JP2020098497A - Image processing method, image processing program, and image processing device - Google Patents

Abstract

To provide an image processing method which enables appropriate and high speed thinning processing.SOLUTION: An image processing method includes: scanning image data in a predetermined direction in an image based on the image data and detecting an edge pixel pair of an object; imparting attribute of an internal edge to the pixel forming the contour of the object and imparting attribute of an external edge to a pixel adjacent to the internal edge outside the object; imparting attribute of an internal non-edge to the pixel determined to be the pixel inside the object on the basis of a positional relationship between the internal edge pixel and the outer edge pixel; and, when determining the internal edge pixel as an attraction pixel, determining whether or not to replace a pixel value of the attraction pixel with a pixel value of the pixel adjacent in a direction opposite the predetermined direction with respect to the attraction pixel, on the basis of the total number of the internal edge pixel and the internal non-edge pixel in an adjacent pixel adjacent to the attraction pixel and the positional relationship therebetween.SELECTED DRAWING: Figure 10

Description

The present invention relates to an image processing method, an image processing program, and an image processing device.

The character image of the document scanned by the scanner may become thick due to the scanner characteristics. Further, since the electrophotographic image forming apparatus has a relatively large dot gain, the character image may be formed thick on the recording medium. A thinning process is known as one of the image processes generally performed in such a case.

The following technique is known in Japanese Patent Application Laid-Open No. 2004-242242 related to the thinning process. A contour area of a character or a line drawing is extracted based on the image data, and an area having a fine line structure is detected based on the image data. Then, thinning processing for adjusting the output level based on the input level of the pixel value is performed on the modified area excluding the area having the thin line structure from the contour area, thereby preventing the thin line from disappearing due to the thinning processing.

Japanese Patent Application No. 2005-341249

However, in the technique disclosed in Patent Document 1, it is necessary to detect a region having a thin line structure having a line width of 2 or 3 pixels or less and exclude the region from the target of the thinning process, which makes the thinning process complicated, There is a problem that it is relatively difficult to speed up the thinning process.

The present invention has been made to solve such a problem. That is, it is an object of the present invention to provide an image processing method, an image processing program, and an image processing apparatus capable of performing appropriate and high-speed thinning processing.

The above problems of the present invention are solved by the following means.

(1) scanning multi-valued image data for each color in a predetermined direction in an image based on the multi-valued image data to detect an edge pixel pair forming an edge of an object; Of the pair of edge pixels detected in (a), the attribute forming the outline of the object is given the attribute of the internal edge to form the internal edge pixel, and the pixel adjacent to the internal edge outside the object is externally output. The step (b) in which an edge attribute is added to form an external edge pixel, and the internal pixel is added to the pixel in which neither the internal edge attribute nor the external edge attribute is added in the step (b). Based on the positional relationship between the edge pixel and the external edge pixel, it is determined whether the pixel is an internal pixel of the object, and an internal non-edge attribute is added to the pixel determined to be the internal pixel of the object. And (c), and when the internal edge pixel is set as the target pixel, the internal edge pixel and the internal non-edge pixel of the adjacent pixels that are close to each other within the predetermined number of pixels from the target pixel are selected. Based on the total number and the positional relationship between the internal edge pixel and the internal non-edge pixel among the adjacent pixels, the pixel value of the target pixel is set to the predetermined direction with respect to the target pixel. And (d) determining whether to replace the pixel value of a pixel adjacent in the opposite direction.

(2) The image processing method according to (1), wherein the multi-valued image data is color image data.

(3) In the step (a), the predetermined 3×1 Laplacian filter for filtering pixel values of three pixels including the edge detection target pixel and two pixels before and after the edge detection target pixel is used. Scanning in the direction, and calculating the edge value of the edge detection target pixel, and detecting a pixel pair adjacent to a pixel whose absolute value of the edge value of at least one color is a threshold value or more as the edge pixel pair. The image processing method according to (1) or (2).

(4) In the step (b), the brightness is calculated for each of the edge pixel pairs detected in the step (a), the attribute of the internal edge is given to the pixel with the lower brightness, and the pixel with the higher brightness is given. The image processing method according to any one of (1) to (3) above, wherein the attribute of the external edge is given to the pixel.

(5) In the step (b), each time the edge pixel pair is detected in the step (a), the attribute is given to each pixel of the detected edge pixel pair, and the step (c) is performed. ), in the step (b), if the attribute firstly given after the attribute of the internal edge is given is the attribute of the internal edge, the two internals given the attribute of the internal edge are given. The image processing method according to any one of (1) to (4) above, wherein the attribute of the internal non-edge is added to all the pixels existing between edge pixels to make the internal non-edge pixels.

(6) In the step (c), if no pixel of the edge pixel pair exists between the edge of the image and the internal edge pixel, the edge of the image and the internal edge pixel are separated from each other. 6. The image processing method according to any one of (1) to (5) above, wherein the internal non-edge attribute is given to pixels in between to be the internal non-edge pixels.

(7) In the step (c), after the external edge pixel of the first edge pixel pair appears, a pixel that first appears in the predetermined direction as a pixel forming the edge pixel pair is the first edge pixel pair. If the inner edge pixel of the second edge pixel pair different from the first edge pixel pair is the pixel adjacent to the inner edge pixel of the second edge pixel pair in a direction opposite to the predetermined direction of the inner edge pixel. An attribute of internal non-edge is given to the internal non-edge pixel, and after the internal edge pixel of the third edge pixel pair appears, first appears as a pixel forming the edge pixel pair in the predetermined direction. When the determined pixel is the external edge pixel of the fourth edge pixel pair different from the third edge pixel pair, the pixel adjacent to the internal edge pixel of the third edge pixel pair in the predetermined direction. The image processing method according to any one of (1) to (6) above, wherein the internal non-edge attribute is added to the internal non-edge pixel to make the internal non-edge pixel.

(8) In the step (d), the predetermined number of pixels is 1, the adjacent pixels are eight adjacent pixels, and in the step (d), among the eight adjacent pixels, the internal edge pixel and The pixel value of the target pixel is set to the target pixel based on the total number of the internal non-edge pixels and the positional relationship between the internal edge pixel and the internal non-edge pixel among the eight adjacent pixels. On the other hand, the image processing method according to any one of (1) to (7), wherein it is determined whether or not the pixel value of a pixel adjacent in the opposite direction to the predetermined direction is replaced.

(9) In the step (d), when the total number and the positional relationship are [1] the total number is 0 or 7, [2] the total number is 1 and eight adjacent pixels are respectively provided. If the value obtained by adding the number of the internal edge pixels and the number of the internal non-edge pixels among the eight adjacent pixels is 2 or less, [3] the total number is 2 and the pixel to which the number is added as the total number is When adjacent, [4] when the total number is 3 and the pixel to which the number is added as the total number is adjacent, [5] when the total number is 4 and the number is added to the total number [6] If the total number is 5, and a pixel that is neither the internal edge pixel nor the internal non-edge pixel among the adjacent pixels is 6 with respect to the pixel of interest, When both the upper and lower sides, both the left and right sides, or both in the diagonal direction are present, and [7] the total number is 6 and the internal edge pixel and the internal non-edge pixel among the adjacent pixels are If any of the pixels exists in both the upper and lower sides, both the left and right sides, or both in the diagonal direction with respect to the target pixel, the pixel value of the target pixel is set to the target pixel. It is determined that the pixel value of the external edge pixel adjacent to the pixel of interest, which is scanned immediately before the pixel scanning, is not replaced, and the total number and the positional relationship are any of the above [1] to [7]. If not, it is determined that the pixel value of the target pixel is to be replaced with the pixel value of the external edge pixel that is scanned immediately before the target pixel is scanned and that is adjacent to the target pixel. Image processing method.

