted from an external device to the image processing apparatus, or the like. . Further, the image forming unit P includes pickup rollers 151 to 154, photoconductors 102Y to 102K, developing rollers 103Y to 103K, mixers 104Y to 104K, an intermediate transfer belt 106, a fixing device 107, and a discharge tray 108.

  The image processing apparatus 100 also includes a processor 801 that is an arithmetic processing unit (for example, a CPU (Central Processing Unit) and an MPU (Micro Processing Unit)), and a memory 802 that includes a volatile storage device and a nonvolatile storage device. The image processing unit 800 is included. The processor 801 has a role of performing various processes in the image processing apparatus 100, and loads a program stored in the nonvolatile storage area of the memory 802 into the volatile storage area of the memory 802, and loads the program It also has a role of realizing various functions by executing. The memory 802 includes, for example, a RAM (Random Access Memory), a ROM (Read Only Memory), a DRAM (Dynamic Random Access Memory), an SRAM (Static Random Access Memory), a VRAM (Video RAM), a hard disk drive, and the like. And has a role of storing various information and programs used in the image processing apparatus 100.

  The image forming apparatus 100 includes a control panel 810 that includes a touch panel display 806. The control panel 810 accepts instructions from the user such as mode switching and displays processing contents to the user.

  Hereinafter, an outline of copy processing will be described as an example of processing in the image processing apparatus 100 according to the present embodiment.

  First, the sheet picked up from the cassette by the pickup rollers 151 to 154 is supplied into the sheet conveying path. The sheet supplied into the sheet conveyance path is conveyed in a predetermined conveyance direction by a plurality of roller pairs.

  Then, images of a plurality of sheet originals that are automatically and continuously conveyed by the automatic document conveying device 109 are read by the scanning optical system 110 at a predetermined image reading position.

  Next, the image processing unit 800 performs image processing on the image data read from the original by the image reading unit R. Based on the data after image processing, electrostatic latent images are formed on the photosensitive surfaces of the photoconductors 102Y, 102M, 102C, and 102K for transferring the Y, M, C, and K developer images to the sheet.

  Subsequently, the developer stirred by the mixers 104Y to 104K in the developing devices is supplied to the photoconductors 102Y to 102K on which the electrostatic latent images are formed as described above by the developing rollers (so-called mag rollers) 103Y to 103K. Is done. Thereby, the electrostatic latent image formed on the photosensitive surface of the photosensitive member is visualized.

  The developer image thus formed on the photosensitive member is transferred onto the belt surface of the intermediate transfer belt 106 (so-called primary transfer), and the developer image conveyed by the rotation of the intermediate transfer belt is a predetermined image. At the secondary transfer position T, the image is transferred onto the conveyed sheet.

  The developer image transferred onto the sheet is heated and fixed to the sheet by the fixing device 107. The sheet on which the developer image is heat-fixed is conveyed through the conveyance path by a plurality of conveyance roller pairs, and is sequentially discharged onto the discharge tray 108.

  Next, the image processing unit 800 of this embodiment will be described. Each unit described below is realized by a program stored in a nonvolatile storage area of the memory 802 being loaded into a volatile storage area of the memory 802 and the processor 801 executing an operation. Various data such as tables, threshold values, parameters, and data generated by each unit are stored in the memory 802. In the following description, a thin line determination unit that is one unit in the image processing unit 800 will be described first. Thereafter, an image area identification unit having a thin line determination unit will be described, and finally the entire image processing unit 800 will be described.

  FIG. 2 shows an example of a block diagram of the thin line determination unit of the present embodiment, and FIG. 3 is a flowchart showing an operation example of the thin line determination unit of the present embodiment. The thin line determination unit 10 includes a monochrome processing unit 1, a filter processing unit 2, an edge inside / outside determination unit 3, an edge region detection unit 4, a black edge detection unit 5, a density determination processing unit 6, an edge internal pixel determination unit 7, and a contraction process. Unit 8, internal pixel width determination unit 9, internal expansion processing unit 31, and edge classification processing unit 32. Hereinafter, the processing of each unit of the thin line determination unit 10 will be described with reference to the flowchart of FIG.

