JP2005101895A - Image processor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To highly accurately discriminate the dot area in an original manuscript. <P>SOLUTION: A pixel for discriminating the dot (a discriminating pixel) which shows the extreme value of the density (a density peak or a density dip) in the prescribed region of the image of the original manuscript, is detected by a pixel detector 111 for detecting the discriminating pixel. An inspection region is successively set on the prescribed region so that each discriminating pixel detected by the pixel detector 111 for detecting the discriminating pixel is located at the reference position of the inspection region. A two-dimensional histogram (a vector histogram) shows the occurrence frequency of the other discriminating pixel to the discriminating pixel at the reference position on the inspection region, and is created by a histogram creating part 111. The distance between the discriminating pixel located at the shortest distance from the reference position and the reference position, and the occurrence frequency of the discriminating pixel are specified by using the two-dimensional histogram. The dot area in the prescribed region is discriminated by a dot discriminating part 102 on the basis of the specified distance and occurrence frequency. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an image processing apparatus mounted on a copying machine or the like, and more particularly to an image processing apparatus having a function of detecting a halftone dot region in a document image.

Conventionally, after detecting a density peak (peak component) or a density dip (dip component) in image data of a document as a technique often used for detecting a halftone dot region on a document on which a halftone image is printed (halftone document) In this image, there is a method of determining an area having a large number of pixels indicating the density peak or density dip as a halftone dot area (for example, Patent Document 1).
JP-A-11-266364

  However, for an original on which an image or the like in which fine characters are densely printed is printed, the pixel indicating the density peak or the density dip (hereinafter, the pixel indicating the density peak or the density dip in the original image used for halftone dot discrimination). If the halftone dot area is determined based on the number of pixels (which is called a discrimination pixel), the area where the fine characters are dense may be erroneously determined as a halftone dot area. On the other hand, there is a case where a determination omission occurs such that an area to be determined as a halftone dot area is not determined as a halftone dot area.

  The present invention has been made in view of the above circumstances, and an object thereof is to provide an image processing apparatus capable of accurately determining a halftone dot region in a document.

  The invention according to claim 1 is an image acquisition unit that acquires a document image, a detection unit that detects a discrimination pixel having an extreme value of density in a predetermined region of the document image acquired by the image acquisition unit, and the detection And a discrimination means for discriminating a halftone dot area in the predetermined area based on a positional relationship between the discrimination pixels detected by the means on a two-dimensional plane and a frequency of occurrence of the positional relation. Device.

  According to a second aspect of the present invention, in the image processing apparatus according to the first aspect, the determination unit is arranged on the predetermined region so that each determination pixel detected by the detection unit is positioned at a reference position of the inspection region. And creating means for creating a two-dimensional histogram representing the frequency of occurrence of other discrimination pixels with respect to a reference position discrimination pixel on the inspection area, and a two-dimensional histogram created by the creation means. Using the distance between the discrimination pixel located at the shortest distance from the reference position and the occurrence frequency of the discrimination pixel, and a halftone dot in the predetermined area based on the identified distance and occurrence frequency And halftone dot discrimination means for discriminating the region.

  According to a third aspect of the present invention, in the image processing apparatus according to the second aspect, the halftone dot determining unit includes a maximum frequency detecting unit that detects a maximum frequency in the two-dimensional histogram, an origin and a maximum in the two-dimensional histogram. A distance calculating means for calculating the distance between the coordinates of the frequency and a ratio calculating means for calculating a ratio of the maximum frequency to the total frequency obtained by summing up the frequencies in the two-dimensional histogram, and the maximum frequency detecting means The halftone dot region in the predetermined region is determined using information on the detected maximum frequency, the distance calculated by the distance calculating unit, and the ratio calculated by the ratio calculating unit.

  According to a fourth aspect of the present invention, in the image processing apparatus according to the second aspect, the halftone dot discriminating means includes a maximum frequency detecting means for detecting a maximum frequency in the two-dimensional histogram, an origin and a maximum in the two-dimensional histogram. A distance calculating means for calculating a distance between the coordinate positions of the frequencies and a total frequency obtained by summing the frequencies at the coordinate positions where the distance from the origin in the two-dimensional histogram is in a range of a predetermined value to a predetermined value. A total frequency calculation means, wherein the halftone dot area in the predetermined area is determined using the distance calculated by the distance calculation means and the total frequency information calculated by the total frequency calculation means. To do.

  According to a fifth aspect of the present invention, in the image processing apparatus according to any one of the first to fourth aspects, the determination unit divides the predetermined area into a plurality of determination areas, and a dot area is determined for each determination area. It is characterized by discriminating.

According to the first aspect of the present invention, a document image is acquired by the image acquisition unit, and a discrimination pixel having an extreme value of density in a predetermined region of the document image acquired by the image acquisition unit is detected by the detection unit. Then, based on the positional relationship between the determination pixels detected by the detection unit on the two-dimensional plane and the occurrence frequency of the positional relationship, the halftone dot region in the predetermined region is determined by the determination unit. As described above, halftone dot discrimination is performed based on the positional relationship between the discrimination pixels on the two-dimensional plane and the frequency of occurrence of the positional relationship, so that the halftone dot region in the document can be accurately determined. .

  According to the second aspect of the present invention, the inspection unit sequentially sets the inspection region on the predetermined region so that each of the determination pixels detected by the detection unit is located at the reference position of the inspection region. Creating means for creating a two-dimensional histogram representing the frequency of occurrence of other discrimination pixels with respect to a reference position discrimination pixel in the image, and using the two-dimensional histogram created by the creation means to determine the shortest distance from the reference position And a halftone dot discriminating unit that identifies the distance between the pixel for use and the reference position and the occurrence frequency of the discrimination pixel and discriminates a halftone dot area in the predetermined area based on the specified distance and occurrence frequency. In this way, a two-dimensional histogram representing the frequency of occurrence of other discrimination pixels with respect to the reference position discrimination pixels on the inspection area is created, and halftone dot discrimination is performed based on the two-dimensional histogram. It is possible to easily determine the point area.