(10) The method further includes a step (e) of accepting the selection of the strength of the thinning process, and when the weak selection is accepted in the step (e), the predetermined direction is set as the first direction and the step (a) is performed. After performing (d) to (d), the steps (a) to (d) are performed with the predetermined direction as a second direction orthogonal to the first direction, and a strong selection is accepted in the step (e). In this case, after performing the steps (a) to (d) with the predetermined direction as the first direction, the steps (a) to (d) are performed with the predetermined direction as the second direction, and further, After performing the steps (a) to (d) with the predetermined direction as a third direction opposite to the first direction, the predetermined direction is set as a fourth direction opposite to the second direction. The image processing method according to any one of (1) to (9), wherein the steps (a) to (d) are performed.

(11) After performing the steps (a) to (d) with the predetermined direction as a fifth direction, the steps (a) to (d) are performed with the predetermined direction as a direction orthogonal to the fifth direction. The image processing method according to any one of (1) to (9) above.

(12) After performing the steps (a) to (d) with the predetermined direction as a sixth direction, the steps (a) to (d) are performed with the predetermined direction opposite to the sixth direction. The image processing method according to any one of (1) to (9) above.

(13) The method further includes a step (f) of generating a plurality of divided data by dividing the multi-valued image data corresponding to a plurality of regions of an image based on the multi-valued image data, and the step (a). The image processing method according to any one of (1) to (12) above, wherein steps (a) to (d) are performed in parallel on the plurality of divided data.

(14) In the step (f), the multi-valued image data is divided corresponding to a plurality of regions of the image based on the multi-valued image data, and a division direction of the image based on the divided data after the division is divided. The image processing method according to (13) above, wherein a margin portion of 2 pixels or more is added to the upper and lower end portions of the, and the plurality of divided data corresponding to the divided images to which the margin portion is added are generated.

(15) In the step (d), if it is determined that the pixel value of the target pixel is replaced with the pixel value of a pixel adjacent to the target pixel in the opposite direction to the predetermined direction, the target value is determined. The pixel value of the pixel is replaced with the pixel value of a pixel adjacent to the target pixel in the direction opposite to the predetermined direction, and the pixel value of the target pixel is set in the predetermined direction with respect to the target pixel. On the other hand, if it is not determined that the pixel value of the pixel adjacent in the opposite direction is to be replaced, the pixel value of the target pixel is not replaced with the pixel value of the pixel adjacent to the target pixel in the opposite direction to the predetermined direction. The image processing method according to any one of (1) to (14), further including step (g).

(16) A step (a) of detecting multi-valued image data for each color in a predetermined direction in an image based on the multi-valued image data to detect an edge pixel pair forming an edge of an object, and the step (a). Of the pair of edge pixels detected in (a), the attribute forming the outline of the object is given the attribute of the internal edge to form the internal edge pixel, and the pixel adjacent to the internal edge outside the object is externally output. The procedure (b) in which an attribute of an edge is added to form an external edge pixel, and the internal pixel is added to a pixel to which neither the attribute of the internal edge nor the attribute of the external edge is added in the procedure (b). Based on the positional relationship between the edge pixel and the external edge pixel, it is determined whether the pixel is an internal pixel of the object, and an internal non-edge attribute is added to the pixel determined to be the internal pixel of the object. (C) and the internal edge pixel and the internal non-edge pixel among the adjacent pixels that are close to each other within a predetermined number of pixels from the target pixel when the internal edge pixel is the target pixel. Based on the total number and the positional relationship between the internal edge pixel and the internal non-edge pixel among the adjacent pixels, the pixel value of the target pixel is set to the predetermined direction with respect to the target pixel. An image processing program for causing a computer to execute a process including a step (d) of determining whether or not to replace a pixel value of a pixel adjacent in the opposite direction.

(17) A detection unit configured to scan the multivalued image data for each color in a predetermined direction in an image based on the multivalued image data to detect an edge pixel pair forming an edge of an object, and the detection unit. Of the detected edge pixel pairs, the attribute forming the outline of the object is given an internal edge attribute to make it an internal edge pixel, and the pixel adjacent to the internal edge outside the object is given the external edge attribute. A first attribute assigning unit that assigns an external edge pixel, and the internal edge pixel to a pixel to which neither the attribute of the internal edge nor the attribute of the external edge is assigned by the first attribute assigning unit Based on the positional relationship between the pixel and the external edge pixel, it is determined whether the pixel is inside the object, and the pixel determined to be the pixel inside the object is given an internal non-edge attribute to be an internal non-edge pixel. A total of the internal edge pixel and the internal non-edge pixel among the adjacent pixels that are within a predetermined number of pixels from the pixel of interest when the second attribute assigning unit and the internal edge pixel are pixels of interest. The pixel value of the target pixel is opposite to the target pixel in the predetermined direction based on the number and the positional relationship between the internal edge pixel and the internal non-edge pixel among the adjacent pixels. An image processing apparatus, comprising: a determination unit that determines whether or not the pixel values of pixels adjacent in the direction are to be replaced.

Attributes of edges inside and outside the object are assigned to pixel pairs forming the edge of the object included in the image, and pixels other than the pixel concerned are determined to be inside the object based on the positional relationship of the pixels to which the attribute is assigned. , Add attributes in the object. Then, among the pixels adjacent to the target pixel having the edge attribute in the object, the target pixel is scanned immediately before the target pixel based on the number and positional relationship of the pixels having the attribute in the object. It is determined whether or not the pixel value is replaced. This enables appropriate and high-speed thinning processing.

It is a schematic diagram showing a configuration of an image forming apparatus. FIG. 3 is a block diagram showing a configuration of an image forming apparatus. It is a flowchart of a thinning process of image data. It is a subroutine flowchart of step S101 of FIG. It is an explanatory view for explaining division of image data. 4 is a flowchart of a subroutine of step S102 of FIG. 7 is a flowchart of a subroutine of step S309 of FIG. It is an explanatory view for explaining embedding processing of an attribute of each pixel of a target image. 7 is a flowchart of a subroutine of step S311 of FIG. It is a subroutine flowchart of step S103 of FIG. It is a figure which shows the replacement conditions which replace the left edge of an object. It is a figure which shows the replacement conditions which replace the left edge of an object. It is a figure which shows the replacement conditions which replace the left edge of an object. It is a figure which shows the replacement conditions which replace the left edge of an object. It is a figure which shows the replacement conditions which replace the left edge of an object. It is a figure which shows the result of a thinning process.

Hereinafter, an image processing method, an image processing program, and an image processing apparatus according to an embodiment of the present invention will be described with reference to the drawings. In addition, in the drawings, the same elements are denoted by the same reference numerals, and overlapping description will be omitted. Further, the dimensional ratios in the drawings are exaggerated for convenience of description, and may differ from the actual ratios.

FIG. 1 is a schematic diagram showing the configuration of an image forming apparatus 100 including an image processing apparatus according to an embodiment of the present invention. FIG. 2 is a block diagram showing the configuration of the image forming apparatus 100.

The image forming apparatus 100 includes a control unit 110, a storage unit 120, a communication unit 130, an operation display unit 140, an image reading unit 150, an image control unit 160, and an image forming unit 170. These components are communicatively coupled to each other by a bus 180. The image forming apparatus 100 may be configured by an MFP (MultiFunction Peripheral). The control unit 110 constitutes a detection unit, a first attribute assignment unit, a second attribute assignment unit, and a determination unit.