  (ACT1) The monochrome processing unit 1 acquires image data in which a document is converted into electronic data by the image reading unit R. In the RGB signal of the image data, the minimum value of R / G / B of each pixel is increased from 255. Monochrome processing is performed using the subtracted value as a representative value of each pixel. Here, the reason for subtracting from 255 is to convert the signal system to a density system in which the white value is 0 and the black value is 255. In the following explanation, the explanation is based on the assumption of the density system. Assumed to be performed. The conversion process to the density system is not necessarily performed. In this case, the subsequent process may be read as a luminance system in which the white value is 255 and the black value is 0. In addition, as a monochromatic method, a method using an average value of RGB is generally used. However, if the average value is used, a chromatic character signal is lost, and the accuracy of edge detection described later is lowered. Therefore, in the present embodiment, a technique using the minimum value of R / G / B is adopted in order to suppress a decrease in detection accuracy of chromatic color characters.

  (ACT2) The filter processing unit 2 performs a smoothing process for suppressing erroneous detection in a halftone dot region in edge detection described later. Note that sharpening processing may be performed to increase edge detection accuracy.

  (ACT3) The black edge detection unit 5 forms a matrix around the pixel of interest with respect to the image that has been monochromeized by the monochrome processing unit 1. Here, the matrix size is set to a size corresponding to the line width to be detected. For example, when it is desired to detect a width of about 7 pixels or less, the matrix size is set to 7 × 7. As an edge detection method, a pixel whose difference between the pixel of interest and the minimum value in the matrix is equal to or greater than a threshold value is a “black edge”;

  (ACT4) The edge region detection unit 4 is a matrix having the same size as the black edge detection unit 5 (size corresponding to the line width to be detected) centered on the target pixel with respect to the image monochromeized by the monochrome processing unit 1 Form. As an edge detection method in the edge region detection unit 4, a pixel whose difference between the maximum value and the minimum value in the matrix is equal to or greater than a threshold value is referred to as an “edge region”, and in other cases, a “non-edge region”.

(ACT5) The edge inside / outside determination unit 3 forms a matrix around the target pixel with respect to the image monochromeized by the monochrome processing unit 1. The matrix size formed here is larger than the size formed by the black edge detection unit 5 or the edge region detection unit 4. If the value calculated by the following formula is equal to or greater than the threshold, the target pixel is determined to be “inside the edge”, and if it is less than the threshold, it is determined to be “outside the edge”. A indicates the signal value of the target pixel, and max and min indicate the maximum value and the minimum value in the matrix, respectively.
edge _io = A-((max + min) / 2) +127

  (ACT6) The density determination processing unit 6 determines whether the target pixel is a “light” pixel or a “dark” pixel for each pixel by comparing the density value of the target pixel with a threshold value.

  (ACT7) Based on the result of the edge region detection unit 4, the edge internal pixel determination unit 7 re-determines whether the pixel determined to be inside the edge by the edge inside / outside determination unit 3 is inside the edge. Only when the result of the edge region detection unit 4 is “non-edge region” and the result of the edge inside / outside determination unit 3 is determined to be “inside the edge”, the edge inside pixel determination unit 7 determines that the pixel is “inside the edge”. Is determined. In cases other than the above, "Other" is assumed.

  (ACT8) The contraction processing unit 8 re-determines whether the pixel is an “edge region” or a “non-edge region” based on the result of the black edge detection unit 5 and the result of the edge region detection unit 4. The contraction processing unit 8 first forms a matrix around the target pixel with respect to the result of the edge region detection unit 4. When a predetermined number or more of “non-edge region” pixels exist around the pixel of interest (matrix size) and the result of the black edge detection unit 5 of the pixel of interest is “non-black edge”, the pixel of interest is “ It is determined as “non-edge region”. When the result of the black edge detection unit 5 of the target pixel is “black edge”, it is unconditionally determined as “edge region”.