  According to the invention described in claim 3, the halftone dot discriminating means calculates the distance between the maximum frequency detecting means for detecting the maximum frequency in the two-dimensional histogram and the origin and the coordinate position of the maximum frequency in the two-dimensional histogram. And a ratio calculation means for calculating the ratio of the maximum frequency to the total frequency obtained by summing up the frequencies in the two-dimensional histogram. The maximum frequency detected by the maximum frequency detection means is calculated by the distance calculation means. The halftone dot area in the predetermined area is discriminated by the halftone dot discriminating means using the calculated distance and the ratio information calculated by the ratio calculating means. Therefore, it is possible to easily determine the halftone dot region based on the two-dimensional histogram.

  According to the invention described in claim 4, the halftone dot discriminating means calculates the distance between the maximum frequency detecting means for detecting the maximum frequency in the two-dimensional histogram and the coordinate position of the maximum frequency in the two-dimensional histogram. A distance calculation means for calculating the total frequency, and a total frequency calculation means for calculating the total frequency obtained by summing the frequencies in the coordinate position where the distance from the origin in the two-dimensional histogram is within a predetermined value and a predetermined value or less. The halftone dot area in the predetermined area is discriminated by the halftone dot discriminating means by using the distance calculated by the means and the information on the total frequency calculated by the total frequency calculating means. Therefore, it is possible to easily determine the halftone dot region based on the two-dimensional histogram.

According to the invention described in claim 5, the predetermined area is divided into a plurality of determination areas by the determination means, and a halftone dot area is determined for each determination area. As a result, the number of times of halftone dot discrimination for an original image increases, and as a result, the halftone dot region of the original can be more accurately discriminated.

  A copying machine as an example of an image processing apparatus according to the present invention will be described below with reference to the drawings. In addition, the structure which attached | subjected the same code | symbol in each figure has shown that it is the same structure.

(First embodiment)
FIG. 1 is a cross-sectional view schematically showing an internal configuration of a copying machine 1 which is an example of an image processing apparatus according to a first embodiment of the present invention. The copying machine 1 is disposed above the document reading unit 5, the main unit 2, the stack tray 3 disposed on the left side of the main unit 2, the document reading unit 5 disposed on the top of the main unit 2. And a document feeding unit 6 provided. Further, a start key 471 for a user to input a print execution instruction, a numeric keypad 472 for inputting the number of copies to be printed, and operations for inputting settings for various copying operations, etc. An operation unit 47 is provided that includes a display 473 (display) including a liquid crystal display (LCD) on which guide information and the like are displayed and various operation buttons for inputting various operation commands are displayed. It has been.

  The document reading section 5 includes a scanner 51 including a CCD (Charge Coupled Device) sensor and an exposure lamp, a document table 52 (platen glass) made of a transparent member such as glass, and a document reading slit 53. The scanner 51 is configured to be movable by a drive unit (not shown). When reading a document placed on the document table 52, the scanner 51 is moved to a position facing the document table 52, and an image acquired while scanning the document image. The data is output to the control unit 10 (or the image memory 7, the HDD 8, or the image processing unit 11) described later. The scanner 51 is moved to a position facing the document reading slit 53 when reading the document conveyed by the document feeding unit 6, and the document feeding operation is performed by the document feeding unit 6 through the document reading slit 53. The image of the document is acquired in synchronization with the image data, and image data for the image is output to the control unit 10.

  The document feeding unit 6 includes a document placing unit 61 for placing a document, a document discharging unit 62 for discharging a document after image reading, and a document placed on the document placing unit 61. A document transport mechanism 63 including a feed roller, a transport roller, and the like for feeding the paper one by one in order and transporting it to a position facing the document reading slit 53 and discharging it to the document discharge section 62 is provided. Further, the document feeding unit 6 is configured to be retractable, and the read document can be placed on the upper surface of the document table 52 by lifting the document table 52 upward so as to open the upper surface of the document table 52. It is configured.

The main body 2 includes a plurality of paper feed cassettes 461 that store papers of different sizes, a paper feed roller 462 that feeds the papers one by one from the paper feed cassette 461 and transports them to the recording unit 40 described later, and a paper feed cassette A recording unit 40 that forms a monochrome image or a color image on the sheet conveyed from 461 is provided.

  The recording unit 40 outputs a laser beam based on the image data acquired by the scanner 51 to expose the photosensitive drum 43, and forms an electrostatic latent image on the surface of the photosensitive drum 43. An image forming unit 44 that forms toner images of each color of cyan (C), magenta (M), yellow (Y), and black (K) on the photosensitive drum 43 based on the electrostatic latent image, and a photosensitive member A transfer unit 41 that transfers the toner image on the drum 43 to the paper, a fixing unit 45 that heats the paper on which the toner image is transferred and fixes the toner image on the paper, and a paper conveyance path in the recording unit 40 are provided. A paper transport device 46 that transports the paper by the transport rollers and the like and discharges the paper to the stack tray 3 or the discharge tray 48. The toner is supplied to each of the cyan, magenta, yellow and black colors from a toner supply container (toner cartridge) (not shown).

  FIG. 2 is a block diagram showing a schematic configuration of the copying machine 1 shown in FIG. The copying machine 1 includes a control unit 10 that controls operation of the entire apparatus. The control unit 10 includes a document reading unit 5 including a scanner 51 and the like, a document feeding unit 6 including a document transport mechanism 63, and an image. The recording unit 40 including the forming unit 44, the operation key 47 such as the start key 471 and the numeric keypad 472, the operation unit 47 including the display 473, the image memory 7, the HDD 8, the network I / F unit 9, and the image processing unit 11 are connected. Has been.

  The image memory 7 stores image data of a document (for example, a halftone document) read by the document reading unit 5 or image data transmitted from an external device (not shown) via a network I / F unit 9 described later. It is a memory that stores temporarily.

  An HDD (Hard Disk Drive) 8 is a storage device that stores image data of a document image read by the document reading unit 5, image data transmitted from an external device, an output format set in the image data, and the like. It is.

  The network I / F unit 9 uses a network interface (for example, 10 / 100Base-TX) or the like to transmit and receive various data to and from an external device connected via a network such as a LAN.

  The image processing unit 11 performs various image processes on a document image (image data) obtained by reading a document by the document reading unit 5. In the image processing unit 11, for example, A / D conversion of image data is performed on a document image read by the document reading unit 5, and the various image processes are performed using the A / D converted image data. The image processing unit 11 includes a discrimination pixel detection unit 111.

  The discrimination pixel detection unit 111 detects discrimination pixels (discrimination pixels 303 shown in FIG. 3 to be described later) that are extreme values of density (density peak or density dip) in the document image.

  The control unit 10 includes a ROM (Read Only Memory) that stores a control program of the copying machine 1, a RAM (Random Access Memory) that temporarily stores data, a microcomputer that reads and executes a control program from the ROM, and the like. The processing for controlling the entire apparatus is executed in accordance with the instruction information input from the operation unit 47 and detection signals from various sensors provided in various places of the apparatus. The control unit 10 includes a histogram creation unit 101, a halftone discrimination unit 102, and a discrimination target area setting unit 103.

  The histogram creation unit 101 has a two-dimensional histogram (for example, a vector histogram 501 described later) having information on the positional relationship between the determination pixels detected by the determination pixel detection unit 111 on the two-dimensional plane and the occurrence frequency of the positional relationship. 901).

  Here, the creation of a vector histogram based on the document image discrimination pixels will be described with reference to FIG. An area denoted by reference numeral 301 indicates a predetermined area (predetermined area 301) in an original image on which image processing related to detection of a density peak or density dip has been performed in the image processing unit 11 (determination pixel detection unit 111). Pixel 302. The predetermined area 301 is an area in which an inspection area 305 described later moves (is set). A black pixel denoted by reference numeral 303 indicates a discrimination pixel (discrimination pixel 303) detected by the discrimination pixel detection unit 111. The predetermined area 301 shows a document image when it is read at a resolution of, for example, 600 dpi, and the number of lines composed of a plurality of determination pixels 303 in the predetermined area 301, that is, the so-called halftone dot line number, for example, 120 lines per inch. (The distance between the discrimination pixels 303 is 5 pixels in length) (see the distance between dots (discrimination pixels 303) with respect to the number of halftone lines at a resolution of 600 dpi shown in FIG. 12).

  An area denoted by reference numeral 304 is an area (consisting of pixels of M rows × N columns) of a predetermined size within the predetermined area 301 (hereinafter referred to as a dot area by creating a vector histogram to determine whether it is a halftone dot area) , Referred to as a discrimination target area 304). Assuming that the coordinate axes for the predetermined area 301 are XY coordinate axes as shown in the figure, here, the length of the vertical and horizontal sides of the determination target area 304 is, for example, 16 lines (16 Pixels), a rectangular matrix region having a length of, for example, 64 pixels in the X-axis direction. However, the determination target area 304 may not be the area composed of 16 lines × 64 pixels, for example, may be an area composed of 64 lines × 16 pixels, or a rectangular matrix area or a square matrix of other sizes. It may be a region.

  A so-called square matrix inspection area 305 surrounded by double lines in the figure, each having a length and width of 8 lines and 8 pixels in length, corresponds to a certain discrimination pixel 303 in the discrimination target area 304. The position of another discrimination pixel 303 (the other discrimination pixel 303 includes the discrimination pixel 303 in an area other than the discrimination target area 304 in the predetermined area 301), that is, the positional relationship between the discrimination pixels 303; And an area for performing an inspection relating to the occurrence frequency (frequency described later) of the positional relationship. However, the length (number of pixels) of the vertical and horizontal sides of the inspection region 305 is not limited to this, and may be a so-called rectangular matrix having different vertical and horizontal sides.

  The diagram indicated by reference numeral 306 shows the inspection area 305 written out for convenience of explanation. The position of a pixel at one corner in the inspection area 305 indicates a positional relationship between the respective determination pixels 303 and a position serving as a reference (base point) for detecting the occurrence frequency (hereinafter, this pixel). Is referred to as a reference position 307). However, the reference position 307 in the inspection area 305 may be any position in the inspection area 305 including other corners. However, in order to correspond to the origin position of the vector histogram described later, the reference numeral 306 is illustrated. The pixel positions at the corners as shown are preferred.

  The histogram creation unit 101 sequentially sets the inspection region 305 on the predetermined region 301 so that each determination pixel 303 detected by the determination pixel detection unit 111 is positioned at the reference position 307 of the inspection region 305, and this inspection region A vector histogram representing the frequency of occurrence of other discrimination pixels 303 with respect to the discrimination pixel 303 at the reference position 307 on 305 is created. When the inspection area 305 is sequentially set on the predetermined area 301, the inspection area 305 is moved one pixel at a time along the pixels of the predetermined area 301 in a predetermined direction (for example, the arrow direction indicated by reference numeral 308 in FIG. 3). A vector histogram is created based on the positional relationship and occurrence frequency information of each discrimination pixel 303 existing in the inspection region 305 at the position.

  The histogram creation unit 101 includes a match determination unit 1011, a shortest position detection unit 1012, and an integration unit 1013. The coincidence determination unit 1011 moves the reference position 307 in the inspection area 305 one pixel at a time along the pixels in the determination target area 304 along with the movement of the inspection area 305, and the reference position 307 becomes the determination pixel. It is determined whether or not the position 303 is reached, that is, whether or not the reference position 307 matches the position of the determination pixel 303.

  The movement of the reference position 307 is performed for all pixels (all regions) in the determination target region 304. In this case, the movement of the reference position 307 starts from, for example, an end (corner) pixel (referred to as a first pixel) indicated by reference numeral 311 in the determination target region 304, and the pixels 312, 313,. When the position of the pixel 314 (the 64th pixel) is reached (when the inspection of the first line 315 is completed), the process proceeds to the second line 316 and the second Move from the position of one pixel to the position of the 64th pixel. Similarly, the third line 317,..., And the sixteenth line 318 are sequentially shifted. In this way, the reference position 307 is set (moved) for all the pixels in the determination target region 304.

  As shown in FIG. 3, the predetermined area 301 includes a determination target area 304 and an outer peripheral area on one side of the determination target area 304, that is, seven lines in the Y-axis direction and seven pixels in the X-axis direction. This area is an area that is combined with the area. The area corresponding to 7 lines in the Y-axis direction and 7 pixels in the X-axis direction is the reference position when the reference position 307 moves in the determination target area 304. This is an area where the inspection area 305 including 307 protrudes. For example, if the inspection area 305 moves to the position indicated by reference numeral 319 as the reference position 307 moves, the inspection area 305 protrudes from the line position of the 16th line 318 by 7 lines in the Y-axis direction. The same applies to the region for seven pixels in the X-axis direction.

  When the coincidence determination unit 1011 detects the coincidence between the reference position 307 and the position of the determination pixel 303, the shortest position detection unit 1012 and the other pixels existing in the inspection region 305 and the determination pixel 303 at the reference position 307 The distance to each of the determination pixels 303 is calculated, and based on the result, the determination pixel 303 at the shortest distance from the reference position 307 is detected. For example, assuming that the pixels at the positions indicated by reference numerals 309 and 310 in the inspection area 305 indicated by reference numeral 306 are the determination pixels 303, the determination pixel 303 at the position indicated by reference numeral 310 is located at the shortest distance from the reference position 307. This is the discrimination pixel 303 in FIG.

The integration unit 1013 is detected by the shortest position detection unit 1012 every time the inspection region 305 is set at a predetermined position on the predetermined region 301 (each time the reference position 307 moves on each pixel of the determination target region 304). The number of appearances of the discrimination pixel 303 at the shortest distance from the discrimination pixel 303 located at the reference position 307 is integrated (counted). The integrated value obtained by the integration by the integration unit 1013 is a frequency, and a vector histogram as shown in FIG. 4 is created using the frequency information, for example.

  As shown in FIG. 4, in the vector histogram 401, the values of the coordinate axes of the vertical axis (Y axis) and the horizontal axis (X axis) are 8 rows (8 lines) and 8 columns (8 pixels) of the inspection area 305, respectively. A pixel corresponding to the position of the pixel and located at the position indicated by reference numeral 402 where the values of the X coordinate and the Y coordinate are zero (hereinafter, this pixel is referred to as the origin) corresponds to the reference position 307 in the inspection region 305. In addition, the integrated value (frequency) is a so-called two-dimensional histogram that is distributed in a two-dimensional coordinate plane having XY axes.

  The frequency “42” at the position indicated by reference numeral 403 in the vector histogram 401 is the discrimination pixel 303 that has become the reference position 307 when the reference position 307 is moved over the entire discrimination target area 304 in FIG. This indicates that the determination pixel 303 (in this case, the pixel indicated by reference numeral 310 when viewed from the reference position 307) at the position having the shortest distance from the terminal appears 42 times. However, since the respective discrimination pixels 303 shown in the predetermined area 301 in this case are regularly arranged (a line formed by a halftone dot is formed), as seen from the position of the reference position 307 as described above. This is a result of appearing 42 times at the same position.

  Each frequency distributed in the coordinate plane is information on “direction” (coordinate position) and “size” (distance from the origin 402) when viewed from the origin (origin 402) indicated by reference numeral 402. Therefore, the frequency is regarded as a vector and is referred to as a vector histogram.

  The halftone dot discrimination unit 102 uses the vector histogram created by the histogram creation unit 101 to determine the distance between the discrimination pixel 303 located at the shortest distance from the reference position 307 and the reference position 307, and the discrimination pixel 303. The occurrence frequency is specified, and the dot area in the predetermined area 301 is determined based on the specified distance and the occurrence frequency. The halftone dot determination unit 102 includes a maximum value detection unit 1021, a distance calculation unit 1022, and a ratio calculation unit 1023.

  Here, for example, using a vector histogram 501 shown in FIG. 5 created by the histogram creation unit 101, a maximum value detection unit 1021, a distance calculation unit 1022, a ratio calculation unit 1023, and a halftone dot discrimination unit 102 including these. Discrimination of a halftone dot region by means of will be described below.

  The maximum value detection unit 1021 represents each frequency in the vector histogram created by the histogram creation unit 101, that is, the maximum value of the frequencies obtained by the integration by the integration unit 1013 (hereinafter, the frequency having the maximum value). Is called the maximum frequency). For example, the maximum frequency in the vector histogram 501 detected by the maximum value detection unit 1021 is the frequency “26” at the position indicated by reference numeral 502.

The distance calculation unit 1022 calculates the distance between the position of the maximum frequency detected by the maximum value detection unit 1021 and the origin of the vector histogram (corresponding to the reference position 307). For example, in the vector histogram 501, the distance calculation unit 1022 calculates the distance between the origin 503 and the maximum frequency “26”. This distance corresponds to the distance between the center points of the pixel at the origin and the pixel at the maximum frequency position in the vector histogram, and can be calculated from the Pythagorean theorem based on the coordinate value of each position. Good. For example, the length between the X coordinates at the origin 503 whose XY coordinates are represented by (0, 0) and the maximum frequency “26” whose XY coordinates are represented by (1, 4) is 1 (for one pixel). Since the length between the Y coordinates is 4 (for 4 pixels), if the distance to be calculated is L, the value of L can be calculated from the above formula of L ² = 1 ² +4 ² by the above 4.12. It is calculated as 3rd place rounded off).

  FIG. 11 shows a table 550 that summarizes the distance between the origin of the vector histogram and the positions of the frequencies distributed in the vector histogram. Such a table 550 is stored in advance in the distance calculation unit 1022 or the like. The distance value may be acquired using this table 550 as necessary. In this case, the distance between the origin 503 and the maximum frequency “26” is obtained as “4.12” from the position information indicated by the reference numeral 551 in the table 550.

  The ratio calculation unit 1023 calculates a ratio (percentage) of the maximum frequency with respect to the total frequency obtained by adding the frequencies distributed in the vector histogram. For example, in the vector histogram 501, since the total frequency is “53” and the maximum frequency is “26”, the ratio to be calculated is about 49% from the formula of (“26” ÷ “53”) × 100. .

The halftone dot determination unit 102 includes a maximum frequency value obtained by the maximum value detection unit 1021, the distance calculation unit 1022, and the ratio calculation unit 1023, the distance between the origin and the maximum frequency, and the ratio of the maximum frequency to the total frequency. Based on this information, it is determined whether or not the determination target area 304 is a halftone dot area. Specifically, if the following three conditions (1) to (3) are satisfied, it is determined that the partial area in the determination target area 304 is a halftone dot area; It is determined that it is not a point area.
(1) Maximum value of frequency in vector histogram> 15
(2) Distance between origin and maximum frequency in vector histogram <5.0
(3) Ratio of maximum frequency to total frequency in vector histogram> 40%

  For the vector histogram 501 shown in FIG. 5, the maximum value is “26” (> 15), the distance between the origin and the maximum frequency is “4.12” (<5.0), and the maximum for the total frequency. Since the frequency ratio is “49%” (> 40%), which satisfies the above three conditions, it is determined that the partial region of the determination target region 304 is a halftone dot region.

The above three conditions are set so that a halftone dot when the number of halftone lines at a resolution of 600 dpi is 133 lines or more is determined as a halftone dot, and a case where it is 120 lines or less is not determined as a halftone dot. Corresponds to a halftone dot (halftone dot image) of 150 lines (screen angle 75 °) (refer to FIG. 12 for the number of halftone lines). Also, the shaded area in the vector histogram 501 indicates an area having a distance from the origin 503 of less than 5.0.

  By the way, the partial area is an area that reflects the result of halftone dot discrimination in the predetermined area 301. In this case, the partial area is one area obtained by dividing the discrimination target area 304 into a plurality of partial areas. . This reflection will be described with reference to FIG. 3. A region 320 indicated by hatching in the determination target region 304 is a partial region (hereinafter referred to as a reflection region 320). For example, when the vector histogram 501 created for the image satisfies a condition for determining a halftone dot (the above conditions (1) to (3)), the reflection area 320 is determined to be a halftone dot area ( If the vector histogram 501 does not satisfy the condition for determining a halftone dot, it is determined (determined) that the reflection area 320 is not a halftone dot area.

  The reflection area 320 is an area at one end in the X-axis direction among areas obtained by dividing the determination target area 304 by a predetermined number (for example, four equal parts) in the X-axis direction. However, the size of the reflection area 320 may not be the size of 16 lines × 16 pixels divided into four equal parts, but may be a partial area having a size of 16 lines × 8 pixels or 16 lines × 32 pixels, for example. In this case, the smaller the size of the reflection area 320 with respect to the determination target area 304 (predetermined area 301), the greater the number of vector histogram creations, that is, the number of halftone dot determinations for the predetermined area 301. The accuracy of halftone dot region discrimination with respect to the predetermined region 301 can be further increased. In other words, the halftone dot determination result is not reflected on the entire determination target area 304 in the predetermined area 301, and the halftone dot determination result is applied to the reflection area 320 having a size smaller than the size of the determination target area 304. By reflecting, it is possible to reduce the probability that the entire discrimination target area 304 is a halftone dot area (misidentification), so that the misclassification area can be narrowed. The accuracy can be further increased.

  The discrimination target area setting unit 103 sequentially sets the area (the discrimination target area 304) where the reference position 307 of the inspection area 305 moves in the predetermined area 301 every time the discrimination result for the reflection area 320 is reflected. is there. For example, when the result of halftone dot discrimination by the halftone dot discrimination unit 102 is reflected in the reflection area 320, the discrimination target area setting unit 103 sets the next discrimination target area 304 to a position adjacent to the reflection area 320, that is, for example, It is set to a position translated from the position of the discrimination target region 304 shown in FIG. 3 by 16 pixels in the X-axis direction (the length of the reflection region 320 in the X-axis direction). When the halftone dot determination for the next determination target region 304 and the reflection of the determination result to the reflection region 320 are completed, the determination target region 304 is further moved to the next position. Thereafter, the same operation is repeated over the entire predetermined area 301.

  The movement to the next position of the discrimination target area 304 shown in FIG. 3 is not limited to the parallel movement in the X-axis direction, for example, 16 lines in the Y-axis direction (the length of the reflection area 320 in the Y-axis direction). It may be a parallel movement, or may be a movement that is alternately (or irregularly) translated in the X-axis direction and the Y-axis direction.

  In addition, the reflection of the determination result in the reflection area 320 over the entire predetermined area 301 causes the remaining areas other than the reflection areas 320 to reflect the determination result (for example, near the end of the predetermined area 301). If the area is smaller than the size of the discrimination target area 304 and the area of the discrimination target area 304 (16 lines × 64 pixels in the case of FIG. 3) cannot be set, a vector histogram is created for the remaining areas. However, it may be configured to perform halftone dot discrimination for the remaining area (this remaining area corresponds to the reflection area 320) based on this vector histogram.

  FIG. 6 is a flowchart showing an example of an operation related to halftone dot discrimination for a document image according to the first embodiment. First, a document image is acquired by reading a document (half-tone document) by the document reading unit 5 (step S1). The discrimination pixel detection unit 111 detects the discrimination pixel 303 from the original image (the predetermined region 301 in the original image) (step S2). Then, the discrimination target area 304 in the document image is set by the discrimination target area setting unit 103 (step S3), and the histogram creation unit 101 creates a vector histogram (for example, the vector histogram 501) for the discrimination target area 304 (step S3). S4).

  Next, the maximum frequency (“26”) in the vector histogram 501 is detected by the maximum value detection unit 1021 (step S5), and the distance between the origin 503 and the position of the maximum frequency is calculated by the distance calculation unit 1022 ( In step S6), the ratio of the maximum frequency to the total frequency is calculated by the ratio calculation unit 1023 (step S7). Then, based on the maximum value, distance, and ratio information obtained by the maximum value detection unit 1021, the distance calculation unit 1022, and the ratio calculation unit 1023, the halftone dot determination unit 102 sets the reflection area 320 in the determination target area 304 to the network. It is determined whether or not it is a point area (step S8).

  When the reflection of the halftone dot discrimination result to the reflection area 320 is not completed over the entire document image (NO in step S9), the process returns to step S3, and the next discrimination target area 304 by the discrimination target area setting unit 103 is returned. Is set. When the reflection of the halftone dot determination result in the reflection area 320 is completed (YES in step S9), the flow ends.

  FIG. 7 is a flowchart showing an example of an operation related to vector histogram creation in step S4 shown in FIG. First, the position of a predetermined pixel in the discrimination target area 304 is set as a target position, that is, the pixel in the discrimination target area 304 that is the position of the reference position 307 is set (step S41), and the reference position 307 and the discrimination pixel 303 are set. The coincidence determination unit 1011 determines whether or not the position matches (step S42). When the reference position 307 and the determination pixel 303 match (YES in step S43), the shortest position detection unit 1012 sets the shortest distance from the determination pixel 303 at the reference position 307 in the inspection region 305. A certain discrimination pixel 303 is detected (step S44), and the number of detections (appearance count) of the discrimination pixel 303 located at the shortest distance from the reference position 307 is integrated (step S45).

  When the setting of the inspection area 305 for all areas of the predetermined area 301 is not completed, that is, when the movement (setting) of the reference position 307 is not completed for all areas of the determination target area 304 ( NO in step S46), the process returns to step S41, and the position of the pixel in the determination target region 304 to be the next reference position 307 is set. When the movement of the reference position 307 is completed for all the areas to be determined 304 (YES in step S46), the creation of the vector histogram is ended.

  If the pixel at the reference position 307 is not the determination pixel 303, that is, if the reference position 307 and the position of the determination pixel 303 do not match (NO in step S43), the number of times the determination pixel 303 is detected. Is not performed, and the process proceeds to step S46.

(Second Embodiment)
FIG. 8 is a block diagram showing a schematic configuration of a copying machine 1a which is an example of an image processing apparatus according to the second embodiment of the present invention. The copying machine 1a shown in FIG. 8 is different from the copying machine 1 shown in FIG. 1 in the following points. That is, in the copier 1a shown in FIG. 8, the halftone dot determination unit 102a includes a total frequency calculation unit 1024. The total frequency calculation unit 1024 calculates a total frequency by summing the frequencies in a position where the distance from the origin of the vector histogram is in a range between a predetermined value and a predetermined value. Since the other configuration is the same as that of the copying machine 1 shown in FIG. 2, the operation of this embodiment will be described below.

  Here, the following description will be made using, for example, a vector histogram 901 shown in FIG. 9 created by the histogram creation unit 101.

The halftone dot determination unit 102a determines that the determination target region 304 is a halftone dot region based on the distance between the origin and the maximum frequency obtained by the distance calculation unit 1022 and the total frequency calculation unit 1024, and information on the total frequency. It is determined whether or not there is. Specifically, when the following two conditions (1) and (2) are satisfied, it is determined that the partial area (reflection area 320) in the determination target area 304 is a halftone dot area, and otherwise, It is determined that the reflection area 320 is not a halftone dot area.
(1) Distance between origin and maximum frequency in vector histogram ≦ 5.0
(2) Total frequency> 25 in the range where the distance from the origin in the vector histogram is 2.5 or more and 5.5 or less

  For the vector histogram 901 shown in FIG. 9, the maximum frequency detected by the maximum value detection unit 1021 is the frequency “22” at the position indicated by reference numeral 902, and the origin (origin 903) and the maximum frequency “ The distance between the position 22 ”is 4.47 (≦ 5.0). In addition, the total frequency of the range in which the distance from the origin 903 is 2.5 or more and 5.5 or less is “42” (> 25), and thus the above two conditions are satisfied. Is determined to be a halftone dot region.

The above two conditions are set such that when the number of halftone lines at a resolution of 600 dpi is 120 lines or more, it is determined as a halftone dot, and when it is 100 lines or less, it is not determined as a halftone dot. Corresponds to halftone dots on line 133 (screen angle 30 °) (see FIG. 12 for the number of halftone dots). In addition, the shaded area in the vector histogram 901 indicates an area whose distance from the origin 903 is 2.5 or more and 5.5 or less.

FIG. 10 is a flowchart showing an example of an operation related to halftone dot discrimination for a document image according to the second embodiment. First, a document image is acquired by reading a document by the document reading unit 5 (step S21). The discrimination pixel detection unit 111 detects the discrimination pixel 303 from the document image (step S22). Then, the discrimination target area 304 in the predetermined area 301 is set by the discrimination target area setting unit 103 (step S23), and the histogram creation unit 101 creates a vector histogram (for example, a vector histogram 901) for the discrimination target area 304 ( Step S24).

Next, the maximum frequency (“22”) in the vector histogram 901 is detected by the maximum value detection unit 1021 (step S25), and the distance between the origin 903 and the position of the maximum frequency is calculated by the distance calculation unit 1022 ( In step S26), the total frequency which is the total value of the frequencies in the range where the distance from the origin 903 is not less than the predetermined value and not more than the predetermined value is calculated by the total frequency calculating unit 1024 (step S27). Then, based on the distance and total frequency information obtained by the distance calculation unit 1022 and the total frequency calculation unit 1024, the halftone dot determination unit 102 determines whether the reflection region 320 in the determination target region 304 is a halftone dot region. A determination is made (step S28).

  When the reflection of the halftone dot determination result to the reflection area 320 is not completed over the entire document image (NO in step S29), the process returns to step S23, and the next determination target area 304 by the determination target area setting unit 103 is returned. Is set. When the reflection of the halftone dot determination result in the reflection area 320 is completed (YES in step S29), the flow ends.

  Note that the flowchart regarding the vector histogram creation operation in step S24 is the same as the flowchart shown in FIG. 7 in the first embodiment, and a description thereof will be omitted.

As described above, according to the image processing apparatus of the present invention, a document image is acquired by the document reading unit 5, and the determination pixel 303 having an extreme value of density in the predetermined region 301 of the document image acquired by the document reading unit 5. Is detected by the discrimination pixel detection unit 111. Then, based on the positional relationship between the determination pixels 303 detected by the determination pixel detection unit 111 on the two-dimensional plane and the frequency of occurrence of the positional relationship, the dot region in the predetermined region 301 is determined by the control unit 10. The As described above, halftone dot discrimination is performed based on the positional relationship between the discrimination pixels 303 on the two-dimensional plane and the information on the frequency of occurrence of the positional relationship, so that the halftone dot region in the document can be accurately determined. it can.

Further, the control unit 10 includes each discrimination pixel 30 detected by the discrimination pixel detection unit 111.
The inspection area 305 is sequentially set on the predetermined area 301 so that 3 is positioned at the reference position 307 of the inspection area 305, and the occurrence frequency of the other determination pixels 303 with respect to the determination pixels 303 at the reference position 307 on the inspection area 305 A histogram creation unit 101 that creates a two-dimensional histogram (vector histogram) that represents the difference between the reference pixel 307 and the reference pixel 307 that is located at the shortest distance from the reference position 307 using the vector histogram created by the histogram creation unit 101. And a halftone dot discriminating unit 102 for discriminating a halftone dot area in the predetermined area 301 based on the identified distance and occurrence frequency. In this way, a vector histogram representing the occurrence frequency (frequency) of another discrimination pixel 303 with respect to the discrimination pixel 303 at the reference position 307 on the inspection region 305 is created, and halftone dot discrimination is performed based on this vector histogram. Therefore, it is possible to easily determine the halftone dot region in the document.

  Further, the halftone dot determination unit 102 includes a maximum value detection unit 1021 that detects the maximum frequency in the vector histogram, a distance calculation unit 1022 that calculates the distance between the origin of the vector histogram and the coordinate position of the maximum frequency, and a vector A ratio calculation unit 1023 that calculates a ratio of the maximum frequency to the total frequency obtained by summing up the frequencies in the histogram, the maximum frequency detected by the maximum value detection unit 1021, the distance calculated by the distance calculation unit 1022, and The halftone dot area in the predetermined area 301 is discriminated by the halftone dot discriminating unit 102 using the ratio information calculated by the ratio calculating unit 1023. Therefore, it is possible to easily determine the halftone dot region based on the vector histogram.

  Further, the halftone dot determination unit 102 includes a maximum value detection unit 1021 that detects the maximum frequency in the vector histogram, a distance calculation unit 1022 that calculates the distance between the origin of the vector histogram and the coordinate position of the maximum frequency, and a vector A total frequency calculation unit 1024 that calculates a total frequency that is a total of the frequencies in the coordinate position in which the distance from the origin in the histogram is in the range of a predetermined value to a predetermined value, and the distance calculated by the distance calculation unit 1022 The halftone dot area in the predetermined area 301 is discriminated by the halftone dot discriminating unit 102 using the information on the total frequency calculated by the total frequency calculating unit 1024. Therefore, it is possible to easily determine the halftone dot region based on the vector histogram.

Further, the control unit 10 divides the predetermined area 301 into a plurality of determination areas, and a halftone dot area is determined for each reflection area 320. That is, in the predetermined area 301, the reflection area 320, which is one of the partial areas obtained by dividing the determination target areas 304 in the predetermined area 301 into a predetermined number, is set, and the predetermined area 301 (the determination target area 304 is determined). ) For each reflection area 320 for the reflection area 320), the number of times of halftone dot discrimination (repetition number) for the document image is increased, and as a result, the halftone dot region in the original is more accurately determined. Can do. In addition, this invention can take the following aspects.

  (A) In each of the above embodiments, the halftone dot is determined for the reflection area 320 in the determination target area 304. In this way, the determination is performed for a partial area of the determination target area 304. It does not have to be. That is, a configuration in which only halftone dot discrimination for the entire discrimination target region 304 may be performed.

  (B) In each of the above embodiments, when the halftone dot discrimination for the reflection area 320 is completed, the next halftone dot discrimination is performed by moving the discrimination target area 304 while sequentially shifting to the position adjacent to the reflection area 320. There may be a configuration in which the determination target area 304 is moved to a position away from the previous reflection area 320 without being moved to an adjacent position.

1 is a cross-sectional view schematically showing an internal configuration of a copier that is an example of an image processing apparatus according to a first embodiment of the present invention. FIG. 2 is a block diagram illustrating a schematic configuration of the copier illustrated in FIG. 1. It is explanatory drawing regarding preparation of the vector histogram based on the pixel for discrimination of a manuscript image. It is a figure which shows an example of a vector histogram. It is a figure which shows an example of a vector histogram. 6 is a flowchart showing an example of an operation related to halftone dot discrimination for a document image according to the first embodiment. It is a flowchart which shows an example of the operation | movement regarding vector histogram preparation in step S4 shown in FIG. FIG. 5 is a block diagram illustrating a schematic configuration of a copier that is an example of an image processing apparatus according to a second embodiment of the present invention. It is a figure which shows an example of a vector histogram. 10 is a flowchart illustrating an example of an operation related to halftone dot discrimination for a document image according to a second embodiment. It is a figure which shows the table which put together the distance of the origin of a vector histogram, and the position of each frequency distributed in a vector histogram. It is a figure which shows the distance between dots with respect to the number of halftone lines in the resolution of 600 dpi.

Explanation of symbols

1 Copying machine (image processing device)
1a Copy machine (image processing device)
5 Document reading unit (image acquisition means)
6 Document Feeding Section 7 Image Memory 8 HDD
10 Control unit (discriminating means)
101 Histogram creation unit (creation means)
1011 Match determination unit 1012 Shortest position detection unit 1013 Integration unit 102 Halftone discrimination unit (halftone discrimination unit)
102a Halftone discrimination unit (halftone discrimination means)
1021 Maximum value detection unit (maximum frequency detection means)
1022 Distance calculation unit (distance calculation means)
1023 Ratio calculation unit (ratio calculation means)
1024 Total frequency calculation unit (total frequency calculation means)
103 Discrimination target area setting unit 11 Image processing unit 111 Discrimination pixel detection unit (detection means)
40 Recording Unit 47 Operation Unit 473 Display 301 Predetermined Area 302 Pixel 303 Discrimination Pixel 304 Discrimination Target Area 305 Inspection Area 307 Reference Position 320 Reflection Area (Determination Area)
401, 501, 901 Vector histogram (two-dimensional histogram)
402, 503, 903 Origin

Claims (5)

Image acquisition means for acquiring a document image;
Detection means for detecting a discrimination pixel having an extreme value of density in a predetermined area of the document image acquired by the image acquisition means;
And a discriminating unit that discriminates a halftone dot region in the predetermined region based on a positional relationship between the discrimination pixels detected by the detecting unit on a two-dimensional plane and an occurrence frequency of the positional relationship. Image processing device. The discrimination means includes
The inspection area is sequentially set on the predetermined area so that each determination pixel detected by the detection means is located at the reference position of the inspection area, and another determination pixel with respect to the determination pixel at the reference position on the inspection area Creating means for creating a two-dimensional histogram representing the occurrence frequency of
Using the two-dimensional histogram created by the creation means, the distance between the discrimination pixel located at the shortest distance from the reference position and the reference position and the occurrence frequency of the discrimination pixel are specified, and the specified distance and occurrence The image processing apparatus according to claim 1, further comprising: a halftone dot discriminating unit that discriminates a halftone dot area in the predetermined area based on a frequency. The halftone dot discrimination means
Maximum frequency detection means for detecting the maximum frequency in the two-dimensional histogram;
Distance calculating means for calculating a distance between the origin and the coordinate position of the maximum frequency in the two-dimensional histogram;
A ratio calculating means for calculating a ratio of the maximum frequency to the total frequency obtained by summing up the frequencies in the two-dimensional histogram,
Determining a halftone dot area in the predetermined area using information on the maximum frequency detected by the maximum frequency detection means, the distance calculated by the distance calculation means, and the ratio calculated by the ratio calculation means; The image processing apparatus according to claim 2, wherein: The halftone dot discrimination means
Maximum frequency detection means for detecting the maximum frequency in the two-dimensional histogram;
Distance calculating means for calculating a distance between the origin and the coordinate position of the maximum frequency in the two-dimensional histogram;
A total frequency calculating means for calculating a total frequency obtained by totaling the frequencies at a coordinate position in which the distance from the origin in the two-dimensional histogram is in a range not less than a predetermined value and not more than a predetermined value;
3. The image processing according to claim 2, wherein the halftone dot region in the predetermined region is determined using the distance calculated by the distance calculating unit and the information on the total frequency calculated by the total frequency calculating unit. apparatus.   The image processing apparatus according to claim 1, wherein the determination unit divides the predetermined region into a plurality of determination regions and determines a halftone dot region for each determination region.