The control unit 110 includes a CPU (Central Processing Unit) and various memories, and controls each of the above units and performs various arithmetic processes according to a program. Details of the operation of the control unit 110 will be described later.

The storage unit 120 includes an HDD (Hard Disc Drive), an SDD (Solid State Drive), or the like, and stores various programs and various data.

The communication unit 130 is an interface for communicating between the image forming apparatus 100 and an external device. As the communication unit 130, a network interface according to standards such as Ethernet (registered trademark), SATA, and IEEE 1394 is used. Further, as the communication unit 130, various local connection interfaces such as a wireless communication interface such as Bluetooth (registered trademark) and IEEE 802.11 are used.

The operation display unit 140 includes a touch panel, a numeric keypad, a start button, a stop button, and the like, displays various kinds of information, and receives inputs of various kinds of instructions.

The image reading unit 150 includes a light source such as a fluorescent lamp and an image sensor such as a CCD (Charge Coupled Device) image sensor. The image reading unit 150 applies light from a light source to a document set at a predetermined reading position, photoelectrically converts the reflected light by an image sensor, and generates image data from the electric signal.

The image control unit 160 performs layout processing and rasterization processing of print data included in the print job or the like received by the communication unit 130, and generates bitmap image data.

The print job is a general term for print commands to the image forming apparatus 100, and includes print data and print settings. The print data is data of a document to be printed, and the print data may include various data such as image data, vector data, and text data. Specifically, the print data may be PDL (Page Description Language) data, PDF (Portable Document Format) data, or TIFF (Tagged Image File Format) data. The print setting is a setting relating to image formation on a sheet, and includes various settings such as the number of pages, the number of copies, a paper type, color or monochrome, and page layout.

The image forming unit 170 includes an image forming unit 40, a fixing unit 50, a paper feeding unit 60, and a paper transporting unit 70.

The image forming unit 40 includes image forming units 41Y, 41M, 41C, and 41K corresponding to toners of Y (yellow), M (magenta), C (cyan), and K (black), respectively. The image forming units 41Y, 41M, 41C, 41K form a toner image on the photosensitive drum through a process of charging, exposing, and developing based on the image data. The exposure is performed by scanning the photosensitive drum with a laser beam. Hereinafter, the scanning direction on the photosensitive drum by the laser light will be referred to as a main scanning direction, and the direction orthogonal to the main scanning direction will be referred to as a sub scanning direction. The toner images formed on the photoconductor drum are sequentially superposed on the intermediate transfer belt 42 and transferred onto the sheet 900 by the secondary transfer roller 43.

The fixing unit 50 has a heating roller 51 and a pressure roller 52, and heats and presses the paper 900 conveyed to the fixing nip of the rollers 51 and 52 to melt and fix the toner image on the paper 900 on the surface thereof. To do.

The sheet 900 on which the toner image has been fixed by the fixing unit 50 is discharged to the sheet discharge tray 190 as a printed matter (output matter).

The sheet feeding unit 60 has a plurality of sheet feeding trays 61 and 62, and sends out the sheets 900 accommodated in the sheet feeding trays 61 and 62 one by one to a downstream transport path.

The paper conveyance unit 70 has a plurality of conveyance rollers for conveying the paper 900, and conveys the paper 900 among the image forming unit 40, the fixing unit 50, and the paper feeding unit 60. The plurality of transport rollers include a registration roller 71 for correcting the inclination of the sheet 900 and a loop roller 72 for forming a predetermined amount of loops on the sheet 900. The paper transport unit 70 discharges the paper 900 on which an image has been formed to the paper discharge tray 90.

Details of the operation of the control unit 110 will be described.

FIG. 3 is a flowchart of the image data thinning processing. This flowchart can be executed by the control unit 110 according to a program stored in the storage unit 120. The image data is, for example, multi-valued image data in which the pixel value of each color has any value from 0 to 255. The image includes color and monochrome image data. The image data includes the image data generated by the image control unit 160 and the image data generated by the image reading unit 150. Hereinafter, the image based on the image data, which is the target of the thinning process, is also referred to as “target image”.

The control unit 110 divides the image data into a plurality of divided data (S101). That is, the control unit 110 divides the image data into a plurality of regions of an image based on the image data. The plurality of pieces of divided data are processed in parallel in steps S102 to S110. Hereinafter, in order to simplify the description, the divided images based on the divided data will also be referred to as target images.

FIG. 4 is a subroutine flowchart of step S101 of FIG. FIG. 5 is an explanatory diagram for explaining division of image data.

The control unit 110 calculates the size of the divided image based on the number of divisions set by the user (S201). In the example of FIG. 5, the size of the target image before division is 1500 pixels (horizontal)×2000 pixels (vertical) (hereinafter, the image size is described as “1500×2000”). When the number of divisions is 3, the image is divided into three divided images of sizes 1500×667, 1500×667, and 1500×666, for example. The division direction may be a sub-scanning direction (vertical) that is orthogonal to the predetermined direction.

The control unit 110 calculates the division position of the image (S202). In the example of FIG. 5, the division position is the position of 667 pixels and 1334 pixels in the coordinate of the image in the sub-scanning direction.

The control unit 110 divides the target image at the calculated division position (S203).

The control unit 110 generates image data (divided data) of the divided image with the margin portion added (S204). In the example of FIG. 5, the margin portion is made up of two pixels or the like in the sub-scanning direction. Therefore, the size of each divided image to which the margin part is added is 1500×671, 1500×671, 1500×670. The margin portion is added to the divided image so that the processing by the 3×3 filter in step S103 described below can be executed as the target pixel for the pixels at the upper and lower ends in the sub-scanning direction of the divided image. To do so. A margin portion may be added to the main scanning direction and the end portions (left and right ends) of the divided image in the main scanning direction.

Returning to FIG. 3, the description will be continued. In steps S102 and S103, the pixels of the target image are scanned in the main scanning direction (first direction), which is a predetermined direction, to detect the left edge of the object and the left side of the object, as described below. Replace the edge of. Objects include characters and graphics.

The control unit 110 detects the left edge of the object in the target image (S102). Specifically, the control unit 110 detects an edge pixel pair forming an edge of the object in the target image. The edge pixel pair includes an inner edge pixel (hereinafter, also referred to as “IE”) forming an outline of the object, and an outer edge pixel (hereinafter, also referred to as “OE”) adjacent to the inner edge pixel outside the object. It is a group of. As will be described below, in step S102, the edge pixel pair on the left side of the object is detected in the target image, and an attribute related to the edge of the object is added to each pixel.

FIG. 6 is a subroutine flowchart of step S102 of FIG.

The control unit 110 initializes the attributes of all the pixels of the target image to the attributes of external non-edge, and sets them as external non-edge pixels (hereinafter, also referred to as “ON”) (S301). Here, the external non-edge pixels are pixels outside the object and are pixels other than the external edge pixels, and the internal non-edge pixels (described later) are pixels other than the internal edge pixels inside the object. is there.

