JP2010199649A - Image processing apparatus, image reader, image forming apparatus, image processing program, and computer-readable recording medium with the image processing program stored - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing apparatus for determining the number of dot lines at a high speed, an image reader, an image forming apparatus, an image processing program, and a computer-readable recording medium with the image processing program stored. <P>SOLUTION: In the image processing apparatus includes a color component selection unit 150, which selects a color component having a smallest density value of R, G and B values of a pixel of interest of an image of an original, an average value calculation unit 152, which calculates an average value of density values of the selected color component in a local block as a set of pixels including the target pixel; an frequency of inversion calculating unit 154 which counts the frequency of inversion of a density value of the selected color component, based on the average value, calculated by the average value calculation unit 152, as the center between pixels which are adjacent to each other in the local block; and a dot line number decision unit 156, which determines the number of dot lines of the local block, including the target pixel based upon the number counted by the inversion frequency calculation unit 154. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention is applied to a digital copying machine, a facsimile machine, etc., and in order to improve the image quality of a recorded image, the level of the number of lines of a halftone dot is discriminated from an image signal obtained by scanning a document, and the result The present invention relates to an image processing apparatus, an image processing method, an image reading apparatus provided with the image processing apparatus, an image forming apparatus, an image processing program, and a recording medium.

  Digital color image input devices such as digital scanners and digital still cameras generally have tristimulus color information (R, G, and B) obtained by a color-separated solid-state image sensor (CCD: Charge Coupled Device). Is converted from an analog signal to a digital signal to input input color image data (color information). When the signal input by the image input device is optimally displayed and output, processing for separating the read original image into small regions having different characteristics is performed. Thereafter, it is possible to reproduce and output a high-quality image by performing optimum image processing on each region.

  Generally, when a document image is separated into small areas, a process of identifying a character area, a halftone dot area, and a photograph area (other areas) existing in the read document image is performed. The image reproducibility can be improved by performing an image quality improvement process suitable for each identified area.

  In the halftone dot region, 65 lines / inch (hereinafter, [line / inch] is written as [lpi]), 85 [lpi], 100 [lpi], 120 [lpi], 133 [lpi], 150 [lpi] ] Halftone dots are drawn with the number of halftone dots per unit length, such as 175 [lpi] or 200 [lpi]. For this reason, various methods have been proposed for determining the number of halftone lines in an area determined to be a halftone area, and it is generally performed to improve image quality by performing appropriate image processing according to the result. It is.

  Japanese Patent Application Laid-Open No. 2004-228561 discloses a technique for identifying the number of halftone lines in an area determined to be a halftone dot area in a document image with high accuracy.

  In the technique described in Patent Document 1, processing is executed for each pixel in the halftone dot region in units of local blocks including the pixel. A local block is an area of an M × N pixel size including the pixel and pixels in the vicinity of the pixel.

  In Patent Document 1, for each pixel, the processing described below is performed on a local block centered on the pixel.

  First, a total sum of density differences of R, G, and B components in adjacent pixels in the local block (this value is called “complexity” in Patent Document 1) is obtained. The color component with the highest degree of complexity is selected as the color component used when identifying the number of halftone lines. Using the density value of the selected color component, whether or not the local block is a flat halftone dot area having a small density change or a non-flat halftone dot area having a large density change is adjacent to the pixel in the local block. The difference between the density values is identified by processing according to a predetermined calculation formula.

  On the other hand, the average value of the density values of the selected color components is calculated in the local block. Using this average value as a threshold value, the density value of each pixel in the local block is binarized. Using this binary data, the number of binary data inverted between adjacent pixels for each row and column in each of the main scanning direction and the sub-scanning direction in the local block (hereinafter referred to as the number of inversions). ) To obtain the maximum value. The sum of the maximum number of inversions in the main scanning direction and the number of inversions in the sub-scanning direction is obtained as the “maximum inversion number” of this local block.

  The above processing is executed for local blocks of all pixels.

  Thereafter, an average value of the maximum number of inversions of the local block identified as the flat halftone dot region is calculated. The average value of the maximum number of inversions is compared with the theoretical maximum number of inversions of the halftone dot document (printed photo original) of each line number obtained in advance to identify the halftone line number of the input image.

  In a flat halftone dot area where the density change is small, by obtaining binary data using the average value of the density values in the area as a single threshold value, it is possible to accurately separate the halftone dots from the non-halftone dots. . Therefore, the number of halftone lines can be accurately identified by executing the above processing. It should be noted that the maximum number of inversions of the local block is not limited to the above-described one. The maximum number of inversions in the main scanning direction is multiplied by the maximum number of inversions in the sub-scanning direction. It is disclosed that any one of the maximum value of the number of inversions in the scanning direction and the maximum value of the number of inversions in the sub-scanning direction may be adopted as the maximum number of inversions.

JP 2006-197037 A

  In the technique described in Patent Document 1, the number of halftone lines cannot be identified unless the process for obtaining the number of inversions is performed from the process for obtaining the degree of congestion for the local blocks of all pixels. When other processing is executed using the result of the number of halftone lines, it is necessary to process the entire image again. Therefore, the time required for the entire image processing becomes long.

  Further, in Patent Document 1, since it is necessary to calculate the sum of density differences of R, G, and B components in adjacent pixels for local blocks of all pixels, such processing also increases the processing time. It becomes a factor of that.

  Accordingly, an object of the present invention is to provide an image processing apparatus, an image reading apparatus, an image forming apparatus, an image processing program, and a computer-readable recording medium on which the image processing program is recorded for determining the number of halftone lines at high speed. It is to be.

  An image processing apparatus according to a first aspect of the present invention is an image processing apparatus that uses an image information reading unit that reads an image of a document. An image processing apparatus includes a color component selecting unit for selecting a color component having the smallest density value among R, G, and B values of a target pixel with respect to the target pixel of an image of a document, and a pixel including the target pixel Average value calculating means for calculating the average value of the density values of the color components selected by the color component selecting means in the local block that is a set of the color component selecting means between the pixels adjacent to each other in the local block Based on the number of inversion times calculating means for counting the number of times that the density value of the color component selected by the inversion is centered on the average value calculated by the average value calculating means, and the number counted by the inversion number calculating means. And a halftone dot number judging means for judging the halftone dot number of the target pixel.

  The color component selection unit selects a color component having the smallest density value among the R, G, and B values of the target pixel for the target pixel. Therefore, as described in Patent Document 1, the processing time can be shortened as compared with the process of calculating the sum of the density differences of R, G, and B components in adjacent pixels.

  The average value calculating means calculates the average value of the density of the selected color component for the local block including the target pixel. The inversion number calculating means counts the number of times that the density value of the selected color component is inverted centering on the average value between adjacent pixels in the local block. The halftone line number determining means determines the number of halftone lines of the target pixel based on the counted number. The number of halftone lines can be determined for each pixel of interest in real time by the color component selection unit, the average value calculation unit, the inversion number calculation unit, and the halftone line number determination unit. When other processing is executed using the result of the number of halftone lines, it is not necessary to process the entire image again as in Patent Document 1. Accordingly, it is possible to reduce the time for the entire image processing. As a result, an image processing apparatus for determining the number of halftone lines at high speed can be provided.

  Preferably, the inversion number calculating means calculates a difference between the density value of the color component selected by the color component selecting means and the average value calculated by the average value calculating means for each pixel of the local block. Difference calculation means and a positive / negative inversion count calculation means for counting the number of times the difference calculated by the difference calculation means among pixels adjacent to each other in the local block is inverted between the adjacent pixels. Including.