  (ACT9) The internal pixel width determination unit 9 determines the width of the internal pixel based on the results of the edge internal pixel determination unit 7 and the contraction processing unit 8. The internal pixel width determination unit 9 forms a matrix around the pixel of interest, and when the result of the edge internal pixel determination unit 7 of the pixel of interest is “inside the edge”, contraction processing is performed for each of the eight directions shown in FIG. The pixels whose result of the section 8 is “non-edge region” are counted until the “edge region” or the size of the matrix is exceeded. For example, in three pixels in the d3 direction (three pixels on the right from the target pixel in FIG. 4), in order from the pixel closest to the target pixel (from the left in the d3 direction in FIG. 4), “non-edge region”, “ In the case of “edge region” and “non-edge region”, the count number is 1, and in the case of “non-edge region”, “non-edge region”, and “edge region”, the count number is 2. Thus, the count value in each direction is 3 at the maximum when the matrix size is 7 × 7, for example.

The internal pixel width determination unit 9 calculates pixel widths in two vertical, horizontal, and diagonal directions using the following formula. In the following equations, d1 to d8 are pixel count values in the respective directions.
Longitudinal direction = d1 + d5 + 1
Lateral direction = d3 + d7 + 1
Diagonal direction 1 = d2 + d6 + 1
Diagonal direction 2 = d4 + d8 + 1
Of the pixel widths in the four directions, when the minimum pixel width is equal to or smaller than the threshold value, “inside the intermediate width line” is set, and when larger than the threshold value, “inside the thick line” is set. When the determination result by the edge internal pixel determination unit 7 of the target pixel is “other”, the determination of the internal pixel width is not performed, and the determination result of “other” is output to the subsequent processing as it is.

  (ACT10) The internal expansion processing unit 31 expands the result of the internal pixel width determination unit 9 around based on the result of the density determination unit 6. The internal expansion processing unit 31 forms a matrix with the pixel of interest at the center and the matrix size formed by the black edge detection unit 5 or more. Here, it is 11 × 11 as an example. The internal dilation processing unit 31 counts the “intermediate width line internal” determination result and the “thick line internal” determination result around the pixel of interest (matrix range (11 × 11)), and the density determination unit 6 of the pixel of interest When the result is “light”, the determination result of the target pixel is replaced with the determination result with the larger count value. If the result of the density determination unit 6 is “dark”, or if the result of the internal pixel width determination unit 9 is “other”, the result of the internal pixel width determination unit 9 is output as it is to other subsequent processes.

  (ACT11) Based on the results of the contraction processing unit 8 and the internal expansion processing unit 31, the edge classification processing unit 32 further uses the determination result of the pixel determined as the edge by the determination result by the contraction processing unit 8 as a line type. Classify accordingly. The edge classification is determined for each pixel based on the combination of the processing results of the contraction processing unit 8 and the internal expansion processing unit 31, and an example of the combination is shown in FIG.

  In addition, the mounting which does not have the internal expansion process part 31 is also considered. In this case, the edge classification processing unit 32 performs classification by combining the results of the contraction processing unit 8, the internal pixel width determination unit 9, and the density determination unit 6 in ACT11. An example of this combination is shown in FIG.

  With the above configuration, in the input image data, it is possible to classify whether the target pixel is “edge” or “non-edge” for each pixel, and when the target pixel is “edge”, “light” It is possible to classify the edge of “intermediate width line”, the edge of “thin thick line”, the edge of “thin line or thick thick line, or dark intermediate width line”.

  Note that a unit (indicated by a broken line in FIG. 2) including the edge inside / outside determination unit 3, the edge region detection unit 4, and the edge internal pixel determination unit 7 is referred to as an edge internal determination unit 33, and the black edge detection unit 5 and the edge A unit (unit indicated by an alternate long and short dash line in FIG. 2) configured by the region detection unit 4 and the contraction processing unit 8 is referred to as an edge determination unit 34. In this case, the edge inside determination unit 33 determines whether or not the pixel of the image data monochromeized by the monochrome processing unit 1 is inside the edge of the line drawn in the image data. The edge determination unit 34 determines whether the pixel of the image data monochromeized by the monochrome processing unit 1 is an edge or a non-edge of a line drawn in the image data, and whether the detection target line is within the matrix Is determined using a matrix having a size that fits in

FIG. 6 is a diagram illustrating a configuration example of the image area identification unit 20 including the thin line determination unit 10 described above.
The image area identification unit 20 further includes an edge detection unit 11 that detects an edge of an image drawn in the scanned image data, a halftone dot determination unit 12 that determines whether the image is a halftone dot, or scanned image data The background determination unit 13 determines whether an arbitrary area (which may be a pixel unit, the same applies hereinafter) is a white background or a background, and the arbitrary area of scanned image data is chromatic or achromatic. An achromatic color detection unit 14 for determining whether or not, a character determination unit 15, and a comprehensive determination unit 16.

  Based on the detection result of the edge detection unit 11 and the result of the halftone dot determination by the halftone dot determination unit 12, the character determination unit 15 uses the combination table of FIG. Judge whether it is "character".

  The comprehensive determination unit 16 outputs two types of determination results, a determination result used by a filter unit 22 and a gradation processing unit 24 described later, and a determination result used by the inking unit 23.

  The comprehensive determination unit 16 uses the character determination result by the character determination unit 15 and the result (edge classification processing) by the character determination unit 15 as the comprehensive determination result (hereinafter referred to as the comprehensive determination result 1) used by the filter unit 22 / tone processing unit 24. 8), using the combination table of FIG. 8A, “non-character”, “character 1” indicating a thin thick line, “character 2” indicating a thin intermediate width line, thin line, dark thick line or Output another “character 3” indicating a dark intermediate width line.

  The comprehensive determination unit 16 also determines the determination result (character determination result) by the character determination unit 15 and the result (background determination result) by the character determination unit 15 as the comprehensive determination result (hereinafter referred to as comprehensive determination result 2) used by the inking unit 23. ), The result by the achromatic color determination unit 14 (achromatic color detection result), and the result by the thin line determination unit 10 (thin line determination result), as shown in the combination table of FIG. "" Black characters on the background "" "Black characters on the background" are output.

  By obtaining these comprehensive determination results, the filter unit 22, the inking unit 23, and the gradation processing unit 24 can perform appropriate processes.

  FIG. 9 is a block diagram illustrating a configuration example of the image processing unit 800 including the image area identification unit 20. The image processing unit 800 generates a black amount (K signal) from the color conversion unit 21 that converts an RGB signal into a CMY signal, a filter unit 22 that performs edge enhancement and smoothing, a ratio of the CMY signal, and the like. An inking unit 23 for converting the image into a color tone, and a tone processing unit 24 for generating a pseudo tone according to the characteristics of the printer.

Specific processing examples of the filter unit 22 and the inking unit 23 will be described below.
When the comprehensive determination result 1 (see FIG. 8A) is determined to be “character 1” (thin thick line) in the processing of the image area identification unit 20, the filter unit 22 is used for character that becomes weak edge enhancement. If the process is performed using a filter and it is determined that the character is “character 2” (thin intermediate width line), the process is performed using a character filter that performs medium edge enhancement. On the other hand, when it is determined as “character 3” (thin line, thick thick line, dark intermediate width line), the filter unit 22 performs processing using a character filter for enhancing edge enhancement. When the comprehensive determination result 1 is determined as “non-character”, the filter unit 22 performs processing using a filter (smoothing process) suitable for a photograph (halftone dot).
Here, the frequency characteristic of the fine line filter is preferably a filter (see FIG. 10A) that emphasizes all frequency bands from low to high frequencies, and the frequency characteristic of the intermediate line filter is fine line. A filter (see FIG. 10B) having a low gain with respect to the characteristics of the filter for use is desirable. As for the frequency characteristics of a photographic filter, a low frequency band is slightly emphasized to improve sharpness, and a medium to high frequency band is smoothed to suppress moire and roughness (see FIG. 10C). ) Is desirable.

  Further, when a pattern having a narrow line-to-line interval as shown in FIG. 11A is read by a scanner, a signal is present to some extent between the lines that are originally the ground (FIG. 11A). When the edge between the lines is not detected as an edge, the signal is not emphasized and the signal remains between the lines (see FIG. 11B). However, according to the present embodiment, since a line between narrowly spaced lines is determined as an edge, it is possible to remove a signal between lines by emphasizing by filtering (see FIG. 11C). ).

  The inking unit 23 determines that the comprehensive determination result 2 (see FIG. 8B) is “black character on background” in the processing of the image area identification unit 20, that is, the region is “black thin line with white background”. ”,“ Because the background is a white black dark middle line or thick line ”, the signals of each color are set so that CMY is reproduced with one color of K without overlapping and reproducing. This is to prevent the character reproduction from deteriorating significantly due to color misregistration at the time of printing when the thin line is reproduced by overlapping CMY.

  Further, when the comprehensive determination result 2 (see FIG. 8B) is determined to be “black character on background” in the processing of the image area identification unit 20, the inking unit 23 reproduces the CMYK superimposed. In addition to setting each color signal, the black amount (K signal) to be generated is set to be large. In this way, for example, it is possible to prevent an extreme reproduction difference from appearing at the switching portion of the “thin line” and the switching portion of the “intermediate width line” with a thin character or the like.

  In addition to “black characters on the background” and “black characters on the background”, the inking unit 23 sets the black amount (K signal) based on the CMY signal ratio by a general inking process (for example, UCR or GCR). The CMY signal is set to be reduced according to the black amount.

  Each threshold value and matrix size used by each unit of the present embodiment may be defined in the memory 802 for each mode such as “photo mode” and “character mode”, for example. Implementation in which the threshold value and the size of the matrix are switched according to the designated mode is also possible.

  Various processes realized by causing a CPU or MPU to execute a program in each of the above-described embodiments can also be executed in a circuit form by an ASIC (Application Specific Integrated Circuit). Needless to say.

  In the above description, the copy function of the image processing apparatus 100 has been described as an example. However, the present embodiment is applicable to each function of the image processing apparatus 100 such as a scan function and a FAX transmission / reception function.

  As described in detail above, line edges can be classified in more detail, and more suitable image processing can be realized for input image data.

  The present invention can be implemented in various other forms without departing from the spirit or main features thereof. Therefore, the above-described embodiment is merely an example in all respects and should not be interpreted in a limited manner. The scope of the present invention is indicated by the scope of claims, and is not restricted by the text of the specification. Further, all modifications, various improvements, alternatives and modifications belonging to the equivalent scope of the claims are all within the scope of the present invention.

  DESCRIPTION OF SYMBOLS 1 Monochrome processing part, 2 Filter processing part, 3 Edge inside / outside determination part, 4 Edge area | region detection part, 5 Black edge detection part, 6 Density determination processing part, 7 Edge internal pixel determination part, 8 Shrinkage processing part, 9 Internal pixel Width determination unit, 31 Internal expansion processing unit, 32 Edge classification processing unit, 33 Edge internal determination unit, 34 Edge determination unit, 10 Fine line determination unit, 11 Edge detection unit, 12 Halftone determination unit, 13 Background determination unit, 14 None Color detection section, 15 character determination section, 16 comprehensive determination section, 20 image area identification section, 21 color conversion section, 22 filter section, 23 inking section, 24 gradation processing section, 100 image processing apparatus, 800 image processing section, 810 Control panel, R image reading unit, P image forming unit.

Claims (12)

An image reading unit that scans a document and converts the document into image data of electronic data;
A monochrome processing unit that converts the image data converted by the image reading unit into monochrome data;
An edge determination unit that determines whether a pixel of the image data monochromeized by the monochrome processing unit is an edge of a line drawn in the image data or a non-edge;
An edge inside determination unit that determines whether or not the pixel of the image data monochromeized by the monochrome processing unit is inside the edge of a line drawn in the image data;
A density determination processing unit that determines whether or not the density value of the pixel of the image data monochromeized by the monochrome processing unit is dark by comparing with a threshold value;
Based on the determination result of the edge determination unit and the determination result of the edge internal determination unit, when the pixel is inside the edge of the line, an internal pixel width determination unit that determines the type of the width of the line;
An edge classification processing unit for further classifying pixels determined to be edges according to the determination result by the edge determination unit based on the determination result of the internal pixel width determination unit and the determination result of the density determination unit according to the line type; ,
An image processing apparatus. The image processing apparatus according to claim 1.
The image processing apparatus according to claim 1, wherein the edge determination unit determines whether or not an edge is detected using a matrix centered on a target pixel. The image processing apparatus according to claim 2,
The image processing apparatus according to claim 1, wherein the size of the matrix is a matrix having a size that allows detection-target lines to be contained within the matrix. The image processing apparatus according to claim 3.
The edge determination unit sets, as a first non-edge, a pixel in which a difference between a value of a target pixel and a minimum value in the matrix centered on the target pixel is less than a threshold value,
A pixel whose difference between the maximum value and the minimum value in the matrix is less than a threshold is defined as a second non-edge,
When a predetermined number or more of second non-edges exist in the matrix centered on the target pixel and the target pixel is the first non-edge, the target pixel is set to the non-edge, thereby forming an edge. An image processing apparatus for determining whether the image is a non-edge. The image processing apparatus according to claim 1.
The edge inside determination unit uses the first matrix having a size in which the detection target line is within the matrix and the second matrix having a size larger than the first matrix, with the pixel of interest as the center. An image processing apparatus that determines whether or not an edge is inside. The image processing apparatus according to claim 1.
The image processing apparatus according to claim 1, wherein the monochrome processing unit converts the minimum value of RGB colors of the image data converted by the image reading unit into a single color as a representative color. The image processing apparatus according to claim 1.
The internal pixel width determination unit is a pixel in which the target pixel is determined to be inside the edge by the edge internal determination unit, and based on the number of pixels from the target pixel to a pixel determined to be an edge by the edge determination unit If the calculated value is greater than or equal to a threshold value, the line width type is determined to be a thick line, and if the calculated value is smaller than the threshold value, the line width type is determined to be an intermediate width line. Processing equipment. The image processing apparatus according to claim 7.
The edge classification processing unit converts pixels determined to be edges according to the determination result by the edge determination unit based on the determination result of the internal pixel width determination unit and the determination result of the density determination unit to a thin intermediate width line. An image processing apparatus that classifies an edge pixel, a thin thick-line edge pixel, and another edge pixel. The image processing apparatus according to claim 1, further comprising:
Character determination for determining whether an arbitrary region of the image data is a character region based on the detection result of the edge of the image drawn in the image data converted by the image reading unit and the result of the halftone dot determination And
A filter unit that performs filtering processing on the image data according to a combination of a result classified according to a line type by the edge classification processing unit and a determination result by the character determination unit;
An image processing apparatus comprising: The image processing apparatus according to claim 9, further comprising:
An achromatic color determining unit for determining whether the arbitrary region is a chromatic color or an achromatic color;
A background determination unit that determines whether the arbitrary region is a white background or a background,
Ink according to the combination of the result classified by the edge classification processing unit according to the line type, the determination result by the character determination unit, the determination result by the achromatic color determination unit, and the determination result by the background determination unit An inking unit that performs an inking process on the image data;
An image processing apparatus comprising: The image processing apparatus according to claim 1.
The threshold value and the size of the matrix are switched according to a mode set by a user. The image processing device
Scan the document, convert the document to electronic image data,
Convert the converted image data to monochrome data,
It is determined whether the pixels of the monochrome image data are edges of lines drawn in the image data or non-edges using a matrix having a size according to the line width of the detection target,
Determining whether the pixel of the monochrome image data is inside the edge of the line drawn in the image data;
It is determined whether the density value of the pixel of the monochrome image data is dark by comparing with the threshold value,
Based on the determination result whether it is the edge or the non-edge and the determination result whether it is inside the edge, when the pixel is inside the edge of the line, the type of the width of the line is determined,
Based on the determination result of the pixel width and the determination result of whether the density value is dark, the determination result of the pixel determined to be an edge in the determination result of the edge or the non-edge is further in accordance with the line type. Image processing method.

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