The control unit 110 uses a 3×1 Laplacian filter for performing a filtering process on a pixel value of three pixels including the target pixel and two pixels before and after the target pixel, in the main scanning of the target image based on the image data. By scanning in the direction, the convolution operation is performed on the image data. In other words, the 3×1 Laplacian filter is a filtering process for a pixel value of three pixels including a target pixel and two pixels adjacent to the target pixel in the main scanning direction and in a direction opposite to the main scanning direction. Is a filter to do. As a result, the control unit 110 calculates the edge value of the pixel of interest (S302). Hereinafter, the target pixel in the Laplacian filter for calculating the edge value is referred to as “edge detection target pixel”. Pixels adjacent to the edge detection target pixel in the direction opposite to the main scanning direction are scanned immediately before the edge detection target pixel by the Laplacian filter, and hence the pixel is hereinafter referred to as the “previous pixel”. A pixel adjacent to the edge-detected pixel of interest in the main scanning direction is scanned immediately after the edge-detected pixel of interest by the Laplacian filter, and hence the pixel is hereinafter referred to as an “immediate pixel”.

The convolution operation using the Laplacian filter is an operation for calculating the edge value of the pixel of interest for edge detection by the following equation (1).

Pixel value of immediately preceding pixel+pixel value of immediately following pixel−2×pixel value of target pixel for edge detection (1)
The control unit 110 determines whether the absolute value of the edge value of the edge detection target pixel is equal to or more than the threshold value (S303). The threshold value can be set to an appropriate value by experiment or the like, and can be set to 80, for example.

When the control unit 110 determines that the absolute value of the edge value of the edge detection target pixel is not greater than or equal to the threshold value (S303: NO), the process returns to step S302 and continues the processing.

When the control unit 110 determines that the absolute value of the edge value of the edge detection target pixel is equal to or larger than the threshold value (S303: YES), the edge detection target pixel is determined to be the edge of the object included in the target image (S304). When it is determined that the edge detection target pixel is the edge of the object included in the target image, it is determined whether the immediately preceding pixel is also an edge (S305).

If the immediately preceding pixel is not an edge (S305: NO), the control unit 110 returns to step S302 and continues the processing.

If the immediately preceding pixel is an edge (S305: YES), the control unit 110 determines that the set of the immediately preceding pixel and the edge detection target pixel is an edge pixel pair. Thereby, the edge pixel pair is detected.

Steps S301 to S305 can be executed for each color (Y (yellow), M (magenta), C (cyan), and K (black)). Here, the execution for each color includes the case where the object of the target image is a single color (for example, black) and is executed for the single color. Therefore, in step S302, the edge value is calculated for each color, and in step S303, it is determined whether the absolute value of the edge value is greater than or equal to the threshold value for each color. Therefore, a pixel pair adjacent to a pixel in which the absolute value of the edge value of at least one color is equal to or larger than the threshold value is detected as an edge pixel pair. Note that steps S301 to S305 may be executed only for a predetermined color (for example, cyan).

When the control unit 110 determines in step S305 that the immediately previous pixel is an edge, the control unit 110 calculates the L ^* values of the immediately previous pixel and the edge detection target pixel (S306). The L ^* value is the lightness in the CIE standard. Instead of L ^* , another value corresponding to the brightness may be calculated.

The control unit 110 determines whether the L ^* value of the immediately preceding pixel is larger than the edge detection target pixel (S307).

When the control unit 110 determines that the L ^* value of the immediately preceding pixel is larger than the edge detection target pixel (S307: YES), the control unit 110 determines the immediately previous pixel as OE and the edge detection target pixel as IE (S308), and proceeds to step S309. Execute.

When the control unit 110 determines that the L ^* value of the immediately preceding pixel is not larger than the edge detection target pixel (S307: NO), the control unit 110 determines that the previous pixel is IE and the edge detection target pixel is OE (S310), and step S311. To execute.

FIG. 7 is a subroutine flowchart of step S309 of FIG. FIG. 8 is an explanatory diagram for explaining the embedding process of the attribute of each pixel of the target image. As described above, the subroutine flowchart of FIG. 7 is executed when it is determined that the immediately preceding pixel is OE and the edge detection target pixel is IE.

The control unit 110 determines that the immediately preceding pixel is a pixel arranged in the main scanning direction with the edge detection target pixel and having a common coordinate in the sub scanning direction (a pixel in the same row as the edge detection target pixel on the target image). It is determined whether the pixel that has been determined to be an edge immediately before being detected as an edge (hereinafter, referred to as “pixel P”) is OE or IE, or whether there is no pixel P (S401).

When the pixel P is OE, the control unit 110 turns on all the pixels between the pixel P and the immediately preceding pixel (S402). In the example of FIG. 8, the pixel of the target image (image) and the attribute given to the pixel are shown. Pixels forming the object among the pixels of the target image are shown in gray color, and pixels of the same color are pixels forming the same object. In step S402, the attribute embedding process is performed in the section a shown in B of FIG. Specifically, the edge detection target pixel (shown by i) is determined to be IE and the immediately preceding pixel (shown as p) is determined to be OE in the section a, and it is determined to be an edge immediately before the immediately preceding pixel is detected as an edge. The pixel P (indicated by P) is OE. Therefore, an embedding process is performed to turn on the pixels between the OE that is the pixel P and the OE that is the immediately preceding pixel. In step S301, the attributes of all pixels are initialized and set to ON. Therefore, the embedding process of step S402 can be omitted.

When the pixel P is the IE, the control unit 110 sets only pixels adjacent to the pixel P in the main scanning direction as internal non-edge pixels (hereinafter, also referred to as “IN”) (S403). In the example of FIG. 8, the attribute embedding process performed in step S403 is the section b shown in B of FIG. Specifically, in the section b, the edge detection target pixel (indicated by i) is determined to be IE, the immediately preceding pixel (indicated by p) is determined to be OE, and the pixel P (indicated by P) is IE. For this reason, an embedding process is performed in which only pixels adjacent to the pixel P, which is an IE, in the main scanning direction are set to IN. Such embedding processing is performed when the target image has a multilayer structure in which another object is arranged on one object. Note that in step S403, all pixels between the pixel P and the immediately preceding pixel may be set to IN. The edge pixel pair including the pixel IE forming the pixel P forms a third edge pixel pair. The pixel IE forming the edge detection target pixel and the OE forming the immediately preceding pixel form a fourth edge pixel pair.

When there is no pixel P, the control unit 110 turns on all the pixels between the edge detection target pixel and the edge detection target pixel opposite to the main scanning direction (S404). .. In the example of FIG. 8, the attribute embedding process is performed in step S404 in the section c shown in A of FIG. Specifically, in the section c, it is determined that the pixel of interest for edge detection (indicated by i) is IE and the immediately preceding pixel (indicated by p) is OE, and the pixel P does not exist. For this reason, the edge detection target pixel is subjected to embedding processing in which the pixel between the edge portion in the direction opposite to the main scanning direction and the edge detection target pixel is turned on.

FIG. 9 is a subroutine flowchart of step S311 of FIG. As described above, the subroutine flowchart of FIG. 9 is executed when it is determined that the immediately preceding pixel is IE and the edge detection target pixel is OE.

The control unit 110 determines whether the pixel P has IE or OE or does not have the pixel P with respect to the pixel having the common coordinates in the main scanning direction with the edge detection target pixel (S501).

When the pixel P is IE, the control unit 110 sets all the pixels between the pixel P and the immediately preceding pixel to IN (S502). In the example of FIG. 8, the attribute embedding processing is performed in step S502 in the section d shown in A of FIG. Specifically, in the section d, it is determined that the target pixel for edge detection (indicated by i) is OE and the immediately preceding pixel (indicated by p) is IE, and it is determined that the pixel is an edge immediately before the preceding pixel is detected as an edge. The pixel P (denoted by P) is the IE. Therefore, an embedding process is performed in which a pixel between the IE that is the pixel P and the IE that is the immediately preceding pixel is set to IN.