  More preferably, the halftone line number determination means determines a threshold value for determining the number of halftone lines of the target pixel according to whether or not the number of times counted by the inversion number calculation means is larger than a predetermined threshold value. Including means.

  More preferably, it further includes filter applying means for selecting an optimum filter according to the number of halftone lines determined by the halftone line number determining means, and applying the filter to the image of the document.

  The filter applying unit selects an optimum filter according to the number of halftone lines determined by the halftone line number determining unit, and applies the filter to the document image. Since the number of halftone lines is determined for each pixel of interest in real time, processing can be performed at high speed even when a filter is applied using the number of halftone lines.

  An image forming apparatus according to the second aspect of the present invention includes any of the image processing apparatuses described above.

  An image reading apparatus according to the third aspect of the present invention includes any of the image processing apparatuses described above.

  An image processing method according to a fourth aspect of the present invention is an image processing method using an image information reading unit that reads an image of a document. In the image processing method, the color component selection unit selects a color component having the smallest density value among the R, G, and B values of the target pixel with respect to the target pixel of the document image; In the local block that is a set of pixels including the target pixel, the average value calculating unit calculates an average value of the color components selected in the color component selecting step, and the inversion number calculating unit An inversion number calculating step for counting the number of times that the density value of the color component selected in the color component selection step is inverted with respect to the average value calculated in the average value calculation step, The number determining unit includes a halftone line number determining step of determining the number of halftone lines of the pixel of interest based on the number counted in the inversion number calculating step.

  Preferably, in the inversion number calculating step, the difference calculating unit calculates, for each pixel of the local block, the density value of the color component selected in the color component selecting step and the average value calculated in the average value calculating step. The difference calculation step for calculating the difference and the positive / negative inversion number calculation unit count the number of times the positive / negative of the difference calculated in the difference calculation step among the adjacent pixels in the local block is inverted between the adjacent pixels. And a positive / negative inversion number calculating step.

  More preferably, in the halftone line number determination step, the threshold value determination unit determines the halftone line number of the target pixel according to whether or not the number of times counted in the inversion number calculation step is larger than a predetermined threshold value. Including a threshold determination step.

  More preferably, the filter applying unit further includes a filter applying step of selecting an optimum filter according to the number of halftone lines determined in the halftone line number determining step, and applying the filter to the image of the document.

  An image processing program according to the fifth aspect of the present invention causes a computer to function as any of the image processing apparatuses described above.

  A recording medium according to a sixth aspect of the present invention is a computer-readable recording medium that records the above-described image processing program.

  As described above, according to the present invention, the color component having the smallest density value is selected from the R, G, and B values of the pixel of interest of the read document image, and attention is paid using the density value of the selected color component. The number of halftone lines of the local block including the pixel is determined. Therefore, as described in Patent Document 1, the processing time can be shortened as compared with the process of calculating the sum of the density differences of R, G, and B components in adjacent pixels.

  Further, according to the present invention, the number of halftone lines can be determined in real time for each pixel of interest. When other processing is executed using the result of the number of halftone lines, it is not necessary to process the entire image again as in Patent Document 1. Accordingly, it is possible to reduce the time for the entire image processing. As a result, it is possible to provide an image processing apparatus, an image reading apparatus, an image forming apparatus, an image processing program, and a computer-readable recording medium recording the image processing program for determining the number of halftone lines at high speed.

1 is a diagram illustrating an overall configuration of an image forming apparatus according to a first embodiment of the present invention. 2 is a block diagram illustrating a hardware configuration of the image forming apparatus. FIG. 3 is a functional block diagram showing a configuration of an image processing circuit 82. FIG. It is a functional block diagram of a halftone line number recognition unit. It is a figure for demonstrating the example of a halftone dot area | region. FIG. 4 is a diagram illustrating a specific example of some pixels of a read document image. It is a figure which shows the program structure for implement | achieving halftone line number recognition processing in a flowchart format. It is a figure which shows the program structure for implement | achieving a filtering process in the flowchart format. It is a figure which shows an example of the optimal filter frequency characteristic. It is a figure which shows the example of the filtering coefficient applied to the local block containing an attention pixel. It is a figure which shows the example of a low frequency edge detection filter. It is a figure which shows an example of the image determined as a halftone dot area | region among the read images. It is a figure which simplifies and shows the structure of the system 300 which concerns on the 2nd Embodiment of this invention. FIG. 2 is a diagram illustrating an appearance and an internal configuration of an image reading device 302. It is a block diagram which shows the hardware constitutions of an image reading apparatus. 3 is a functional block diagram illustrating a configuration of an image processing circuit 404. FIG. It is a block diagram which shows the hardware constitutions of the terminal device. 3 is a functional block diagram illustrating a configuration of an image processing unit 460. FIG.

  In the following description of the embodiments, the same parts are denoted by the same reference numerals. Their functions and names are also the same. Therefore, detailed description thereof will not be repeated.

[First Embodiment]
(Functional configuration)
FIG. 1 is a diagram showing an overall configuration of an image forming apparatus 20 according to the first embodiment of the present invention. Referring to FIG. 1, an image forming apparatus 20 is, for example, an electrophotographic multifunction machine that functions as a copying machine, a printer, a facsimile machine, and the like, and (1) image information of a document is stored in the apparatus main body 22. Image information reading unit 24 for reading and outputting RGB (R: Red, G: Green, B: Blue) analog image signals, and (2) recording based on image information processed by image processing circuit 82 shown in FIG. An image forming unit 26 that forms an image on paper, (3) a paper supply unit 30 that supplies recording paper from the multi-stage paper feeding cassette 28 to the image forming unit 26, and (4) an image is formed in the image forming unit 26. A fixing unit 32 for fixing the image transferred on the recording paper, (5) a paper discharging unit 36 for discharging the recording paper on which the image is fixed to the paper discharge tray 34, and (6) the entire image forming apparatus 20. Control equipment to control And a 38.

  In the image forming apparatus 20, recording paper is also supplied to the image forming unit 26 from the manual feed tray 40 and the automatic paper feed cassette 42 outside the apparatus main body 22 via the paper supply unit 30. The manual feed tray 40 is disposed on the side opposite to the paper discharge tray 34. The automatic paper feed cassette 42 can accommodate a large amount of recording paper, and is connected to the apparatus main body 22 by an external attachment below the manual feed tray 40.

  The image information reading unit 24 includes an optical system 44 capable of reading a monochrome image or color image of a document, and a document table 46 made of a transparent glass body is disposed above the optical system 44.

  The optical system 44 includes a document scanning unit, an optical lens, a CCD line sensor, and the like, and feeds the document to a document reading position on the document table 46 by an operation related to the automatic document feeder 48 provided on the document table 46. The black and white image or color image of the original document read is relatively read at a predetermined exposure position (reading position). The document image information read by the optical system 44 is output to the image processing circuit 82.

  One end of the automatic document feeder 48 is rotatably supported by the apparatus body 22 at a predetermined angle so that a document can be directly placed on the document table 46. The automatic document feeder 48 includes a document feed tray 50, a reversing path path 52, a document discharge tray 54, and the like, and a plurality of documents placed on the document feed tray 50 are one sheet. Each sheet is automatically fed onto the document reading position on the document table 46.

  In the image information reading unit 24, when the document placed on the document feed tray 50 is a double-sided document, the double-sided document faces downward from the document feed tray 50 onto the document reading position of the document table 46. It will be fed in the state. Image information on the surface of the double-sided document fed to the document reading position is read by the optical system 44. When reading of the image information on the front side is completed, the front and back sides are reversed by the reverse path path 52 in the automatic document feeder 48, and the double-sided original is fed with the back side facing down on the reading position. Image information on the back side of the document is read again by the optical system 44. When the reading of the image information on both the front and back sides of the document is completed, the double-sided document is discharged to the document discharge tray 54 of the automatic document feeder 48.