When the pixel P is OE, the control unit 110 sets only the pixel adjacent to the immediately preceding pixel in the direction opposite to the main scanning direction to IN (S503). In the example of FIG. 8, the attribute embedding process is performed in step S503 in the section e shown in B of FIG. Specifically, in the section e, the edge detection target pixel (indicated by i) is determined to be OE, the immediately preceding pixel (indicated by p) is determined to be IE, and the pixel P (indicated by P) is OE. For this reason, the embedding process is performed on the immediately preceding pixel which is OE so that only the pixel adjacent in the opposite direction to the main scanning direction is IN. Such embedding processing is performed when the target image has a multilayer structure. Note that in step S503, all the pixels between the pixel P and the immediately preceding pixel may be set to IN. The edge pixel pair including the pixel OE forming the pixel P forms a first edge pixel pair. The pixel OE forming the edge detection target pixel and the IE forming the immediately preceding pixel form a second edge pixel pair.

If the pixel P is not present, the control unit 110 sets all the pixels between the edge portion in the opposite direction to the main scanning direction and the immediately preceding pixel to IN with respect to the edge detection target pixel (S504). In the example of FIG. 8, the attribute embedding process is performed in step S504 in the section f shown in C of FIG. Specifically, in the section f, it is determined that the pixel of interest for edge detection (shown by i) is OE and the immediately preceding pixel (shown by p) is IE, and the pixel P does not exist. Therefore, the edge detection target pixel is subjected to the embedding process in which the pixel between the end portion in the direction opposite to the main scanning direction and the immediately previous pixel IE is set to IN.

Returning to FIG. 6, the description will be continued. The control unit 110 determines whether the left edge detection processing has been completed for all pixels of the target image (S312). When the control unit 110 does not determine that the left edge detection processing has been completed for all pixels (S312: NO), the control unit 110 returns to step S302 and continues the processing. When the control unit 110 determines that the left edge detection processing has been completed for all pixels (S312: YES), the control unit 110 returns to the flowchart of FIG. 3 and executes the processing of step S103.

FIG. 10 is a subroutine flowchart of step S103 of FIG.

The control unit 110 scans each row from the first row to the last row in the main scanning direction, which is a predetermined direction, with each pixel as a pixel of interest, and confirms the attribute of each pixel (S601).

The control unit 110 determines whether the pixel of interest is IE (S602). When the control unit 110 determines that the target pixel is not the IE (S602: NO), the control unit 110 returns to step S601 and continues the processing.

When the control unit 110 determines that the pixel of interest is the IE (S602; YES), the total number of INs and IEs that are close to the pixel of interest (the total number of inners that are the pixels having the attribute inside the object). Is calculated (S603).

Steps S601 to S603 can be executed using a 3×3 filter that calculates the total number of IN and IE among the neighboring pixels that are close to the target pixel within a predetermined number of pixels, with the target pixel as the center. In the following, as an example, IN of eight adjacent pixels (hereinafter, also simply referred to as “adjacent pixels”) that are close to the central pixel of interest within one pixel number (that is, adjacent to the pixel of interest around the pixel of interest) It is assumed that steps S601 to S603 are executed using a 3×3 filter for calculating the total number of IEs and IEs.

The control unit 110 determines a replacement condition for replacing the left edge of the object based on the total number of INs and IEs of the adjacent pixels and the positional relationship between IN and IE of the adjacent pixels ( S604). Hereinafter, among the adjacent pixels, the IN and IE pixels are referred to as “adjacent inner pixels”. In addition, the total number of adjacent inner pixels is referred to as “the number of adjacent inner pixels”. Replacing the left edge of the object means replacing the pixel value of the pixel of interest with the pixel value of the pixel adjacent to the pixel of interest in the main scanning direction which is the predetermined direction in the opposite direction (left side). Hereinafter, it is also simply referred to as “replacement processing”.

11A to 11E are diagrams showing replacement conditions for replacing the left edge of the object. 11A to 11E, whether or not the pixel value of the target pixel can be replaced with the pixel value of the pixel adjacent to the target pixel in the opposite direction to the main scanning direction, which is the predetermined direction, for each adjacent inner pixel number. Are divided by the positional relationship between IN and IE, which are the inner inner pixels, and are shown together with the 3×3 filter. The central pixel (pixel indicated by “I”) of the 3×3 filter shown in FIGS. 11A to 11E is the target pixel, and the adjacent inner pixel is indicated by a white “1” on the black background. There is. Note that among the peripheral pixels, the pixels that are not the adjacent inner pixels are indicated by “0” on the white background. 11A to 11E, in the case where the pixel of interest cannot be IN, the combination of the pixel of interest and the adjacent inner pixel (the one with a black star mark at the lower left of the 3×3 filter (see FIG. 11C Etc.)) is also shown. Such a pixel of interest that is not IN is not a target for replacing the left edge (see step S602).

When the number of adjacent inner pixels as shown in FIG. 11A is 0, the pixel value of the target pixel is maintained without performing the replacement process. When the number of adjacent inner pixels is 0, the pixel of interest that is IE may be present as the isolated point of a character including the isolated point (for example, the characters “i” and “j”), but the replacement process is performed. This may cause garbled characters (for example, the points forming the character “i” disappear).

If the number of adjacent inner pixels is 1, and if the number of IN and IE pixels (including the pixel of interest) adjacent (further) to the adjacent inner pixel is three or more, the object replacement process is performed. On the other hand, in other cases, the replacement process is not performed. This means that when the number of adjacent inner pixels is 1 and the number of IN and IE pixels (including the pixel of interest) adjacent to the adjacent inner pixel is 2 or less, the adjacent inner pixel can exist as an isolated line, This is because by performing the replacement process, the isolated line that should exist may disappear.

As shown in FIGS. 11A to 11C, when the number of adjacent inner pixels is 2 to 4, when the adjacent inner pixels are adjacent to each other, the replacement process is performed. On the other hand, in other cases, the replacement process is not performed. This is because when the adjacent inner pixels are not adjacent to each other, the adjacent inner pixels often form a continuous line, but the continuous line may be divided by performing the replacement process.

When the number of adjacent inner pixels is 5 and 6, if at least one of the adjacent pixels other than the adjacent inner pixel is point-symmetric with respect to the pixel of interest, the replacement process is not performed. On the other hand, in other cases, the replacement process is performed. This is because when the pixels other than the proximity inner pixel among the proximity pixels are point-symmetric with respect to the pixel of interest, the proximity inner pixel often constitutes a connection point of a certain region, while the replacement processing is performed. By doing so, the connection point can be divided. If the positional relationship between IN and IE, which are the inner pixels close to each other, is shown in the broken line frame in FIGS. 11D and 11E, a defect that a blank character may be cut off by performing the replacement process may occur. There is. Therefore, when such a problem occurs, the replacement process does not have to be performed when the positional relationship between the adjacent inner pixels IN and IE in the broken line frame in FIGS. 11D and 11E is reached.

When the number of adjacent inner pixels is 7, the replacement process is not performed and the pixel value of the target pixel is maintained. This is because if the number of adjacent inner pixels is 7, the replacement process may often result in an inappropriate thinning process.

Note that the number of adjacent inner pixels does not become 8. This is because assuming that the number of adjacent inner pixels is 8, the target pixel cannot be IE, and the assumption of the adjacent inner pixels is lacking.

As a result of determining the replacement condition, if the control unit 110 does not determine to perform the replacement process (S605: NO), the control unit 110 executes the process of step S607.

When the control unit 110 determines to perform the replacement process (S605: YES), it replaces the pixel value of the target pixel with the pixel value of the immediately preceding pixel (S606). For example, when the target image is a color image, all pixel values of Y, M, C, and K of the target pixel are replaced with all pixel values of Y, M, C, and K of the target pixel. It

The control unit 110 determines whether or not the replacement processing has been completed for all pixels (S607), and if not completed (S607: NO), returns to step S601 and continues the processing.

When the control unit 110 determines that the replacement process has been completed for all pixels (S607: YES), the process ends.

In this way, by replacing the left edge of the object based on the number of adjacent inner pixels and the positional relationship between the adjacent inner pixels, it is possible to perform appropriate and high-speed thinning processing.

Returning to FIG. 3, the description will be continued. The control unit 110 detects the left edge (S102) and replaces the left edge (S103) with the predetermined direction as the main scanning direction, and then executes the predetermined direction in the sub-scanning direction (first As the two directions, the upper edge of the object is detected (S104) and the upper edge of the object is replaced (S105). As a result, the thinning processing on the upper side of the object is further executed, and the degree of thinning by the thinning processing increases. The processing in steps S104 and S105 is the same as the processing in steps S103 and S104, respectively, except that the predetermined direction (including the orientation of the Laplacian filter) is different, and thus the description thereof is omitted.

The control unit 110 determines whether the thinning process setting is set to “strong” (S106). The strength of the thinning process is set by the control unit 110 based on the selection of the strength of the thinning process input by the user on the operation display unit 140. The setting of the strength of the thinning process may be set in advance in the image forming apparatus 100 or may be set in the print job.

When the setting of the thinning process is not set to "strong" (that is, when it is set to "weak") (S106: NO), the control unit 110 ends the process.

When the setting of the thinning process is set to “strong” (S106: YES), the control unit 110 regards the predetermined direction as the opposite direction (third direction) to the main scanning direction, and the right edge of the object. Is detected (S107), and the right edge of the object is replaced (S108). After that, the control unit 110 sets the predetermined direction to the direction opposite to the sub-scanning direction (the fourth direction), and detects the lower edge of the object (S109) and replaces the lower edge of the object (S110). To do. By replacing the right edge of the object (S108), the thinning processing on the right side of the object is performed, and by replacing the lower edge of the object (S108), the thinning processing on the lower side of the object is performed. Thereby, the degree of thinning by the thinning processing can be further increased. The processes in steps S107 and S108 and the processes in steps S109 and S110 are the same as the processes in steps S103 and S104, respectively, except that the predetermined directions are different, and thus the description thereof is omitted.

Note that some steps may be omitted in the flowchart of FIG. 3 and other steps may be added. For example, step S101 may be omitted, and steps S102 to S110 may be executed without dividing the target image. Further, only steps S102 to S105 may be executed. Further, only steps S102 and S103, and steps S107 and S108 may be executed. Further, some of the steps may be executed simultaneously, or one step may be divided into a plurality of steps and executed. Also, the order of each step may be changed.

FIG. 12 is a diagram showing a result of the thinning process. FIG. 12A is a diagram showing the result of the thinning process for the target image of black characters (text) in comparison with the case where the thinning process is not performed. FIG. 12B is a diagram showing the result of the thinning process for the target image of the white characters, in comparison with the case where the thinning process is not performed. In FIG. 12, the result of thinning unprocessed, the result of thinning process of “weak” setting, and the result of thinning process of “strong” setting are shown by comparing the original image and the output image. ing. The original image is a target image before being formed by the image forming unit 170, and the output image is a target image formed on the sheet 900 by the image forming unit 170.

As shown in A of FIG. 12, in the original image, the line of the character is thinner in the image subjected to the thinning processing than in the image not subjected to the thinning processing. On the other hand, when comparing the original image and the output image, the output image has thicker character lines. By performing the thinning processing, it can be seen that the line thickness of the characters in the output image is brought closer to the original image that has not been thinned.

As shown in FIG. 12B, in the original image, the thinned image has thicker character lines than the image that has not been thinned. This is because the pixels with low lightness are determined to be inside the object (IE or the like), and thus the edge replacement process is performed on the black portion other than the character. On the other hand, when comparing the original image and the output image, the lines of the characters in the output image are thinner. By performing the thinning processing, it can be seen that the line thickness of the characters in the output image is brought closer to the original image that has not been thinned.

The embodiment described above has the following effects.

An attribute inside and outside the object is given to each pixel pair forming the edge of the object included in the image, and the pixel other than the pixel is determined to be the inside of the object based on the positional relationship between the pixels to which the attribute is given. Add the attributes in. Then, it is determined whether or not the pixel of interest is replaced with the pixel value of the pixel scanned immediately before the pixel of interest, based on the number and positional relationship of the pixels having the attribute in the object among the pixels adjacent to the pixel of interest. .. As a result, even if the attribute of each pixel of the image is not known, appropriate and high-speed thinning processing can be performed.

Further, the image data is color image data. As a result, it is possible to effectively and appropriately perform the thinning process on the color image data.

Further, a 3×1 Laplacian filter, which performs filtering processing on pixel values of three pixels including the edge detection target pixel and two pixels before and after the edge detection target pixel, is scanned in a predetermined direction to detect the edge detection target pixel. The edge value is calculated, and a pixel pair in which pixels whose absolute value of the edge value of at least one color is equal to or larger than the threshold is adjacent is detected as an edge pixel pair. Thereby, the edge pixel pair can be detected at high speed and with high accuracy.

Further, the brightness is calculated for each of the detected edge pixel pairs, the attribute of the inner edge is given to the pixel having the lower lightness, and the attribute of the outer edge is given to the pixel having the lower lightness. As a result, the attributes inside and outside the object can be added to the edge pixel pair at high speed and with high accuracy.

Further, each time an edge pixel pair is detected, an attribute is given to each pixel of the edge pixel pair, and the attribute first given after the attribute of the internal edge is given is the attribute of the internal edge, The internal non-edge attribute is added to all the pixels existing between the two internal edge pixels to which the internal edge attribute has been added to make the pixel an internal non-edge pixel. As a result, attributes can be added to pixels inside the object at high speed and with high accuracy.

Further, when no pixel of the edge pixel pair exists between the edge of the target image and the internal edge pixel, the attribute of the internal non-edge is given to the pixel between the edge and the internal edge pixel. To be internal non-edge pixels. As a result, the attribute can be added to the pixels inside the object arranged at the edge of the target image at high speed and with high accuracy.

Furthermore, after the external edge pixel of the first edge pixel pair appears, the first pixel that appears in the predetermined direction as a pixel forming the edge pixel pair is the second edge pixel different from the first edge pixel pair. In the case of the internal edge pixel of the pair, the internal non-edge attribute is given to the pixel adjacent to the internal edge pixel of the second edge pixel pair in the direction opposite to the predetermined direction to make the internal non-edge pixel. Then, after the internal edge pixel of the third edge pixel pair appears, the pixel that first appears in the predetermined direction as a pixel forming the edge pixel pair is a fourth edge pixel different from the third edge pixel pair. If the pixel is an external edge pixel of a pair, the pixel adjacent to the internal edge pixel of the third edge pixel pair in the predetermined direction is given an attribute of internal non-edge to be an internal non-edge pixel. This makes it possible to perform appropriate and high-speed thinning processing even on a target image having a multi-layered structure by overlapping a plurality of objects.