  The image forming unit 26 includes a photosensitive drum 56, a charger 58, a laser scanning unit (hereinafter referred to as “LSU”) 60 that functions as an exposure unit, a developing unit 62, a transfer unit 63, a cleaning unit 64, and a toner supply unit 66. Including. The charger 58 charges the photosensitive drum 56 to a predetermined potential. The LSU 60 performs laser processing according to image data read by the image information reading unit 24 or image data such as image information transferred from an external device such as a client personal computer (hereinafter referred to as “client PC”) 88 shown in FIG. Light is irradiated to form an electrostatic latent image on the photosensitive drum 56. The developing device 62 supplies toner to the electrostatic latent image formed on the photosensitive drum 56 via a developing roller to visualize the toner image. The transfer unit 63 transfers the toner image formed on the photosensitive drum 56 onto the recording paper. The cleaning device 64 collects the toner remaining on the photosensitive drum 56 after the transfer process is completed. The toner supplier 66 supplies toner into the developing device 62.

  The photosensitive drum 56 is supported by the apparatus main body 22 so as to be rotatable clockwise in FIG. A charger 58, an LSU 60, a developing device 62, a transfer unit 63, and a cleaning device 64 are arranged in this order along the rotation direction of the photosensitive drum 56.

  The fixing unit 32 includes a pair of roller pairs of an upper pressure roller 68 and a lower heating roller 70. The heating roller 70 has a built-in heater, and the temperature of the heating roller 70 is detected by a fixing temperature sensor.

(Hardware configuration)
FIG. 2 is a block diagram illustrating a hardware configuration of the image forming apparatus 20. Referring to FIG. 2, the image forming apparatus 20 includes an image information reading unit 24, an image forming unit 26, a paper supply unit 30, a fixing unit 32, a paper discharge unit 36, an automatic document feeder 48, and an automatic paper feed cassette 42. A network interface card (NIC) 90 that interfaces with a client PC 88, which is one of external devices, via a LAN (Local Area Network) line 86, and an operation panel 84 including a display unit and an operation unit (not shown). Including.

  The image forming apparatus 20 further includes an image information reading unit 24, an image forming unit 26, a paper supply unit 30, a fixing unit 32, a paper discharge unit 36, an automatic document feeder 48, and an automatic paper feed cassette via a common bus line 38L. 42, the NIC 90, and the operation panel 84, and a control device 38 that controls these and functions as an image processing device.

  The control device 38 is substantially a computer, and a CPU (Central Processing Unit) 72 that realizes a function as an image forming device by executing a computer program for realizing the image processing of the present embodiment. A ROM (Read Only Memory) 74 for storing a program executed by the CPU 72, and a RAM (Random Access Memory) 76 for providing various program storage areas, all connected to the CPU 72 via the common bus line 38L. , An HDD (Hard Disk Drive) 78 that is a nonvolatile storage device capable of holding various programs and data even when the power is cut off, and for storing image data read by the image information reading unit 24 Picture The image memory 80 and a circuit for reproducing the image information of one side of the double-sided document read by the image information reading unit 24 or the image information of the other side, and functioning as an image processing device. And an image processing circuit 82.

  The program stored in the ROM 74 is read from the ROM 74 and stored in the RAM 76 at the time of execution. The stored program is read from an address in the RAM 76 indicated by a register functioning as a program counter (not shown) in the CPU 72. The read program is interpreted and executed by the CPU 72. Data necessary for execution is read from an address specified by an instruction in a register in the CPU 72, the RAM 76, or the HDD 78. Similarly to this, the result of the execution is also stored in an address specified by an instruction in the register in the CPU 72, the RAM 76, or the HDD 78.

  The CPU 72 controls the image information reading unit 24, the image forming unit 26, the paper supply unit 30, the fixing unit 32, the automatic paper feed cassette 42, the automatic document feeder 48, and the NIC 90 to read the document, output the document, and the client PC 88. A desired operation such as communication with the external device is executed, and data is stored in or read from the RAM 76, the HDD 78, and the image memory 80.

  In the image forming apparatus 20, the control device 38 functioning as an image processing apparatus converts image information input from an external device such as the image information reading unit 24 or the client PC 88 into an electrical signal of each color, and Output to LSU 60 respectively.

  Note that the image processing program according to the present embodiment may be transmitted from another device to the control device 38 via the LAN line 86 and the NIC 90 and stored in the HDD 78.

(Configuration of image processing circuit 82)
FIG. 3 is a functional block diagram showing the configuration of the image processing circuit 82. Referring to FIG. 3, the image processing circuit 82 converts the RGB analog image signal read by the image information reading unit 24 into CMYK (C: cyan) according to the setting content designated by the user using the operation panel 84. , M: magenta, Y: yellow, K: black), and outputs the digital signal to the image forming unit 26.

  The image processing circuit 82 includes an A / D (analog / digital) conversion unit 100 for converting the RGB analog image signal read by the image information reading unit 24 into a digital signal and outputting the digital signal, and the A / D conversion unit 100. A shading correction unit 102 for performing processing for removing various distortions generated in the illumination system, the imaging system, and the imaging system of the image information reading unit 24 on the output digital signal.

  Further, the image processing circuit 82 adjusts the color balance for the RGB digital signal output by the shading correction unit 102, and at the same time, handles the density signal and the like for the image processing system employed in the color image processing apparatus. An input tone correction unit 104 for performing processing to convert the signal, and an RGB digital signal output by the input tone correction unit 104, for example, an image of a document, for example, a character edge region, a halftone dot region, a high density photograph And a region separation processing unit 106 that separates the region into a low-density photo region. Hereinafter, separating an original image into, for example, a character edge region, a halftone dot region, a high density photographic region, and a low density photographic region is referred to as “region separation”.

  The image processing circuit 82 further has a halftone line number signal indicating whether each pixel is greater than or equal to a certain number of halftone lines with respect to the RGB digital signal output by the region separation processing unit 106. A halftone line number recognition unit 108 for outputting an RGB digital signal is included.

  In addition, the image processing circuit 82 further causes color turbidity based on the spectral characteristics of the CMY color material including unnecessary absorption components in order to achieve color reproduction fidelity with respect to the RGB digital signal output by the dotted line number recognition unit 108. The color correction unit 110 for outputting the CMY three-color signal after color correction, the black generation process for generating a black (K) signal from the CMY three-color signal after the color correction, and the original And a black generation and under color removal unit 112 for executing a process of subtracting the black signal obtained by the black generation process from the CMY signal and outputting a new CMY signal.

  The image processing circuit 82 further performs the region separation result by the region separation processing unit 106 and the number of halftone lines output by the halftone line number recognition unit 108 on the image data of the CMYK signal output from the black generation and under color removal unit 112. A spatial filter processing unit 114 for performing spatial filter processing using a digital filter based on the signal and correcting the spatial frequency characteristic to prevent blurring and graininess of the output image is included.

  The image processing circuit 82 further executes an output gradation correction process for converting the CMYK signal output from the spatial filter processing unit 114 into a halftone dot area ratio that is a characteristic value for the image forming unit 26. Output tone correction unit 116 for performing the tone reproduction for separating the CMYK signals output by the output tone correction unit 116 into pixels and performing tone reproduction processing for processing so that each tone can be reproduced A processing unit (halftone generation processing unit) 118.

  As a general method of black generation processing executed by the black generation and under color removal unit 112, there is a method of performing black generation by skeleton black. The method is shown below. Here, the input / output characteristic of the skeleton curve is set to y = f (x), the UCR (Under Color Removal) rate is set to α (0 <α <1), and input from the color correction unit 110 to the black generation and under color removal unit 112. The data to be output is C, M, and Y, and the data output by the black generation and under color removal unit 112 is C ′, M ′, Y ′, and K ′. Then, C ′, M ′, Y ′, and K ′ are output by the following equations.

  In order to improve the reproducibility of black characters or color characters, the spatial filter processing unit 114 increases the high-frequency enhancement amount in the sharp enhancement processing in the spatial filter processing in the character edge region separated in the region separation processing unit 106. Enlarge. In addition, the spatial filter processing unit 114 performs low-pass filter processing for removing the input halftone dot component on the area determined as the halftone dot area.

  The gradation reproduction processing unit 118 performs halftone processing so that gradation can be reproduced on an optimal screen corresponding to each region separation result.

(Configuration of the dot number recognition unit 108)
FIG. 4 is a functional block diagram of the halftone line number recognition unit 108. Referring to FIG. 4, halftone line number recognizing unit 108 determines that the number of halftone lines in a region including the pixel is predetermined for each pixel of the document image in accordance with the RGB digital signal from region separation processing unit 106. A dot line number signal indicating whether or not the threshold value is exceeded and an RGB digital signal from the region separation processing unit 106 are output.

  Specifically, the halftone line number signal indicates whether the number of halftone lines in a predetermined area centered on each pixel is smaller than a threshold value X [lpi] or greater than X [lpi]. In the present embodiment, X is 65 [lpi], 85 [lpi], 100 [lpi], 120 [lpi], 133 [lpi], 150 [lpi], 175 [lpi], and 200 [lpi]. Take one of the values. The halftone line number recognition unit 108 determines whether or not the number of halftone lines in the region including each pixel is equal to or greater than a threshold value, and the threshold value is arbitrarily determined. The number of halftone lines to be compared is not limited to the above numerical values, and may be arbitrarily determined according to the application. In the present embodiment, for a pixel, outputting a halftone line number signal to an area including a certain pixel, that is, determining whether the number of halftone lines in the area including the pixel is equal to or greater than a threshold value. This is called “determining the number of halftone dots”. Details of the halftone line number determination will be described later.

  The size of the document image is assumed to be X pixels × Y pixels (X and Y are both integers of 1 or more). The halftone line number recognition unit 108 performs a process of determining the number of halftone lines of each pixel by performing raster scan scanning from the pixel in the first row and first column of the document image. In the present embodiment, raster scan scanning refers to the following processing. First, pay attention to the pixel in the first row and the first column, and determine the number of halftone lines for the target pixel. Thereafter, the number of halftone dots is determined for each pixel in order from left to right for the pixels in the first row in the halftone dot region. Thereafter, the same processing is executed for the second and subsequent lines. In the present embodiment, a pixel for which processing for determining the number of halftone lines is currently executed in raster scan scanning is referred to as a “target pixel”.

  FIG. 5 is a diagram for explaining an example of pixels of a document image. Referring to FIG. 5, in this example, it is assumed that the size of document image 180 is 21 × 17.

  The halftone line number recognition unit 108 determines the number of halftone lines for a target pixel using a local block that is a set of pixels including the target pixel. In the present embodiment, the local block has a size of 11 pixels × 11 pixels centered on the target pixel among the pixels of the document image.

  For example, in FIG. 5, if the pixel 182 in the sixth row and the sixth column in the document image 180 is the target pixel, the pixel set 184 centering on the pixel 182 becomes the local block of the target pixel.

  Note that where the target pixel is located in the local block may be arbitrarily determined according to the application. Also, the pixel size of the local block may be arbitrarily determined according to the application.

  Referring to FIG. 4 again, the halftone line number recognizing unit 108 selects the color having the smallest density value (hereinafter referred to as a selected color) among the RGB digital signals of the target pixel output by the region separation processing unit 106. In order to calculate the average value of the density values of the selected color selected by the color component selecting unit 150 for selecting and outputting the density value of the color and the local block including the target pixel. Average value calculation unit 152.

  The halftone line number recognition unit 108 further uses the average value calculated by the average value calculation unit 152 to calculate the total number of inversions indicating the number of times the density value has changed greatly between pixels in the local block. An inversion number calculation unit 154 and a halftone line number determination unit 156 for determining the number of halftone lines of the pixel of interest using the total number of inversions calculated by the inversion number calculation unit 154 are included.

  The inversion number calculation unit 154 performs the following processing for each pixel of the local block.

  Here, the density value of the pixel, the density value of a pixel adjacent on the right side of the pixel (hereinafter referred to as “right pixel”), and the pixel adjacent on the lower side of the pixel (hereinafter referred to as “lower side”). The density value of the pixel and the average value calculated by the average value calculation unit 152 are f (i, j), f (i + 1, j), f (i, j-1), and Ave.

  In a local block, the density of a portion that is a halftone dot is usually smaller than the average value of the density of the local block, and the density of a portion that is not a halftone dot is larger than the average value.

  Therefore, using f (i, j), f (i + 1, j), f (i, j-1), and Ave, the density value and average value of each of the pixel, the right pixel, and the lower pixel are The differences sub_1, sub_2, and sub_3 are calculated as follows.

  However, when the pixel is located at the right end of the local block, sub_2 is not calculated. Also, sub_3 is not calculated when the pixel is located at the lower end of the local block.

  The product of sub_1 and sub_2 and the product of sub_1 and sub_3 are set to cond_1 and cond_2, respectively.

  If cond_1 is negative, the density is inverted between the pixel and the right pixel, centering on the average value. If cond_1 is positive, the density values of the pixel and the right pixel are both large or small with respect to the average value. That is, if the pixel is a halftone dot, the right pixel is also a halftone dot, and if the pixel is not a halftone dot, the right pixel is not a halftone dot.

  The same can be said for cond_2.

  Thereafter, the number of negative ones of cond_1 and cond_2 in the pixel is counted.

  This value is summed for all pixels in the local block. The total value is the total number of inversions described above.

  The greater the number of halftone dots in the local block, that is, the greater the number of halftone lines, the greater the total number of inversions.

  Hereinafter, a specific example of the process of calculating the total number of inversions will be described.

  FIG. 6A is a diagram illustrating some pixels of a read document image. Referring to FIG. 6A, pixel A is a pixel of interest. In this example, the size of the local block is 2 × 2. The right pixel of pixel A and the lower pixel of pixel A are pixel B and pixel C, respectively, and the lower pixel of pixel B and the pixel that is also the right pixel of pixel C are pixel D. The local block of the pixel A is assumed to be composed of the pixels A to D.

  FIG. 6B is a diagram illustrating density values of the pixels A to D. Referring to FIG. 6B, the density values of pixels A to D are 220, 230, 50, and 60, respectively. The average density value of the local blocks is 140. In this example, pixel A and pixel B are not halftone dots, and pixel C and pixel D are halftone dots.

  According to the calculation rule described above, the number of inversions in each of the pixels A to D is 1, and as a result, the total number of inversions is 4.

  The halftone line number determination unit 156 determines the number of halftone lines for the target pixel by comparing the total number of inversions calculated by the inversion number calculation unit 154 with a predetermined first threshold value. The first threshold value is determined in advance by experiments corresponding to the threshold value for determining the number of halftone lines. If the total number of inversions is greater than or equal to the first threshold value, the halftone line number determination unit 156 has the halftone line number in the local block including the target pixel equal to or greater than the threshold value of the halftone line number (eg, 133). If the total number of inversions is smaller than the first threshold value, the number of halftone dots in the local block including the target pixel is larger than the threshold value for judging the number of halftone lines. It is determined to be small (for example, smaller than 133 [lpi]).

(Software configuration)
FIG. 7 is a flowchart showing a control structure of a program executed by the halftone line number recognition unit 108. Referring to FIG. 7, this program receives the RGB digital signal output by region separation processing unit 106, and uses the pixel in the first row and the first column in the original image as a target pixel in steps 200 and 200. After step 202, the selected color of the target pixel is determined and the density value of the selected color is output. After step 202, the average value of the density value of the selected color of the local block including the target pixel is calculated. 204, and after step 204, using the average value and the density value of each pixel of the local block, step 206 for calculating the total number of inversions by the method described above, and after step 206, By comparing with the first threshold value, it is confirmed whether or not the number of halftone lines in the local block including the target pixel is equal to or more than the threshold value for judging the number of halftone lines. And a flop 208.

  The program further determines after step 208 whether or not it has been confirmed in step 208 that the number of halftone lines in the local block is equal to or greater than a threshold value for determining the number of halftone lines. And when the number of halftone lines in the local block is determined to be greater than or equal to the threshold value for judging the number of halftone lines in step 210, the current number of halftone lines of the target pixel is the threshold. And outputting a dot line number signal indicating that the value is greater than or equal to the value, and ending this program. When step 212 is executed, in the present embodiment, processing is performed on the assumption that the number of halftone lines is equal to or greater than the threshold value for all pixels to be processed thereafter.

  The program further outputs step 214 indicating a dot-line number signal indicating that the pixel of interest when the dot-dot number in the local block including the pixel of interest is determined to be smaller than the threshold value in step 210; After step 214, it is determined whether or not the processing has been completed for all the pixels in the halftone dot region, and step 216 for branching the control flow according to the determination result, and the processing has not been completed for all the pixels in step 216. And step 218 in which the pixel next to the current pixel of interest is set as the pixel of interest in accordance with the raster scan scanning, and the control is returned to step 202. If it is determined in step 216 that all pixels have been processed, this program ends.

  In step 212 and step 214, the halftone line number signal is output to the black generation and under color removal unit 112, the spatial filter processing unit 114, and the gradation reproduction processing unit 118.

  FIG. 8 is a flowchart showing a control structure of a program executed by the spatial filter processing unit 114. Referring to FIG. 8, this program includes step 240 in which attention is paid to the pixel in the first row and first column in the original image, and the target pixel after step 240 according to the output result of halftone line number recognition unit 108. It is determined whether or not the number of halftone lines in the local block is greater than or equal to the threshold value, and the flow of control branches according to the determination result. In step 244, the number of halftone lines in the local block including the target pixel is the threshold. If it is determined that the value is greater than or equal to the value, the high-line number filtering process described later is performed on the target pixel and pixels that are raster-scan scanned after the target pixel, and the program ends. Step 246.

  In step 244, when it is determined in step 244 that the number of halftone lines in the local block including the pixel of interest is smaller than the threshold value, step 248 that executes low-line number filtering processing, which will be described later, and step 248 After that, it is determined whether or not the above processing has been completed for all the pixels of the original image, and the flow of control is branched according to the determination result, and the processing has not been completed for all the pixels in step 250. And if so, step 252 determines the next pixel of the current pixel of interest as the pixel of interest and returns control to step 244. If it is determined in step 250 that the processing has been completed for all pixels, the program ends.

<Filtering process>
Hereinafter, the high line number filtering process and the low line number filtering process executed in steps 246 and 248, respectively, will be described.

  The purpose for applying the filtering process will be described before the description of the filtering process.

  In the halftone dot area, moire may occur due to interference between the halftone dot period and periodic halftone processing such as dither processing. In order to suppress moire, a smoothing process may be performed in advance to suppress the amplitude of a halftone image. At that time, image quality deterioration may occur at the same time, such as a halftone dot photograph and characters on the halftone dot being blurred.

  Therefore, this problem can be solved by applying a filtering process described below to the image. Thereby, it is possible to achieve both moire suppression and halftone dot photography and sharpness of characters on halftone dots for any number of halftone dots.

  The greater the number of halftone lines, the higher the frequency of the halftone image. In order to suppress the moiré that causes the greatest image quality degradation, it is necessary to apply a smoothing filter that lowers the amplitude of all the halftone frequencies. For this reason, the halftone lines output by the halftone number recognition unit 108 are used. The occurrence of moire can be suppressed by reducing the gain near the number, that is, by increasing the loss.

  FIGS. 9A to 9C are diagrams showing examples of optimum filter frequency characteristics when the numbers of halftone lines are 85 [lpi], 133 [lpi], and 175 [lpi], respectively. Referring to FIG. 9A, in the case of 85 [lpi], the frequency hits a slightly lower position compared to the number of other halftone lines, and in order to remove moire generated at 85 [lpi]. Therefore, it is necessary to perform a filtering process so that the gain near the frequency corresponding to the number of halftone lines is reduced. Referring to FIGS. 9B and 9C, even in the case of 133 [lpi] and 175 [lpi], the gains of other lines are increased so that smoothing is not applied.

  FIGS. 10A to 10C show examples of filtering coefficients applied to a local block including a pixel of interest when the numbers of halftone lines are 85 [lpi], 133 [lpi], and 175 [lpi], respectively. FIG. Referring to FIGS. 10A to 10C, the pixel size of each filtering coefficient is the same as the size of the local block. FIGS. 10A to 9C correspond to the Fourier transforms of the diagrams shown in FIGS.

  In the filtering process for the high number of lines executed in step 246, filtering coefficients as shown in FIGS. 10A to 10C are applied to the local block including the target pixel. In step 246, a filtering coefficient corresponding to the number of halftone lines output from the halftone number recognition unit 108 is applied to the local block. Specifically, each density value of the local block is multiplied by a filtering coefficient corresponding to the density value, and then the sum of the multiplied numbers is calculated for all the pixels of the local block. The total is divided by the total number of pixels in the local block, and the divided value is set as a new density value of the target pixel.

  In step 248, a filtering coefficient having a frequency lower than the number of halftone lines output from the halftone line number recognition unit 108 is applied to the target pixel.

<Other methods for suppressing moire>
In order to suppress moire, there is a method of detecting a character on a halftone dot and performing an emphasis process different from a photographic halftone dot and a background halftone dot, in addition to the filtering process described above. With respect to this method, the character on the high line number halftone dot has different frequency characteristics between the character and the high line number halftone dot. Therefore, the low frequency edge detection filter shown in FIGS. Therefore, it is possible to detect characters on a halftone dot with high accuracy without erroneously detecting the edge.

  However, it is difficult to detect a character on a low line number halftone dot because the frequency characteristic of the low line number halftone dot is similar to the frequency characteristic of the character, and image quality deterioration is caused because of the large misdetection of the halftone dot edge. Therefore, based on the halftone dot number signal recognized by the halftone dot number recognition unit 108, the character detection process on the halftone dot is performed only in the case of a high halftone halftone dot, for example, a halftone dot of 133 [lpi] or more. Alternatively, the on-dot character detection result is validated. With this processing, it is possible to improve the readability of characters on a high line number halftone dot without causing image quality degradation.

  Note that the halftone line number signal output by the halftone line number recognition unit 108 may be used by the color correction unit 110 and the gradation reproduction processing unit 118.

(Operation)
1 to 10, image forming apparatus 20 according to the present embodiment having the above-described configuration operates as follows.

  Assume that the user sets an original on the automatic document feeder 48 and instructs the image forming apparatus 20 to copy the image of the original onto a recording sheet.

  The image information reading unit 24 of the image forming apparatus 20 reads an image of a document.

  First, the image forming apparatus 20 performs the following processing on the document image.

  The A / D conversion unit 100 of the image forming apparatus 20 converts the RGB analog signal read by the image information reading unit 24 into a digital signal, and outputs the converted signal as an RGB digital signal. The shading correction unit 102 of the image forming apparatus 20 removes various distortions generated in the illumination system, the imaging system, and the imaging system of the image information reading unit 24 from the RGB digital signal output by the A / D conversion unit 100. Processing is performed, and RGB RGB reflectance signals are converted into density signals and color balance is adjusted.

  The input tone correction unit 104 of the image forming apparatus 20 adjusts the color balance with respect to the RGB digital signal output by the shading correction unit 102, and at the same time, employs a density signal or the like in the color image processing apparatus. A process of converting the signal into a signal easy to handle for the image processing system is executed.

  The region separation processing unit 106 of the image forming apparatus 20 separates the RGB digital signals output from the input tone correction unit 104 into regions.

  The following processing is performed in the halftone dot number recognition unit 108 of the image forming apparatus 20 for the RGB digital signal determined to be a halftone dot region by the region separation processing unit 106.

  The image forming apparatus 20 pays attention to the pixel in the first row and the first column in the document image (step 200 shown in FIG. 7). The image forming apparatus 20 outputs the color component having the highest density value among the RGB digital signals of the target pixel and the density value of the color component (step 202 shown in FIG. 7). The image forming apparatus 20 calculates the average value of the density values of the colors output in step 202 in the local block including the target pixel (step 204 shown in FIG. 7). The image forming apparatus 20 calculates the total number of inversions in the local block (step 206 shown in FIG. 7), and compares the total number of inversions with the first threshold value, thereby including the local pixel including the target pixel. It is checked whether the number of halftone lines in the block is equal to or greater than a threshold value (step 208 shown in FIG. 7).

  When the image forming apparatus 20 confirms that the number of halftone lines in the local block is smaller than the threshold value (NO in step 214 shown in FIG. 7), the image forming apparatus 20 outputs a halftone line number signal indicating that to the target pixel ( Step 214) shown in FIG. If there is a pixel in the original image that has not been subjected to the above-described steps 202 to 210 (NO in step 216 shown in FIG. 7), the image forming apparatus 20 selects another pixel in the original image as the target pixel. Then, the processing of steps 202 to 210 is executed.

  If the image forming apparatus 20 confirms in step 210 that the number of halftone lines in the local block including the target pixel is equal to or greater than the threshold (YES in step 214 shown in FIG. 7), the current target pixel and the target pixel Thereafter, a dot number signal indicating that the number of dot lines in the local block including each pixel is equal to or greater than a threshold value is output for the pixels to be scanned by raster scanning (step 212 shown in FIG. 7).

  Hereinafter, a specific example of the processing from Step 200 to Step 218 will be described.

  FIG. 12A illustrates an example of a document image. Referring to FIG. 12A, a plurality of halftone dots are drawn on the document image. It is assumed that the halftone dot drawing color of this image is cyan. When the halftone dot is drawn in cyan, the inversion of the halftone dot can be easily read by using the density value of the R color of RGB.

  Therefore, in this case, in step 202 shown in FIG. 7, the image forming apparatus 20 sets R as the selected color.

  FIG. 12B is a diagram showing R density values for each pixel of the image shown in FIG. Referring to FIG. 12B, the density value of the pixel on which the halftone dot is drawn is small, and the density value of the pixel on which the halftone dot is not drawn is large. If the set of pixels shown in FIGS. 12A and 12B is a local block, in step 204, the average value of density values in this local block is calculated as 175.8.

  FIG. 12C shows a value obtained by subtracting the average value from the density value for each pixel. Referring to FIG. 12C, the value of a pixel in which a halftone dot is drawn is smaller than 0, and the value of a pixel in which a halftone dot is not drawn is larger than zero.

  In step 206, the total value of the number of inversions in this local block is calculated as 15. Thereafter, in step 208, it is determined whether the pixel of interest of the local block is greater than or equal to a certain number of halftone lines, or less, depending on whether the total value is greater than or equal to a threshold value.

  The color correction unit 110 of the image forming apparatus 20 uses the spectral characteristics of the CMY color material including unnecessary absorption components to realize faithful color reproduction with respect to the RGB digital signal output by the halftone line number recognition unit 108. A process for removing the color turbidity based on the color correction is performed, and a CMY three-color signal after color correction is output.

  The black generation and under color removal unit 112 of the image forming apparatus 20 generates a black signal obtained from the black generation process from the original CMY signal by generating a black (K) signal from the CMY three-color signal after color correction. A process of subtracting and outputting a new CMY signal is executed.

  The spatial filter processing unit 114 of the image forming apparatus 20 performs the following on the CMYK digital signal output by the black generation and under color removal unit 112 and the halftone line number signal output for each pixel by the halftone line number recognition unit 108. Execute the process.

  The spatial filter processing unit 114 pays attention to the pixel in the first row and the first column in the document image (step 240 shown in FIG. 8). The spatial filter processing unit 114 determines whether or not the number of dotted lines in the local block including the target pixel is equal to or greater than a threshold value (step 244 shown in FIG. 8).

  If it is determined in step 244 that the number of halftone lines in the local block is smaller than the threshold value, the spatial filter processing unit 114 executes low-line number filtering processing on the target pixel (shown in FIG. 8). Step 248). If there is a pixel for which filtering processing has not been completed for all pixels of the document image (NO in step 250 shown in FIG. 7), the spatial filter processing unit 114 sets the pixel to be scanned next as a target pixel, The processing after step 244 is executed.

  If it is determined in step 244 that the number of halftone lines in the local block including the target pixel is equal to or greater than the threshold value, the spatial filter processing unit 114 performs the raster scan scan on the target pixel and the target pixel and thereafter. A high line number filtering process is executed for (2) shown in FIG.

(Effect of this embodiment)
As described above, by using the image processing apparatus 20 according to the first embodiment, the color component having the minimum density value is selected from the color components RGB of the target pixel, and the color component is networked. A process of outputting a dotted line number signal is executed. This process is completed in the local block. Therefore, as compared with the technique described in Patent Document 1, it is possible to realize high-speed processing with respect to determining the number of halftone lines for the target pixel.

(Modification of this embodiment)
In the embodiment described above, the halftone line number recognition unit 108 outputs a halftone line number signal for all pixels of the document image. However, the present invention is not limited to such an embodiment, and the halftone line number recognition unit 108 outputs a halftone line number signal in real time, the black generation and under color removal unit 112, the spatial filter processing unit 114, and the floor. The tone reproduction processing unit 118 may execute its own processing in real time each time a halftone line number signal is output.

  By executing such real-time processing, it is not necessary to process the entire image again, and the time required for image processing can be shortened.

[Second Embodiment]
FIG. 13 is a diagram showing a simplified configuration of a system 300 according to the second embodiment of the present invention. Referring to FIG. 13, a system 300 is connected to an image reading device 302 that functions as a scanner for reading an image of a document, and the image reading device 302 and a USB (Universal Serial Bus) via a communication line 308. A terminal device 304 for performing image processing on an image of a document read by the image reading device 302 is connected to the terminal device 304 via a communication line 310 by USB, and the image information processed by the terminal device 304 is converted into image information. And a printer device 306 for forming an image on a recording sheet based on the image data.

(Configuration of image reading apparatus)
FIG. 14A is a perspective view showing the appearance of the image reading apparatus 302. Referring to FIG. 14A, the image reading apparatus 302 includes an image information reading unit 320 and an operation panel 324.

  Here, the operation description for the image information reading unit 320 to read the image of the document will be described together with the description regarding the configuration of the image information reading unit 320.

  FIG. 14B is a diagram illustrating a simplified internal configuration of the image reading apparatus 302. Referring to FIGS. 14A and 14B, the user sets a document on document set tray 322 of image information reading unit 320. When the user operates the operation panel 324 installed in front of the image information reading unit 320, the size, scaling factor, and the like of the printing paper are input and set. The user operates the operation panel 324 to instruct document reading.

  In response to the above instruction, the image information reading unit 320 sends the document on the document set tray 322 to the platen glass 368 through the space between the separating plate 350 and the conveying roller 358 by the pickup roller 360. The image information reading unit 320 conveys the document on the platen glass 368 in the sub-scanning direction, and discharges the document to the document discharge tray 326.

  At this time, the reading unit 366 reads an image of the document. The reading unit 366 includes a first scanning unit 356 and a second scanning unit 354. Both the first scanning unit 356 and the second scanning unit 354 are moved to a predetermined position and positioned. The exposure lamp of the first scanning unit 356 irradiates the surface of the document through the platen glass 368, and the reflected light of the document is imaged by the reflecting mirrors of the first scanning unit 356 and the second scanning unit 354 to form an imaging lens 362. Lead to. The guided reflected light of the original is condensed on the CCD 364 by the imaging lens 362, and an image on the surface of the original is formed on the CCD 364 to read the image on the surface of the original.

(Hardware configuration of image reading apparatus)
FIG. 15 is a block diagram illustrating a hardware configuration of the image reading apparatus 302. Referring to FIG. 15, an image reading device 302 includes an image information reading unit 320, a USB interface unit 328 that interfaces with a terminal device 304 via a communication line 308, and an operation panel including a display unit and an operation unit (not shown). 324.

  The image reading device 302 is further connected to the image information reading unit 320, the USB interface unit 328, and the operation panel 324 via the common bus line 414, and controls these to control the control device 400 functioning as an image processing device. Including.

  The control device 400 is substantially a computer, and by executing a computer program for realizing the image processing of the present embodiment, a CPU 402 that realizes functions as a scanner and an image processing device, and a common bus line A ROM 406 for storing a program executed by the CPU 402, a RAM 408 for providing a storage area for various programs, various programs and data, etc. even when the power is cut off. HDD 410, which is a non-volatile storage device capable of storing image data, an image memory 412 for storing image data read by the image information reading unit 320, and an image of one side of a double-sided document read by the image information reading unit 320 To perform image reproduction of information or image information on the other side A circuit, and an image processing circuit 404 which functions as an image processing apparatus.

  The ROM 406 and the RAM 408 realize the same functions as the ROM 74 and the RAM 76 according to the first embodiment, respectively.

  The CPU 402 controls the image information reading unit 320 and the USB interface unit 328 to execute desired operations such as document reading and image information output to the terminal device 304, and stores data in the RAM 408, HDD 410, and image memory 412. Or read from it.

  In the image reading device 302, the control device 400 that functions as a scanner and an image processing device converts image information input from the image information reading unit 320 into electrical signals of each color and outputs the electrical signals to the terminal device 304.

(Configuration of image processing circuit)
FIG. 16 is a functional block diagram showing the configuration of the image processing circuit 404. Referring to FIG. 16, the image processing circuit 404 performs image processing on the RGB analog image signal read by the image information reading unit 320 according to the setting content designated by the user using the operation panel 324, The digital signal and the halftone line number signal for each pixel are output to the terminal device 304 in the same manner as in the first embodiment.

  The image processing circuit 404 converts the RGB analog image signal read by the image information reading unit 320 into a digital signal and outputs the digital signal, and the digital signal output by the A / D conversion unit 420 The image information reading unit 320 includes a shading correction unit 422 for performing processing for removing various distortions generated in the illumination system, the imaging system, and the imaging system.

  The image processing circuit 404 further includes a region separation processing unit 424 that separates the image of the document from the RGB digital signal output by the shading correction unit 422, an RGB digital signal output by the region separation processing unit 424, and each pixel. A halftone line number recognition unit 426 for outputting a halftone line number signal to the terminal device 304.

(Configuration of terminal device)
FIG. 17 is a block diagram showing an internal configuration of the terminal device 304. Referring to FIG. 17, the terminal device 304 has a first USB interface unit 454 that interfaces with the image reading device 302 via the communication line 308 and a second interface that interfaces with the printer device 306 via the communication line 310. USB interface unit 456, storage device 452 for storing various information such as programs, and an image for further image processing according to the image information when image information is received from image reading device 302 And a processing unit 460.

  The terminal device 304 is further connected to a bus 458 connected to the first USB interface unit 454, the second USB interface unit 456, the storage device 452, and the image processing unit 460, and to the bus 458. And a control unit 450 for realizing a function of executing image processing on the image information from 302.

  The control unit 450 governs overall control of the terminal device 304. Note that the control unit 450 controls the first USB interface unit 454, the second USB interface unit 456, the storage device 452, and the image processing unit 460.

  FIG. 18 is a functional block diagram illustrating a configuration of the image processing unit 460. Referring to FIG. 18, the image processing unit 460 performs spectral separation of CMY color materials including unnecessary absorption components in order to realize color reproduction fidelity with respect to RGB digital signals that are image information from the image reading device 302. A process of removing color turbidity based on the characteristics, and a color correction unit 480 for outputting CMY three-color signals after color correction, and image data of the CMY signals output from the color correction unit 480, A spatial filter process using a digital filter is performed on the basis of the region separation result and halftone line number signal output by the image reading device 302, and processing is performed to prevent blurring and graininess deterioration of the output image by correcting the spatial frequency characteristics. And a spatial filter processing unit 482.

  The image processing unit 460 further includes a gradation reproduction processing unit 484 for performing gradation reproduction processing for separating the CMY signals output from the spatial filter processing unit 482 into pixels and performing reproduction so that each gradation can be reproduced, A printer language translation unit 486 for converting the CMY signal into a printer language by the gradation reproduction processing unit 484 and outputting the printer language to the printer device 306 is included.

  The printer device 306 prints an image on a sheet in accordance with image information from the terminal device 304.

(Software configuration)
The program executed by the dotted line number recognition unit 426 of the image reading apparatus 302 is the same as the program shown by the flowchart of FIG. The program executed by the spatial filter processing unit 482 of the terminal device 304 is the same as the program shown by the flowchart of FIG.

(Operation)
Referring to FIGS. 13 to 18, system 300 according to the present embodiment operates as follows.

  A user sets a document on the document set tray 322, instructs the image reading device 302 to scan the image of the document, and instructs the printer device 306 to print the scanned image data via the terminal device 304. Shall.

  An image information reading unit 320 of the image reading device 302 reads an image of a document.

  First, the image reading device 302 performs the following processing on the document image.

  The A / D conversion unit 420 of the image reading device 302 converts the RGB analog signal read by the image information reading unit 320 into a digital signal, and outputs the converted signal as an RGB digital signal. The shading correction unit 422 of the image reading apparatus 302 removes various distortions generated in the illumination system, the imaging system, and the imaging system of the image information reading unit 320 from the RGB digital signal output by the A / D conversion unit 420. Processing is performed, and RGB RGB reflectance signals are converted into density signals and color balance is adjusted.

  The region separation processing unit 424 of the image reading device 302 separates the RGB digital signal output by the shading correction unit 422 into regions. The region separation processing unit 424 outputs the region separation result to the terminal device 304.

  The halftone line number recognition unit 426 of the image reading apparatus 302 performs the same processing as the halftone line number recognition unit 108 according to the first embodiment on the RGB digital signal output by the region separation processing unit 424. The halftone line number recognition unit 426 outputs the RGB digital signal and the halftone line number signal to the terminal device 304.

  The color correction unit 480 of the terminal device 304 uses the color based on the spectral characteristics of the CMY color material including unnecessary absorption components in order to realize faithful color reproduction with respect to the RGB digital signal output by the image reading device 302. A process for removing turbidity is performed, and a CMY three-color signal after color correction is output.

  The spatial filter processing unit 482 of the terminal device 304 performs the first implementation on the CMY digital signal output by the color correction unit 480 and the region separation result and halftone line number signal output by the image reading device 302. The same processing as that of the spatial filter processing unit 114 according to the embodiment is executed.

  The gradation reproduction processing unit 484 of the terminal device 304 performs gradation reproduction processing that separates the CMY signals output from the spatial filter processing unit 482 into pixels and performs processing so that each gradation can be reproduced.

  The printer language selection unit 486 of the terminal device 304 converts the CMY signal into the printer language by the gradation reproduction processing unit 484 and outputs the converted signal to the printer device 306.

  The printer device 306 prints an image on a sheet in accordance with image information from the terminal device 304.

[Modification]
The present invention can also record an image processing method for performing dot number recognition processing on a computer-readable recording medium on which a program to be executed by a computer is recorded.

  As a result, the number of halftone lines can be recognized, and a recording medium recording a program for performing an image processing method for performing appropriate processing based on the result can be provided in a portable manner.

  The recording medium may be a program medium such as a memory (not shown) such as a ROM because processing is performed by a microcomputer, and a program reading device as an external storage device (not shown) is provided. It may be a program medium that can be read by being inserted.

  In any case, the stored program may be configured to be accessed and executed by the microprocessor, and the program is read out, and the read program is stored in a program storage area (not shown) of the microcomputer. A method of downloading and executing the program may be used. In this case, it is assumed that the download program is stored in the main device in advance.

  Here, the program medium is a recording medium configured to be separable from the main body, and includes a tape system such as a magnetic tape and a cassette tape, a magnetic disk such as a floppy (registered trademark) disk and a hard disk, and a CD-ROM / MO / Disk system of optical disks such as MD / DVD, card system such as IC card (including memory card) / optical card, or mask ROM, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), flash It may be a medium that carries a fixed program including a semiconductor memory.

  In this case, since the system configuration is capable of connecting a communication network including the Internet, the medium may be a medium that fluidly carries the program so as to download the program from the communication network. When the program is downloaded from the communication network as described above, the download program may be stored in the main device in advance or installed from another recording medium.

  The above-described image processing method is executed by reading the recording medium by a digital color image forming apparatus or a program reading apparatus provided in a computer system.

  The computer system includes an image input device such as a flatbed scanner, a film scanner, and a digital camera, a computer that performs various processes such as the image processing method by loading a predetermined program, and displays the processing results of the computer. An image display device such as a CRT display and a liquid crystal display, and a printer that outputs the processing results of the computer to paper. Furthermore, a network card, a modem, and the like are provided as communication means for connecting to a server or the like via a network.

  The embodiment disclosed herein is merely an example, and the present invention is not limited to the above-described embodiment. The scope of the present invention is indicated by each claim in the claims after taking into account the description of the detailed description of the invention, and all modifications within the meaning and scope equivalent to the wording described therein are intended. Including.

  The image processing method of the present invention can be applied to either a color or monochrome digital copying machine, but any other apparatus that needs to improve the reproducibility of image data that is input and output. Any device can be applied. An example of such a device is a reading device such as a scanner.

20 Image processing device 24, 320 Image information reading unit 38, 400 Control device 72, 402 CPU
74,406 ROM
76,408 RAM
78,410 HDD
80, 412 Image memory 82, 404 Image processing circuit 108, 426 Halftone line number recognition unit 114, 482 Spatial filter processing unit 150 Color component selection unit 152 Average value calculation unit 154 Inversion number calculation unit 156 Halftone line number determination unit 300 System 302 Image reading device 304 Terminal device 450 Control unit 452 Storage device

Claims (12)

An image processing apparatus using an image information reading unit for reading an image of a document,
Color component selection means for selecting a color component having the smallest density value among the R, G, and B values of the target pixel for the target pixel of the document image;
In a local block that is a set of pixels including the target pixel, an average value calculating unit for calculating an average value of density values of the color components selected by the color component selecting unit;
For counting the number of times that the density value of the color component selected by the color component selection unit is inverted around the average value calculated by the average value calculation unit between adjacent pixels in the local block. Reversal number calculating means;
An image processing apparatus comprising: a halftone line number determining unit for determining the number of halftone lines of the local block including the target pixel based on the number counted by the inversion number calculating unit. The inversion number calculating means includes
Difference calculation means for calculating the difference between the density value of the color component selected by the color component selection means and the average value calculated by the average value calculation means for each pixel of the local block;
The positive / negative inversion number calculation means for counting the number of times that the difference calculated by the difference calculation means among pixels adjacent to each other in the local block is inverted between the adjacent pixels. The image processing apparatus according to 1.   The halftone line number determination unit is configured to determine the number of halftone lines of the local block including the target pixel according to whether the number of times counted by the inversion number calculation unit is greater than a predetermined threshold value. The image processing apparatus according to claim 1, further comprising a threshold determination unit.   2. The image according to claim 1, further comprising filter applying means for selecting an optimum filter according to the number of halftone lines determined by the halftone line number determining means and applying the filter to an image of a document. Processing equipment.   An image forming apparatus comprising the image processing apparatus according to claim 1.   An image reading apparatus comprising the image processing apparatus according to claim 1. An image processing method using an image information reading unit for reading an image of a document,
A color component selection step in which a color component selection unit selects a color component having the smallest density value among the R, G, and B values of the target pixel with respect to the target pixel of the document image;
An average value calculating unit that calculates an average value of the color components selected in the color component selection step in a local block that is a set of pixels including the target pixel; and
The inversion number calculation unit inverts the density value of the color component selected in the color component selection step between the pixels adjacent to each other in the local block, with the average value calculated in the average value calculation step as a center. A reversal count calculation step for counting the number of times;
An image processing method including: a halftone line number determination unit that determines a halftone line number of the local block including the target pixel based on the number counted in the inversion number calculating step. The inversion number calculating step includes:
The difference calculation unit calculates a difference between the density value of the color component selected in the color component selection step and the average value calculated in the average value calculation step for each pixel of the local block. Steps,
A positive / negative inversion number calculating unit that counts the number of times the positive / negative of the difference calculated in the difference calculating step among pixels adjacent to each other in the local block is inverted between the adjacent pixels; The image processing method according to claim 7, comprising:   In the halftone line number determination step, the threshold value determination unit determines whether the number of times counted in the inversion number calculation step is larger than a predetermined threshold value, and the network of the local block including the target pixel. The image processing method according to claim 7, further comprising a threshold determination step for determining the number of dotted lines.   The filter application unit further includes a filter application step of selecting an optimum filter according to the number of halftone lines determined in the halftone line number determination step, and applying the filter to an image of the document. The image processing method as described.   An image processing program for causing a computer to function as the image processing apparatus according to any one of claims 1 to 4. A computer-readable recording medium on which the image processing program according to claim 11 is recorded.

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