Furthermore, regarding the total number of internal edge pixels and internal non-edge pixels among the eight adjacent pixels adjacent to the pixel of interest, and the positional relationship between the internal edge pixels and the internal non-edge pixels among the eight adjacent pixels, Based on this, it is determined whether to replace the pixel value of the target pixel with the pixel value of the external edge pixel adjacent to the target pixel, which is scanned immediately before the target pixel is scanned. Thereby, the thinning process can be performed more appropriately according to the feature of the object.

Further, (1) when the total number is 0 or 7, (2) when the total number is 1 and the number of internal edge pixels and internal non-edge pixels among the eight pixels adjacent to eight adjacent pixels is When the added value is 2 or less, (3) when the total number is 2 and the pixels whose numbers are added as the total number are adjacent to each other, (4) when the total number is 3 and the total number is When the pixels to which the numbers are added are adjacent, (5) the total number is 4, and when the pixels to which the numbers are added as the total number are adjacent, (6) the total number is 5, Among the adjacent pixels, when a pixel that is neither an internal edge pixel nor an internal non-edge pixel exists in both upper and lower sides, both left and right sides, or both in an oblique direction with respect to the target pixel, and ( 7) The total number is 6, and among the adjacent pixels, a pixel that is neither an internal edge pixel nor an internal non-edge pixel is located above or below the target pixel, both to the left or right, or both in a diagonal direction. When it exists, in either case, it is determined that the pixel value of the target pixel is not replaced with the pixel value of the external edge pixel adjacent to the target pixel, which is scanned immediately before the target pixel is scanned. In other cases, it is determined that the pixel value of the target pixel is replaced with the pixel value of the external edge pixel that is scanned immediately before the target pixel and that is adjacent to the target pixel. As a result, it is possible to perform the thinning processing more appropriately and with high accuracy according to the characteristics of the object.

Further, if the selection of the strength of the thinning process is accepted, and if the selection of the weakness is accepted, the thinning process is performed with the predetermined direction as the first direction, and then the predetermined direction is orthogonal to the first direction. The thinning process is performed as the direction. When a strong selection is accepted, the thinning process is performed with the predetermined direction as the first direction, and then the thinning process is performed with the predetermined direction as the second direction, and the predetermined direction is set as the first direction. The thinning process is performed as a third direction that is the opposite direction to the one direction, and then the thinning process is performed as a fourth direction that is the opposite direction to the second direction. Thereby, it is possible to perform an appropriate thinning process according to the user's request.

Further, after performing the thinning process with the predetermined direction as the fifth direction, the thinning process is performed with the predetermined direction as a direction orthogonal to the fifth direction. As a result, it is possible to reduce the burden on the user regarding the setting of the thinning processing and to realize the appropriate thinning processing.

Further, after performing the thinning process with the predetermined direction as the sixth direction, the thinning process is performed with the predetermined direction as the direction opposite to the sixth direction. As a result, it is possible to reduce the burden on the user regarding the setting of the thinning processing and to realize the appropriate thinning processing.

Further, a plurality of divided data is generated by dividing the multivalued image data corresponding to a plurality of regions of an image based on the multivalued image data, and the thinning processing is performed in parallel on the plurality of divided data. I do. As a result, it is possible to further speed up the thinning process.

Further, the multi-valued image data is divided corresponding to a plurality of regions of the image based on the multi-valued image data, and a margin portion of 2 pixels or more is provided at upper and lower ends in the division direction of the image based on the divided data. The thinning processing is performed in parallel on a plurality of divided data corresponding to the divided images to which the added margins have been added. As a result, it is possible to further speed up and improve the accuracy of the thinning process.

The present invention is not limited to the above embodiments.

For example, in the embodiment, the eight adjacent pixels when the IE is the target pixel are the adjacent pixels, and based on the total number of IE and IN among the adjacent pixels and the positional relationship between the IE and IN, It is determined whether or not the pixel value of the target pixel is replaced with the pixel value of the OE adjacent to the target pixel, which is scanned immediately before the target pixel is scanned. However, the adjacent pixels may be nine or more pixels selected in ascending order of the distance to the pixel of interest.

Further, the setting of the thinning process does not have to be in two levels of strength and weakness, and may be in three levels of strength and weakness. In this case, when the medium setting is made, for example, the thinning processing in steps S101 to S108 can be executed.

Further, in the embodiment, the sheet is described as an example of the storage medium, but the recording medium is not limited to the sheet and may be a resin film or the like.

The present invention is also applicable to an inkjet image forming apparatus.

Further, in the embodiment, part or all of the processing executed by the program may be replaced with hardware such as a circuit and executed.

40 Imaging department,
50 fixing section,
60 paper feed section,
70 paper transport section,
100 image forming apparatus,
110 control unit,
120 storage unit,
130 Communication unit,
140 Operation display,
150 image reading unit,
160 image control unit,
170 image forming unit,
900 sheets.

Claims (17)

Scanning the multi-valued image data for each color in a predetermined direction in an image based on the multi-valued image data to detect an edge pixel pair forming an edge of an object;
Among the edge pixel pairs detected in the step (a), the pixels forming the outline of the object are given the attribute of the internal edge to be the internal edge pixels, and the pixels adjacent to the internal edge outside the object. A step (b) in which the attribute of the external edge is given to the external edge pixel, and
Based on the positional relationship between the internal edge pixel and the external edge pixel, for the pixel to which neither the internal edge attribute nor the external edge attribute is given in the step (b), A step (c) of judging whether the pixel is an internal pixel and giving an internal non-edge attribute to the pixel judged to be an internal pixel of the object to be an internal non-edge pixel;
The total number of the internal edge pixel and the internal non-edge pixel among the adjacent pixels that are close to each other within a predetermined number of pixels from the target pixel when the internal edge pixels are the target pixels, and the adjacent pixel The pixel value of the target pixel based on the positional relationship between the internal edge pixel and the internal non-edge pixel, and the pixel value of the pixel adjacent to the target pixel in the opposite direction to the predetermined direction. A step (d) of determining whether to replace with a value
An image processing method comprising: The image processing method according to claim 1, wherein the multi-valued image data is color image data. In the step (a), a 3×1 Laplacian filter that performs a filtering process on a pixel value of three pixels including an edge detection target pixel and two pixels before and after the edge detection target pixel is scanned in the predetermined direction. Then, the edge value of the edge detection target pixel is calculated, and a pixel pair in which at least one pixel whose absolute value of the edge value of one color is a threshold value or more is adjacent is detected as the edge pixel pair. 2. The image processing method described in 2. In the step (b), the brightness is calculated for each of the edge pixel pairs detected in the step (a), the attribute of the internal edge is given to the pixel having the lower brightness, and the pixel having the higher brightness is assigned to the pixel having the higher brightness. The image processing method according to claim 1, wherein the attribute of the external edge is added. The step (b) assigns the attribute to each pixel of the detected edge pixel pair every time the edge pixel pair is detected in the step (a),
In the step (c), in the step (b), if the attribute firstly given after the attribute of the internal edge is given is the attribute of the internal edge, the attribute of the internal edge is given. The image processing method according to claim 1, wherein the attribute of the internal non-edge is given to all the pixels existing between the two internal edge pixels to make the internal non-edge pixel. In the step (c), if no pixel of the edge pixel pair exists between the edge of the image and the internal edge pixel, the pixel between the edge of the image and the internal edge pixel is displayed. The image processing method according to claim 1, wherein the internal non-edge attribute is given to the internal non-edge pixel to obtain the internal non-edge pixel. The step (c) includes
After the external edge pixel of the first edge pixel pair appears, a second pixel that first appears in the predetermined direction as a pixel forming the edge pixel pair is different from the first edge pixel pair. In the case of the internal edge pixel of the edge pixel pair, the internal non-edge attribute is given to the pixel adjacent to the internal edge pixel of the second edge pixel pair in the opposite direction to the predetermined direction. Internal non-edge pixels,
After the appearance of the inner edge pixel of the third edge pixel pair, a pixel first appearing as a pixel forming the edge pixel pair in the predetermined direction is different from the third edge pixel pair in the fourth direction. If the pixel is the outer edge pixel of the edge pixel pair, the inner non-edge pixel is given the attribute of the inner non-edge to the pixel adjacent to the inner edge pixel of the third edge pixel pair in the predetermined direction. The image processing method according to any one of claims 1 to 6. In the step (d), the predetermined number of pixels is 1, the adjacent pixels are eight adjacent pixels, and in the step (d), the internal edge pixel and the internal non-pixel among the eight adjacent pixels are included. Based on the total number of edge pixels and the positional relationship between the internal edge pixel and the internal non-edge pixel among the eight adjacent pixels, the pixel value of the pixel of interest is set to the pixel of interest. The image processing method according to claim 1, wherein it is determined whether or not the pixel value of a pixel adjacent in the opposite direction to the predetermined direction is replaced. The step (d) includes
The total number and the positional relationship are
(1) When the total number is 0 or 7,
(2) When the total number is 1 and the value obtained by adding the numbers of the internal edge pixels and the internal non-edge pixels among the eight pixels adjacent to the eight adjacent pixels is 2 or less,
(3) When the total number is 2 and the pixels whose numbers are added as the total number are adjacent to each other,
(4) When the total number is 3 and the pixels whose numbers are added as the total number are adjacent to each other,
(5) When the total number is 4 and the pixels whose numbers are added as the total number are adjacent to each other,
(6) The total number is 5, and among the adjacent pixels, a pixel that is neither the internal edge pixel nor the internal non-edge pixel is above and below the attention pixel, both left and right, or diagonal. If present in both directions, and
(7) The total number is 6, and among the adjacent pixels, a pixel that is neither the internal edge pixel nor the internal non-edge pixel is both above and below the left and right, or diagonally with respect to the target pixel. If present in both directions,
In any of the above, it is determined that the pixel value of the target pixel is not replaced with the pixel value of the external edge pixel that is scanned immediately before the target pixel and that is adjacent to the target pixel.
When the total number and the positional relationship are none of (1) to (7), the pixel value of the target pixel is adjacent to the target pixel scanned immediately before the target pixel is scanned. The image processing method according to claim 8, wherein it is determined that the pixel value of the external edge pixel is replaced. The method further includes a step (e) of accepting selection of strength of thinning processing,
When the weak selection is accepted in the step (e), the predetermined direction is orthogonal to the first direction after performing the steps (a) to (d) with the predetermined direction as the first direction. Performing steps (a) to (d) as a second direction,
When a strong selection is accepted in the step (e), the steps (a) to (d) are performed with the predetermined direction as the first direction, and then the predetermined direction is set as the second direction. After performing steps (a) to (d) and further performing steps (a) to (d) with the predetermined direction as a third direction opposite to the first direction, the predetermined direction is changed. The image processing method according to claim 1, wherein the steps (a) to (d) are performed as a fourth direction which is an opposite direction to the second direction. The steps (a) to (d) are performed with the predetermined direction as a fifth direction, and then the steps (a) to (d) are performed with the predetermined direction as a direction orthogonal to the fifth direction. Item 10. The image processing method according to any one of Items 1 to 9. The steps (a) to (d) are performed with the predetermined direction as a sixth direction, and then the steps (a) to (d) are performed with the predetermined direction as an opposite direction to the sixth direction. Item 10. The image processing method according to any one of Items 1 to 9. The method further includes a step (f) of generating a plurality of divided data by dividing the multi-valued image data corresponding to a plurality of regions of an image based on the multi-valued image data,
The image processing method according to claim 1, wherein steps (a) to (d) are performed in parallel on the plurality of divided data. In the step (f), the multi-valued image data is divided corresponding to a plurality of regions of the image based on the multi-valued image data, and the image based on the divided data after the division is divided into upper and lower parts in the division direction. 14. The image processing method according to claim 13, wherein a margin portion of 2 pixels or more is added to an end portion, and the plurality of divided data corresponding to the divided images to which the margin portion is added are generated. The pixel of the pixel of interest when it is determined in the step (d) that the pixel value of the pixel of interest is to be replaced with the pixel value of a pixel adjacent to the pixel of interest in the opposite direction to the predetermined direction. The value is replaced with the pixel value of a pixel adjacent to the target pixel in the opposite direction to the predetermined direction, and the pixel value of the target pixel is opposite to the target pixel in the opposite direction to the predetermined direction. If it is not determined that the pixel value of the pixel adjacent to the pixel of interest is to be replaced with the pixel value of the pixel of interest, the pixel value of the pixel of interest is not replaced with the pixel value of the pixel adjacent to the pixel of interest in the direction opposite to the predetermined direction (g The image processing method according to claim 1, further comprising: A step (a) of scanning the multivalued image data for each color in a predetermined direction in an image based on the multivalued image data to detect edge pixel pairs forming an edge of an object;
Among the edge pixel pairs detected in the step (a), the pixels forming the outline of the object are given the attribute of the internal edge to be the internal edge pixels, and the pixels adjacent to the internal edge outside the object. A step (b) in which the attribute of the external edge is added to the external edge pixel, and
Based on the positional relationship between the internal edge pixel and the external edge pixel, for the pixel to which neither the internal edge attribute nor the external edge attribute has been given in the step (b), A step (c) of determining whether the pixel is an internal pixel and adding an attribute of internal non-edge to the pixel determined to be an internal pixel of the object to be an internal non-edge pixel;
The total number of the internal edge pixel and the internal non-edge pixel among the adjacent pixels that are close to each other within a predetermined number of pixels from the target pixel when the internal edge pixels are the target pixels, and the adjacent pixel The pixel value of the target pixel based on the positional relationship between the internal edge pixel and the internal non-edge pixel, and the pixel value of the pixel adjacent to the target pixel in the opposite direction to the predetermined direction. A procedure (d) for determining whether to replace with a value,
An image processing program for causing a computer to execute the processing including the above. A multi-valued image data, for each color, scanning in a predetermined direction in an image based on the multi-valued image data, a detection unit for detecting an edge pixel pair forming an edge of an object;
Of the edge pixel pairs detected by the detection unit, the pixels forming the outline of the object are given the attribute of the internal edge to be internal edge pixels, and the pixels adjacent to the internal edge outside the object are externally output. A first attribute assigning unit that assigns an edge attribute to an external edge pixel;
Based on the positional relationship between the internal edge pixel and the external edge pixel, for the pixel for which neither the internal edge attribute nor the external edge attribute has been assigned by the first attribute assigning unit, the object A second attribute assigning unit that determines whether the pixel is an internal non-edge pixel by assigning an internal non-edge attribute to the pixel determined to be an internal pixel of the object.
The total number of the internal edge pixel and the internal non-edge pixel among the adjacent pixels that are close to each other within a predetermined number of pixels from the target pixel when the internal edge pixels are the target pixels, and the adjacent pixel The pixel value of the target pixel based on the positional relationship between the internal edge pixel and the internal non-edge pixel, and the pixel value of the pixel adjacent to the target pixel in the opposite direction to the predetermined direction. A determination unit that determines whether to replace with a value,
An image processing apparatus having: