JP2008154131A - Image forming apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To improve image quality by determining whether a document is colored or monochromatic and changing printer γ characteristics and a feature amount extraction threshold. <P>SOLUTION: Image data of a document are read, it is discriminated based on the read image data whether the document is colored or monochromatic, image data for output constituted of an achromatic/chromatic color component are generated from the read image data and stored, and the stored image data are outputted. In the case where the read image data are determined as a colored document, an image is outputted based on the achromatic/chromatic color component of the stored image data and in the case where the read image data are determined as a monochromatic document, image data of the stored achromatic color component are outputted. A feature amount of image data after color conversion is extracted and on the basis of a result thereof, gradation characteristics are converted. Regarding a threshold used for such gradation characteristic conversion, an amplitude that varies periodically is determined to vary greatly, to vary a little or not to vary and on the basis of a colored/monochromatic discrimination result, the feature amount extraction threshold and the gradation characteristics are switched. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention determines whether a document is a color document or a monochrome document, outputs a color copy if the document is a color document, and outputs a monochrome copy if the document is a monochrome document. About.

  Conventionally, in a color copying machine equipped with a function for judging whether a document is color or monochrome and outputting using monochrome (achromatic toner or ink) or using chromatic toner or ink, In the method of outputting without pre-scanning, for example, RGB data from a scanner is converted into YMCK data by color correction processing, and when it is determined that the document is a color document, YMCK data is output and the document is a monochrome document. Is determined, it may be realized by outputting only K data of YMCK data.

  The RGB data obtained by reading is converted into YMCK data by color correction processing, and stored in a memory. If it is determined that the document is a color document, the stored and saved YMCK data is output and color printing is performed. On the other hand, if it is determined that the document is a monochrome document, K component data of YMCK output from the RGB image data is output.

At this time, the K component increases or decreases according to the amount of UCR (Under Color Removal). When the UCR amount is 100%, when copying a full-color photographic document, the roughness is conspicuous. Therefore, the UCR amount is suppressed to about 80%, and from the middle density to the Bk like skeleton black in printing. The UCR amount is set so that is generated.
JP-A-8-65530

  However, when such a setting method is applied and it is determined that the document is a monochrome document, the density of black may be reduced, the density of highlight may be too low, or may not be reproduced.

  In addition, when extracting a feature amount and determining a character image region and a photographic image, the region that should be determined as a character image is determined as a photographic image region in order to reduce the density of characters. The portion is processed by gradation processing that should be adapted to the photographic portion, and the character may be blurred or blurred, resulting in a case where the reproducibility of the character is deteriorated.

  The present invention has been made in view of such circumstances, and changes the gradation characteristics and feature amount extraction threshold of the printer γ based on the determination result of whether the original is a color original or a monochrome original. Accordingly, an object of the present invention is to provide an image forming apparatus capable of improving the copy image when it is determined as a color document and the image quality when it is determined as a monochrome document.

  The present invention includes an image reading unit that reads a document and outputs image data, a color determination unit that determines whether a document is a color document or a monochrome document based on the image data read by the image reading unit, and the image reading unit Color correction means for generating output image data consisting of achromatic components and chromatic color components for output by the image output means from the read image data, storage means for storing the image data after the color conversion, An image output means for outputting the stored image data, and when it is determined from the read image data that the document is a color document, the chromatic color of the achromatic component of the stored image data An image is output based on the component, and when the original is determined to be a monochrome original from the read image data, the stored achromatic color An image forming apparatus that outputs image data for a portion of the image data, the feature amount extracting means for extracting the feature amount of the image data after the color conversion, and the tone characteristic conversion based on the feature amount extraction result of the image data A gradation characteristic conversion means, and based on the feature value extraction result of the image data, the threshold value applied by the gradation characteristic conversion means is a threshold having a large periodic fluctuation amplitude or a small fluctuation amplitude. Alternatively, the threshold value is switched to any one of the threshold values that do not vary, and the feature value extraction threshold value of the feature value extraction means and the gradation characteristic of the gradation characteristic conversion means are switched based on the determination result of the color determination means. It is.

  Further, the image processing apparatus further includes means for setting an image quality mode, and the feature value extraction threshold to be applied to the achromatic color component after color correction and the gradation characteristic conversion means based on the image quality mode and the color determination result. The tone characteristics are set.

  Further, the apparatus further includes means for setting an achromatic color component amount after color correction, and applied to the achromatic color component after color correction from the set amount of the achromatic color component amount after the previous color correction and the color determination result. The feature amount extraction threshold value and the gradation characteristic of the gradation characteristic conversion means are set.

  In addition, when a small amount of achromatic color component is selected, the feature amount extraction threshold is lowered so that it can be easily determined as a character region, and further, the density of the achromatic color component after gradation conversion is increased. It is set to.

  The means for setting the achromatic color component amount after color correction is the operation unit.

  The feature amount extraction threshold is a high density determination threshold, a primary differential extraction threshold for data after the primary differential filter processing, and a secondary differential extraction threshold for image data after the secondary differential filter processing.

  Further, the image forming apparatus further comprises means for storing image data determined to be a color document or a monochrome document, and stores a determination result as to whether the document is a color document or a monochrome document as bibliographic information. It is what I kept.

  Therefore, according to the present invention, it is determined that the original is a color original by changing the gradation characteristics and the feature amount extraction threshold of the printer γ based on the determination result of whether the original is a color original or a monochrome original. In this case, it is possible to improve the image quality when the copy image is determined to be a monochrome original and the image quality is determined to be a monochrome original.

  In addition, when it is determined that the document is a monochrome document compared to the case where the document is a color document, the feature amount extraction type threshold is changed so that the image data after color correction is easily determined as a character. Since the gradation characteristics are changed so that the density is high and the highlight density is high, the image quality of color copy when it is determined as a color document and the image quality of monochrome copy when it is determined as a monochrome document are improved. The effect that it can do is also acquired.

  In addition, when it is determined that the document is a monochrome document compared to the case where the document is a color document, the feature amount extraction type threshold is changed so that the image data after color correction is easily determined as a character. Since the gradation characteristics are changed so that the density is high and the highlight density is increased, the color copy image quality when it is determined as a color document and the monochrome copy when it is determined as a monochrome document The image quality can be improved.

  In addition, when it is determined that the document is a monochrome document compared to the case where the document is a color document, the feature amount extraction type threshold is changed so that the image data after color correction is easily determined as a character. The gradation characteristics are changed so that the density is high and the highlight density is high. At this time, since the setting value of the achromatic color amount (UCR amount) in which the amount of K component after color correction changes according to the setting value of the UCR amount, the color copy when it is determined as a color original is changed. There is an effect that the image quality and the image quality of the monochrome copy when it is determined to be a monochrome document can be improved.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

  An outline of the mechanism of the copying machine main body 101 will be described with reference to FIG.

  In FIG. 1, charging is performed to charge the surface of the photoconductive drum 102 around an organic photoconductor (OPC) drum 102 having a diameter of 120 [mm], which is an image carrier disposed almost at the center of the copying machine main body 101. Charger 103, laser optical system 104 for forming an electrostatic latent image by irradiating the surface of uniformly charged photoconductive drum 102 with a semiconductor laser beam, and supplying each color toner to the electrostatic latent image for development. A black developing device 105 that obtains a toner image every time, and three color developing devices 106, 107, and 108 of yellow Y, magenta M, and cyan C, and an intermediate for sequentially transferring the toner images for each color formed on the photosensitive drum 102 A transfer belt 109, a bias roller 110 for applying a transfer voltage to the intermediate transfer belt 109, and a toner for removing toner remaining on the surface of the photosensitive drum 102 after transfer. Training device 111, such as a charge eliminating unit 112 are sequentially arranged to eliminate the charge remaining on the surface of the photosensitive drum 102 after the transfer.

  The intermediate transfer belt 109 has a transfer bias roller 113 for applying a voltage for transferring the transferred toner image to the transfer material, and a belt cleaning device 114 for cleaning the toner image remaining on the transfer material after transfer. Is arranged.

  A fixing device 116 that heats and pressurizes and fixes the toner image is disposed at the end of the conveyance belt 115 that conveys the transfer material peeled off from the intermediate transfer belt 109. A paper discharge tray 117 is attached to the section.

  Next, a control system built in the copying machine will be described with reference to FIG.

  As shown in FIG. 2, the control system includes a main control unit (CPU) 130, a predetermined ROM 131 and RAM 132 are attached to the main control unit 130, and the main control unit 130 includes It is connected to various sensors 160, power supply / bias control 161, communication control 162, drive control 163, and the like via an interface I / O 133, and performs control inside the copier or communication between inside and outside the copier.

  More specifically, the various sensors 160, the power / bias control 161, the communication control 162, and the drive control 163 are described in detail. The laser optical system control unit 134, the power supply circuit 135, the optical sensor 136 (ac), and the toner density sensor 137. The environmental sensor 138, the photoreceptor surface potential sensor 139, the toner supply circuit 140, the intermediate transfer belt driving unit 141, and the operation unit 142 are connected to each other. The laser optical system control unit 134 adjusts the laser output of the laser optical system 104, and the power supply circuit 135 supplies a predetermined discharge voltage for charging to the charging charger 113 and a developing device. A development bias having a predetermined voltage is applied to 105, 106, 107, and 108, and a predetermined transfer voltage is applied to the bias roller 110 and the transfer bias roller 113.

  The optical sensors 136 (a to c) are respectively opposed to the photoconductor 102 and are opposed to the optical sensor 136a and the transfer belt 109 for detecting the toner adhesion amount on the photoconductor 102, and the toner on the transfer belt 109 is detected. An optical sensor 136b for detecting the adhesion amount and an optical sensor 136c for detecting the toner adhesion amount on the conveyance belt 115 are shown in the figure so as to face the conveyance belt 115. In practice, any one of the optical sensors 136 (a to c) may be detected.

  Above the laser optical system 104, a contact glass 118 serving as a document placement table disposed above the copier body 101, an exposure lamp 119 for irradiating the document on the contact glass 118 with scanning light, and reflected light from the document Is guided to the imaging lens 122 by the reflection mirror 121 and is incident on the image sensor array 123 of a CCD (Charge Coupled Device) which is a photoelectric conversion element. The image signal converted into an electrical signal by the CCD image sensor array 123 is controlled by an unillustrated image processing device to control the laser oscillation of the semiconductor laser in the laser optical system 104.

  The optical sensor 136 includes a light-emitting element such as a light-emitting diode and a light-receiving element such as a photosensor that are arranged in the vicinity of the post-transfer area of the photosensitive drum 102, and a detection pattern latent image formed on the photosensitive drum 102. The toner adhesion amount in the toner image and the toner adhesion amount in the background portion are detected for each color, and the so-called residual potential after the charge removal from the photoreceptor is detected.

  The detection output signal from the photoelectric sensor 136 is applied to a photoelectric sensor control unit (not shown). The photoelectric sensor control unit obtains a ratio between the toner adhesion amount in the detection pattern toner image and the toner adhesion amount in the background portion, compares the ratio value with a reference value, detects a change in image density, and detects the toner density sensor. The control value 137 is corrected.

  Further, the toner concentration sensor 137 detects the toner concentration in the developing devices 105 to 108 based on a change in magnetic permeability of the developer present in the developing devices 105 to 108. The toner density sensor 137 compares the detected toner density value with a reference value, and when the toner density falls below a certain value and becomes a toner shortage state, a toner replenishment signal having a magnitude corresponding to the shortage is supplied to the toner. A function of applying to the supply circuit 140 is provided.

  The potential sensor 139 detects the surface potential of the photoconductor 102 that is an image carrier, and the intermediate transfer belt drive unit 141 controls the drive of the intermediate transfer belt.

  A developer containing black toner and a carrier is accommodated in the black developing device 105, which is agitated by the rotation of the agent agitating member 202 and pumped up on the sleeve by the developer regulating member 202 on the developing sleeve 201B. Adjust the developer amount. The supplied developer is magnetically carried on the developing sleeve 201B and rotates as a magnetic brush in the rotating direction of the developing sleeve 201B.

  A block diagram of the laser modulation process is shown in FIG.

  The writing frequency is 18.6 [MHz], and the scanning time for one pixel is 53.8 [nsec].

  The 8-bit image data can be subjected to γ conversion by a look-up table (LUT) 451.

  The pulse width modulation process (PWM) 452 converts the 8-bit image signal into an 8-value pulse width based on the 8-bit image signal, and the power modulation process (PM) 453 performs 32-value power modulation with the lower 5 bits. The laser diode (LD) 454 emits light based on the modulated signal. The light emission intensity is monitored by a photo detector (PD) 455, and correction is performed for each dot.

  The maximum value of the intensity of the laser beam can be varied to 8 bits (256 levels) independently of the image signal.

With respect to the size of one pixel, the beam diameter in the main scanning direction (this is defined as the width when the intensity of the stationary beam attenuates to 1 / e ² with respect to the maximum value) is 600 DPI, In one pixel 42.3 [•], the beam diameter is 50 [•] in the main scanning direction and 60 [•] in the sub-scanning direction.

  Next, an image processing flow will be described based on the block diagram of FIG.

  400 is a scanner, 401 is a shading process, 402 is a scanner γ conversion process, 403 is an image separation / color determination process, 404 is a spatial filter process, 405 is a hue determination process, 406 is a color conversion UCR process, and 407 is a pattern generation (1 , 408 is a scaling process, 409 is a printer γ conversion (1) process, 410 is a binary gradation process, 411 is an image compression / expansion process, 412 is a feature amount extraction / low density determination process, and 413 is a printer. γ conversion (2) processing, 414 is multi-value gradation processing, 415 is PCI I / F (interface), 416 is system bus, 414 is ROM, 415 is CPU, 416 is RAM, 417 is system controller, 418 is external Memory 419 is a LAN (Local Area Network) I / F, 420 is a pattern generation (2) process, 42 Reference numeral 1 denotes a printer γ conversion (3) process, 422 a printer, and 452 a printer controller. Reference numeral 423 denotes an engine controller, 424 denotes an HDD (hard disk), and 425 denotes a plotter controller.

  An original to be copied is color-separated into R, G, and B by a color scanner 420 and read as a 10-bit signal as an example. The read image signal is corrected for unevenness in the main scanning direction by a shading correction process 401 and output as an 8-bit signal.

  In the scanner γ conversion process 402, a read signal from the scanner is converted from reflectance data to brightness data.

  In the image separation / color determination process 403, character portion and photo portion determination, chromatic / achromatic color determination, and color document / monochrome document determination are performed.

  FIG. 6 shows a liquid crystal screen 108 of the entire operation unit shown in FIG. When “automatic color selection” is selected in FIG. 6, an “automatic color selection” mode is set. In the “automatic color selection” mode, it is determined from the RGB image data read by the scanner 401 whether the read original is a color original or a monochrome original. For example, the determination method compares the maximum value and the minimum value between RGB data with a predetermined threshold value, and if the difference, the length, and the number of pixels are within the predetermined value, an achromatic color, that is, a monochrome document. If it is determined that the document is a monochrome document, the document is determined to be a color document.

  Note that the liquid crystal screen of FIG. 6 is a display example when the density notch is the central five notch, automatic character / photo mode, automatic proton selection, and 100% magnification.

  When the “initial setting” key in the operation unit shown in FIG. 5 is selected, the screen illustrated in FIG. 5 is reached. The determination level for determining a color document and a monochrome document can be changed at the “color determination level”. If the color document is close to the color document, it is easy to determine that the document is a color document. That is, when close to color, the maximum and minimum values between RGB data are compared, the threshold is changed so that even if the difference is small, the color is determined, and the length and the number of pixels are small. However, the threshold value is changed so as to be determined as a color document.

  In the “color priority setting” in the screen illustrated in FIG. 5, there are options of “color priority” and “monochrome priority”, and these options are effective in the “automatic color selection” mode. This will be described in the color correction / UCR 406.

  In the spatial filter processing 404, in addition to processing for changing the frequency characteristics of the image signal, such as edge enhancement and smoothing according to the user's preference, such as a sharp image or a soft image, the spatial filter processing 404 corresponds to the edge degree of the image signal. Edge enhancement processing (adaptive edge enhancement processing) is performed. For example, so-called adaptive edge enhancement, in which edge enhancement is performed on a character edge and edge enhancement is not performed on a halftone image, is performed on each of the R, G, and B signals.

  FIG. 7 shows an example of adaptive edge enhancement processing.

  The image signal converted from the reflectance linearity to the lightness linearity by the scanner γ conversion 402 is smoothed by the smoothing filter processing 1101. As an example, a coefficient as shown in FIG.

  Further, the differential component of the image data is extracted by the 3 × 3 Laplacian filter 1102 at the next stage. A specific example of the Laplacian filter is shown in FIG.

  Of the 10-bit image signal not subjected to γ conversion by the scanner γ conversion 402, the edge amount detection filter 1103 performs edge detection on the upper 8 bits (one example).

  Specific examples of the edge amount detection filter are shown in FIGS. Among the edge amounts obtained by the edge detection filters of FIGS. 9A to 9D, the maximum value is used as the edge degree in the subsequent stage.

  The edge degree is smoothed by the subsequent smoothing filter 1104 as necessary. This reduces the influence of the sensitivity difference between the even and odd pixels of the scanner.

  As an example, a coefficient as shown in FIG. 9 (e) is used.

  Table conversion processing 1105 converts the obtained edge degree into a table. The values of this table specify the darkness of lines and dots (including contrast and density) and the smoothness of the halftone dots. An example of the table is shown in FIG. The edge degree is the largest with black lines or dots on a white background, and the edge degree becomes smaller as the pixel boundaries become smoother, such as finely printed halftone dots, silver halide photographs, and thermal transfer originals.

  The product (image signal D) of the edge degree (image signal C) converted by the table conversion process 1105 and the output value (image signal B) of the Laplacian filter 1102 is the image signal after smoothing (image signal A). Is transmitted to the subsequent image processing as an image signal E.

  As shown in FIG. 11, the color correction UCR processing 406 includes a masking processing unit, a three-dimensional color space conversion processing unit, a UCR processing unit, and an adaptive GCR processing unit.

  The masking processing unit converts the RGB characteristics of the input system into standard RGB characteristics that do not depend on the document type or scanner characteristics. In the copy operation, the three-dimensional color space conversion processing unit calculates the amount of color material YMC necessary for faithful color reproduction according to the spectral characteristics of the color material of the output system.

  The UCR processing unit replaces the portion where the three colors of YMC overlap with Bk (black) according to the UCR amount set by the operation unit or the like. The adaptive GCR processing unit determines the edge portion of the character from the feature amount of the image, performs processing so as to increase the UCR amount of the edge of the black character, and generates YMCK image data. TWAIN ("Technology (Toolkit) Without An (Any) Interesting (Important) Name") When used as a scanner or FAX application or distribution scanner, the three-dimensional color space conversion processing unit uses the requester's application Thus, parameters for conversion into sRGB (standard RGB), Adobe-RGB, sYCC, etc. are set.

  The masking processing unit and the color space conversion processing unit correspond in principle to a matrix operation represented by the following equation.

Here, the matrix coefficient aij is determined by the spectral characteristics of the input system and the output system (coloring material). Here, the primary masking equation is taken as an example, but color correction can be performed with higher accuracy by using a quadratic term such as B2 and BG, or a higher-order term. The arithmetic expression may be changed depending on the hue, or the Neugebauer equation may be used. In any method, Y, M, and C can be obtained from the values of B, G, and R (or B, G, and R may be used).

On the other hand, UCR processing can be performed by calculating using the following equation.
Y ′ = Y−α · min (Y, M, C)
M ′ = M−α · min (Y, M, C)
C ′ = C−α · min (Y, M, C)
Bk = α · min (Y, M, C)
... Formula 2
In the above equation, α is a coefficient that determines the amount of UCR, and when α = 1, 100% UCR processing is performed. α may be a constant value. For example, when α is close to 1 in the high density portion and close to 0 in the highlight portion (low image density portion), the image in the highlight portion can be smoothed.

  The color correction coefficient is different from the six hues of RGBYMC into 12 hues obtained by further dividing each of the six hues of RGBYMC and into every 14 hues of black and white. A hue determination process 405 determines which hue the image data is to be determined. Based on the determined result, a masking coefficient for each hue is selected.

  The pattern generation (1) process 407 generates a pattern as necessary. In the scaling process 408, vertical / horizontal scaling is performed. The printer γ conversion (1) processing 409 performs γ conversion at the time of binary copy output or at the time of scanner TWAIN / distribution scanner application. A linear γ table is set for multi-value copying.

  In the binarization gradation processing 410, simple binarization processing, binary error diffusion processing, and binary dither processing are performed at the time of binary copying and FAX output, and the processing is not performed at the time of multi-level copying.

  The image data compressed by the image compression / decompression processing 411 is output to the controller 452 through the PCI interface I / F 415 and stored in the image memory 418. In the image data read and compressed in the automatic color determination mode, a color determination result as to whether the original is a color original or a monochrome original is also stored as bibliographic information (embodiment of claim 7).

  The compressed image data stored in the image memory 418 is called and then decompressed by the image compression / decompression processing 411 through the PCI I / F 415. The image data stored in the image memory 418 is used by an external computer from the LAN interface I / F 419 via the LAN.

  The feature amount extraction / low density determination processing 412 performs feature amount extraction of the image data, and determines whether the target pixel data is an edge, a non-edge, or a weak edge corresponding to an intermediate between the edge and the non-edge. The determination and whether or not the density is low are performed.

  The printer γ conversion process (2) 413 performs printer γ conversion for edge portions, weak edges, and non-edges based on the feature amount extraction result in the feature amount extraction / low density determination processing 412. Alternatively, printer γ conversion processing using an edge or non-edge printer γ table is performed on pixels determined to be weak edge portions according to the gradation processing parameters.

  In the gradation processing 414, the gradation processing parameters are switched based on the feature amount extraction result and the low density determination result of the feature amount extraction / low density determination processing 412 to convert 8-bit image data to 4-bit image data as an example. And gradation processing.

  A printer γ conversion process (3) 421 performs gradation conversion on 2 or 4-bit image data in which a variation in printer characteristics is corrected and outputs the image data to the printer 422.

  The pattern generation process (2) 420 generates patch data having different write values during the process control process.

  The above-described feature amount extraction / low density determination processing 412, printer γ conversion processing (2) 413, and gradation processing 414 are performed by the image processing processor 454. A hardware configuration of the image processor 454 will be described.

  FIG. 12 is a block diagram showing the internal configuration of the image processor 1204.

  In the block diagram of FIG. 12, the image processor 1204 includes a plurality of input / output ports 1401 for data input / output with the outside, and can arbitrarily set data input and output.

  In addition, a bus switch / local memory group 1402 is provided inside so as to be connected to the input / output port 1401, and the memory control unit 1403 controls the memory area to be used and the path of the data bus. Input data and output data are assigned to the bus switch / local memory group 1402 as a buffer memory, stored in each of them, and external I / F is controlled.

  Various processing is performed in the processor array unit 1404 on the image data stored in the bus switch / local memory group 1402, and the output result (processed image data) is again sent to the bus switch / local memory group 1402. Store. The processing procedure in the processor array unit 1404, parameters for processing, and the like are exchanged between the program RAM 1405 and the data RAM 1406.

  The contents of the program RAM 1405 and the data RAM 1406 are downloaded from the process controller 211 to the host buffer 1407 via the serial I / F 1408. Further, the process controller 211 reads the contents of the data RAM 1406 and monitors the progress of processing.

  If the processing contents are changed or the processing mode required by the system is changed, the contents of the program RAM 1405 and data RAM 1406 referred to by the processor array unit 1404 are updated. Among the configurations described above, the processor array unit 1404 corresponds to the SIMD type image data processing unit and the sequential type image data processing unit according to the present embodiment.

  Next, the SIMD type image data processing unit and the sequential image data processing unit of the image processing apparatus will be described.

  FIG. 13 is a diagram illustrating the configuration of the SIMD type image data processing unit 1500 and the sequential image data calculation processing unit 1507. In this embodiment, first, the SIMD type image data processing unit 1500 will be described, and then the sequential type image data processing unit 1507 will be described.

  Note that the image data parallel processing unit 1500 and the image data sequential processing unit 1507 process an image as a plurality of pixel lines including a plurality of pixels arranged in one direction. FIG. 14 is a diagram for explaining pixel lines, and shows four pixel lines of pixel lines a to d. In addition, pixels indicated by hatching in the figure are target pixels to be processed this time.

  In the present embodiment, in the error diffusion process of the target pixel, the influence of surrounding pixels on the target pixel is considered for both pixels included in the same pixel line and pixels included in different pixel lines. Then, an error diffusion process between pixels included in a pixel line different from the target pixel is performed by the SIMD image data processing unit 1500, and pixels included in the same pixel line as the target pixel ( The sequential image data processing unit 1507 performs error diffusion processing with the pixel).

  The SIMD type image data processing unit 1500 includes a SIMD type processor 1506, five data input / output buses 1501a to 1501e for inputting image data and control signals to the SIMD type image data processing unit 1500, and data input / output buses 1501a to 1501a. 1501e is switched to switch the image data and control signals input to the SIMD type processor 1506, and the bus switches 1502a to 1502c for switching the bus width of the connected bus, and data used for processing the input image data are stored. 20 RAMs 1503 that control the memory controller 1505a, memory controller 1505b, memory controller 1505a, or memory controller 1505b that control the corresponding RAM 1503 Therefore and four memory switches 1504a~1504d for switching the RAM 1503.

  In the above configuration, the memory controller controlled by the bus switches 1502a to 1502c is distinguished as the memory controller 1505b, and the memory controller not controlled by the bus switches 1502a to 1502c is distinguished as the memory controller 1505a.

  (Configuration of SIMD processor) FIG. 15 is an explanatory diagram showing a schematic configuration of a SIMD processor. SIMD (Single Instruction stream Multiple Data stream) is a system that executes a single instruction in parallel for a plurality of data, and is composed of a plurality of PEs (processor elements). This SIMD type processor is disposed in the processor array section 1404 in FIG.

  Each PE has a register (Reg) 2001 for storing data, a multiplexer (MUX) 2002 for accessing a register of another PE, a barrel shifter (Shift Expand) 2003, an arithmetic logic unit (ALU) 2004, and a logical result. An accumulator (A) 2005 to be stored and a temporary register (F) 2006 for temporarily saving the contents of the accumulator.

  Each register 2001 is connected to an address bus and a data bus (read line and word line), and stores an instruction code defining processing and data to be processed. The contents of the register 2001 are input to the logical operation unit 2004, and the operation processing result is stored in the accumulator 2005. In order to retrieve the result outside the PE, the result is temporarily saved in the temporary register 2006. By extracting the contents of the temporary register 2006, the processing result for the target data is obtained.

  The instruction code is given to each PE with the same contents, the processing target data is given in a different state for each PE, and the contents of the register 2001 of the adjacent PE are referred to in the multiplexer 2002, so that the operation results are processed in parallel. Is output to the computer 2005.

  For example, if the content of one line of image data is arranged in the PE for each pixel and is subjected to arithmetic processing with the same instruction code, a processing result for one line can be obtained in a shorter time than sequential processing for each pixel. In particular, in the spatial filter processing and shading correction processing, the instruction code for each PE is an arithmetic expression itself, and the processing can be performed in common for all the PEs.

  The SIMD type processor 1506 described above includes registers 0 (R0) to 23 (R23). Each of R0 to R23 functions as a data interface between the PE in the SIMD type processor 1506 and the memory controllers 1505a and 1505b. The bus switch 1502a switches the memory controller 1505b connected to R0 to R3 and inputs a control signal to the SIMD type processor.

  The bus switch 1502b switches the memory controller 1505 connected to R4 and R5 and inputs a control signal to the SIMD type processor. The bus switch 1502c switches the memory controller 1505 connected to R6 to R9 and inputs a control signal to the SIMD type processor. The bus switch 1502c switches the memory controller 1505b connected to R6 to R9 and inputs a control signal to the SIMD type processor.

  The memory switch 1504a exchanges image data between the PE in the SIMD type processor 1506 and the RAM 1503 using a memory controller 1505b connected to R0 to R5. The memory switch 1504b exchanges image data between the PE in the SIMD type processor 1506 and the RAM 1503 using the memory controller 1505b connected to R6 and R7. The memory switch 1504c exchanges image data between the PE in the SIMD type processor 1506 and the RAM 1503 using the memory controller 1505a or the memory controller 1505b connected to R8 to R13.

  The memory switch 1504d exchanges image data between the PE in the SIMD type processor 1506 and the RAM 1503 using the memory controller 1505a connected to R14 to R19.

  The image data control unit 203 inputs control signals for processing image data together with the image data to the bus switches 1502a to 1502c via the data input / output buses 1501a to 1501e. The bus switches 1502a to 1502c switch the bus width of the connected bus based on the control signal signal. Further, the memory switches 1504a to 1504c are switched so that the memory controller 1505b connected indirectly or directly is controlled to take out data necessary for processing image data from the RAM 1503.

  When performing error diffusion processing, the SIMD type image data processing unit 1500 inputs image data created by the reading unit and the sensor board unit 1202 via the image data control unit 1203. Then, error data that is a difference between pixel data included in a pixel line (previous pixel line) processed before the pixel line (current pixel line) including the target pixel (previous pixel line) and a predetermined threshold value and the target pixel Add pixel data.

  The SIMD type image data processing unit 1500 uses the SIMD type processor 1506 to execute addition with error data in parallel for a plurality of target pixels. For this reason, a plurality of error data corresponding to the number of pixels processed in batch by the SIMD processor 1506 is stored in any of the RAMs 1503 connected to the SIMD processor 1506. In this embodiment, the SIMD processor 1506 collectively performs addition processing for one pixel line, and error data for one pixel line is stored in the RAM 1503.

  The addition value of the image data and error data for one pixel line collectively processed by the SIMD type processor 1506 is sent to the sequential image data processing unit 1507 from at least two of R20, R21, R23, and R22 one by one. Is output. The error data used in the above processing is calculated by a sequential image data processing unit 1507, which will be described later, and is input to the SIMD type processor 1506.

  On the other hand, the sequential image data processing unit 1507 is hardware that operates regardless of the control of the computer program. In FIG. 15, two sequential image data processing units 1507 are connected to the SIMD processor 1506, but the image processing apparatus according to the present embodiment performs error diffusion in which any one of them is sequentially performed. It shall be used exclusively for processing.

  FIG. 16 is a block diagram for explaining the gradation processing method.

  Image processing block FIG. 2 illustrates processing for one color of YMCK among the feature amount extraction / low density determination processing 412, printer γ conversion processing (2) 413, and gradation processing 414. On the other hand, since the copying machine 101 illustrated in FIG. 1 has a configuration in which four colors are processed in parallel, the processing block shown in FIG. 16 is used for four colors when applied to the copying machine 101.

  As illustrated in FIG. 16, the feature amount extraction / low density determination process 412 includes a line memory 4121, a feature amount extraction unit 4122, and a low density determination unit 4123. The line memory 4121 stores a plurality of lines (for example, five lines) used in the feature amount extraction unit. The feature amount extraction unit 4122 determines, from the image data, an edge portion, a non-edge portion, and a weak edge portion (region having an edge degree intermediate between the edge portion and the non-edge portion) (1, 2) by processing described later. To do. The low density determination unit 4123 compares the image data with a predetermined density threshold value and determines whether the image data corresponds to a low density (highlight) part or is image data other than highlights.

  In FIG. 16, the printer γ conversion process (2) 413 includes a printer γ conversion processing unit 4132 and printer γ table data 4131. The printer gamma conversion processing unit 4132 performs printer gamma conversion by referring to the printer gamma table set in the printer gamma table data 4131 based on the 2-bit feature quantity extraction result from the feature quantity extraction unit 4122.

  The gradation processing unit 414 includes a threshold selection unit 4150 and an error diffusion processing unit 4151.

  The quantization threshold value generation unit 4150 obtains a 2-bit feature value extraction result Chr (x0, y0) (≡C = {0, 1, 2, 2) for the target pixel (x0, y0) from the feature value extraction / low density determination process 412. 3}, hereinafter simplified to C) and 2-bit low density determination result Dns (x0, y0) (≡D = {0, 1, 2, 3}, hereinafter simplified to D) A quantization threshold is generated.

Here, for convenience, x0 is a value that designates a pixel in the main scanning direction, and y0 is a value that designates the position of a pixel in the sub-scanning direction. For 600 dpi, for example, by adding a margin to the number of pixels read A3 size _{document, x0 = {0,1,2, ~,} x0 max}; y = {0,1,2, ..., y0 max} And x0 _max = 7,100 and y0 _max = 10,000. In the case of dealing with document sizes such as A1 size and A1 size, x0 _max and y0 _max are larger values.

  The quantization threshold value table unit 4142 includes a quantization threshold value Thr [C, corresponding to the feature value extraction result C = {0, 1, 2, 3} and the low density determination result D = {0, 1, 2, 3}. D] [x, y, i] are set in advance.

Also, the blue noise addition selection table unit 4144 has a blue noise addition table Fbn [C, corresponding to each of the quantization threshold values Thr [C, D] [x, y, i] set in the quantization threshold value table unit 4142. D] [x, y, i] are set. Here, x and y of [x, y, i] are respectively used as a matrix size x _{max in} the main scanning direction and a matrix size y _max in the sub scanning direction of the quantization threshold matrix.
x = {0, 1, 2,..., x _max−1 −1} (Equation 3)
y = {0, 1, 2,..., y _max−1 } (Formula 4)
I represents the number of output gradations of the image data as M,
i = {0, 1, 2,..., M−2} (Formula 5)
Move the value of.

In order to simplify the following explanation, Z is a set of integers, and (Equation 3) to (Equation 5) are expressed as Z {x _max } = {x∈Z; 0 ≦ x <x _max } (Equation 6)
Z {y _max } = {y∈Z; 0 ≦ y <y _max } (Formula 7)
Z {M−1} = {i∈Z; 0 ≦ i <M−1} (Formula 8)
Also represent the same meaning.

That is, in (Equation 6), x∈Z represents “x is an integer” and represents movement within a range of 0 ≦ x <x _max , so x = {0, 1, 2,. x _max-1 } can be taken.

Similarly, a range of values Z {x0 _max } that can be taken by the position x0 in the main scanning direction, a range of values Z {y0 _max } that can be taken by the position y0 in the sub-scanning direction, and a range of values that can be taken by the feature amount extraction result C Z _{{C max},} low concentration determination result D is possible range of values _{Z {D max},} quantization threshold Thr [C, D] [x , y, i] can take a range of values Z {N}, Value range Z {Bn} that blue noise Bn [k] can take, value range Z {Bn _max } that index k of Bn [k] can take, blue noise addition selection Fbn [C, D] [x, y , I] also defines a range of possible values Z {Fbn},
Z {x0 _max } = {x0εZ; 0 ≦ x0 <x0 _max }
Z {y0 _max } = {y0εZ; 0 ≦ y0 <y0 _max }
Z {C _max } = {CεZ; 0 ≦ C <C _max }
Z {D _max } = {DεZ; 0 ≦ D <D _max },
Z {N} = {DinεZ; 0 ≦ Din <N−1},
Z {Bn} = {± 1}
Z {Bn _max } = {kεZ; 0 ≦ k <bn _max }
Z {Fbn} = {0, 1}
And so on.

In the present embodiment, C _max = D _max = 4, but is not limited to this value, and may be changed as necessary.

  FIG. 17 illustrates the configuration of the quantization threshold Thr [C, D] [x, y, i].

Quantization threshold values Thr [C, D] [x, y, i] of the main scanning direction size x _max and the sub scanning direction size y _max are prepared for M−1 levels, which is the feature amount extraction result Chr (x 0 , Y0) (= C) εZ {C _max }, and four types corresponding to the low density determination result Dns (x0, y0) (= D) εZ {D _max }, quantization It is set in the threshold value table unit 4142. Since this is a quantization threshold for one color, actually, four colors are set.

Quantization threshold Thr [C, D] [x , y, i] ∈Z {N} (C∈Z {C max}, D∈Z {D max} x∈Z {x max}, y∈Z {y _max }, i∈Z {M−1}) corresponding to each threshold value, blue noise addition selection Fbn [C, D] [x, y, i] ∈Z {Fbn} (C∈Z {C _max }) _{, D∈Z {D max} x∈Z {} x max}, y∈Z {y max}, i∈Z {M-1}) is set to blue noise adding selection table section 4144.

  The quantization threshold selection unit 4141 and the blue noise addition selection unit 4143 are respectively applied to the pixel of interest (x0, y0) based on the feature amount extraction result C and the low density determination result D, and the quantization threshold Thr [C, D]. [X, y, i] is selected from the quantization threshold table 4142, and the blue noise addition selection flag Fbn [C, D] [x, y, i] is selected from the blue noise addition selection table 4144.

  The gradation processing will be described by taking 4-bit error diffusion processing as an example.

  The quantization threshold value generator 1140 generates quantization threshold values 1 to 15 (th1 to th15). The relationship between the quantization thresholds is: quantization threshold 1 (th1) ≦ quantization threshold 2 (th2) ≦ ... ≦ quantization threshold 15 (th15).

  The quantizer 1121 compares the input image data with the quantization thresholds th1 to th15. When the value is larger than th15, the quantizer 1121 is “16”, when it is larger than th14, “15”. In the following description, it is assumed that 4-bit (16 gradations) quantized data 1101 having a value of “0” is output when smaller than 1 ”and th1.

  The error integrating unit 4149 calculates a diffusion error to be added to the next target pixel from the quantization error data stored in the error buffer 4148. In this embodiment, the error integration unit 4149 calculates diffusion error data using an error diffusion matrix having a size of 3 pixels in the sub-scanning direction and 5 pixels in the main scanning direction as shown in FIG. In FIG. 18, the mark * corresponds to the position of the next pixel of interest, and a, b,. . . , K, l are coefficients corresponding to the positions of the 12 processed pixels in the vicinity (the sum is 32). In the error diffusion matrix unit 1125, a value obtained by dividing the product sum of the quantization error for the 12 processed pixels and the corresponding coefficients a to l by 32 is sent to the error addition unit 1125 as a diffusion error for the next pixel of interest. give.

  FIG. 19 illustrates a block diagram of the feature amount extraction / low density determination unit 4122.

  The feature amount extraction unit 4122 performs edge detection of the image data Din (x0, y0). In this embodiment, the feature amount extraction unit 4122 outputs a level as an output of the feature amount extraction result Chr (x0, y0) for the target pixel (x0, y0). 2 bits of edge data representing an edge level from 3 (edge degree maximum) to level 0 (non-edge) are output.

  For example, the feature amount is extracted using four types of primary differential 5 × 5 differential filters 1 to 4 shown in FIG. 20 and the secondary differential filter shown in FIG. 21, and the main scanning direction, the sub-scanning direction, and the main scanning. Edge amount is detected in four directions inclined ± 45 ° from the direction, the edge amount with the maximum absolute value is selected, and the absolute value of the edge amount is set to the four level edge levels from level 0 to level 3. Quantize to output.

  The low density determination unit 4123 compares a predetermined threshold value with the input image data Din, and outputs the low density determination result Dns (x0, y0) for the target pixel (x0, y0) with the lowest density being 0 and the highest. A value with a density of 3 or the like is output.

  The error diffusion matrix unit 1124 calculates a diffusion error to be added to the next target pixel from the quantization error data stored in the error storage unit 1123. In this embodiment, the error diffusion matrix unit 1125 calculates diffusion error data using an error diffusion matrix having a size of 3 pixels in the sub-scanning direction and 5 pixels in the main scanning direction as shown in FIG.

  In FIG. 18, the mark * corresponds to the position of the next pixel of interest, and a, b,. . . , K, l are coefficients corresponding to the positions of the 12 processed pixels in the vicinity (the sum is 32). In the error diffusion matrix unit 1125, a value obtained by dividing the product sum of the quantization error for the 12 processed pixels and the corresponding coefficients a to l by 32 is sent to the error addition unit 1125 as a diffusion error for the next pixel of interest. give.

  The image feature extraction unit 1130 includes an edge detection unit 1131 and a region expansion processing unit 1132. The edge detection unit 1131 performs edge detection of the image data 1100, and outputs 4-bit edge data representing edge levels from level 0 (maximum edge degree) to level 8 (non-edge) in this embodiment. More specifically, for example, the four types of primary differential 5 × 5 differential filters 1 to 4 shown in FIG. 20 and the secondary differential filter of FIG. 21 are used, and the main scanning direction, sub-scanning direction, and main scanning direction are used. The edge amount is detected in four directions inclined by ± 45 ° from the edge, the edge amount having the maximum absolute value is selected, and the absolute value of the edge amount is set to four edge levels from level 0 to level 3. Quantize and output.

  The region expansion processing unit 1132 performs region expansion processing with a width of 7 pixels on the edge detected by the edge detection unit 1131. The region expansion processing unit 1132 refers to the edge data output from the edge detection unit 1131 and generates 7 pixels around the target pixel. The minimum edge level (maximum edge degree) in the 7 pixel area (range of 3 pixels before and after in the main scanning direction and 3 pixels before and after in the sub-scanning direction) Output as edge data. This edge data is given to the quantization threshold value generator 1140.

  The quantization threshold generation unit 1140 generates a quantization threshold that periodically oscillates in the image space with a vibration width corresponding to the edge level represented by the edge data output from the region expansion processing unit 1132. This is given to the quantizer 1121 of the quantization processing unit 1120. The dither threshold value generation unit 1141 and the coefficient (0 to 3) corresponding to the edge level indicated by the edge data are output to the dither threshold value generation unit 1141. A multiplier 1142 for multiplying and an adder 1143 for adding a fixed value to the output value of the multiplier 1142.

  As an example, the dither threshold value generator 1141 is arranged so as to grow the lines in order from the smallest threshold values 1 to 6 as shown in FIG. 22A (1 is the minimum, 6 is the maximum). The dither threshold value that vibrates periodically from 1 to 6 on the image plane is output.

  Here, the same threshold value is used for pixels having the same value. The dither threshold period corresponds to 192 Lpi in the case of 600 dpi image formation. Such a dither threshold value generation unit 1141 can be easily realized by a ROM that stores the dither threshold value matrix, a counter that counts main and sub-scan timing signals of image data, and generates a read address of the ROM. .

  Here, when the pixels set to 1 in FIG. 22A are arranged in the main scanning direction, this means that a dot in which two pixels are arranged in the main scanning direction is formed first. In this way, for the purpose of stable dot formation, two pixels of one value, which is a writing level with less energy, are arranged.

  The screen angle and line growth direction in this case are shown in FIG. The growth direction of the line is indicated by “direction 1 in which the line grows” in the drawing.

  The multiplying unit 1142 gives a coefficient 3 when the edge level indicated by the edge data from the image feature extracting unit 1130 is level 0 (non-edge), a coefficient 2 when it is level 1, a coefficient 1 when it is level 2, and a level 3 At the time of (maximum edge degree), the coefficient 0 is multiplied by the output value of the dither threshold value generator 1141.

  If the quantized data 1101 of the image processing apparatus configured as described above is given to, for example, an electrophotographic printer or the like, the resolution of characters, image change points, a relatively low number of halftone dot image portions, and the like can be obtained. In addition, a photograph, a portion with little change in the image, a halftone dot image with a high number of lines, etc. are smooth and stable, and it is possible to form a high-quality image in which these regions are aligned without a sense of incongruity. This will be described below.

  The quantization threshold generated by the quantization threshold generation unit 140 is fixed at a portion where the change is steep and the edge level is level 3 (edge degree is the highest) in the image, such as the edge of a character or line drawing. Since the processing unit 1120 performs a quantization process by a pure error diffusion method using a fixed threshold value, an image with high resolution can be formed.

  In a portion where the edge degree is low, such as a flat portion of a photograph or image, the oscillation width of the quantization threshold generated by the quantization threshold generation unit 1140 is large. Therefore, the quantization processing of the quantization processing unit 1120 is dithered. Processing is performed, and the image data is converted to halftone dots with a dither threshold period. Since a dither threshold matrix having a threshold arrangement as shown in FIG. 22A is used to generate a quantization threshold, the center of the line grown along the screen angle within the dither threshold period as the density level of the image data increases. The output dots grow in a spiral shape from the part.

  FIG. 22B shows the order in which the lines grow and the magnitude relationship between the quantization thresholds as another example of FIG. 22A. Although the order of pixels formed when a line grows is different from the case of FIG. 22A, even if such a value is set, a line along the screen angle is formed and a smooth image is formed. You can

As shown in FIG. 24, a region determined as a character region based on the values of the high density threshold value, primary differential feature value extraction threshold value 1, 2 and secondary differential feature value extraction threshold value 1 and 2 (hatched portion in the figure) Can be adjusted. For example, by setting any threshold value low, the area determined as a character is enlarged (FIG. 25).
From the determination area by (primary differential determination threshold 1 & high concentration determination area + secondary differential determination threshold 1),
A region excluding a determination region by (primary differentiation determination threshold 2 & high concentration determination region + secondary differentiation determination threshold 2) is used.

  The quaternary chart of FIG. 26 shows a conceptual diagram showing the relationship between the UCR amount and the printer γ characteristic in the automatic color determination mode.

  In FIG. 26, the horizontal axis of the first quadrant is an 8-bit YMC signal that is an output after color space conversion processing at the time of copying, and Y (Yellow component) = M (Magenta component) = C (Cyan component) Represents the magnitude of the signal. The maximum value is 0 and the maximum value is 255. The horizontal axis indicates the amount of K (Black) component after UCR processing.

  The second quadrant is a process from after the UCR process to before the printer γ conversion (2) process 413. Here, the gradation is not changed.

  The third quadrant represents the characteristics of the printer γ conversion (2) process.

  The fourth quadrant shows the relationship between the characteristic after the conversion process by the printer γ conversion (2) and the amount of Y = M = C, that is, the UCR process 100%.

  In the first quadrant, I-1) is UCR 100%, I-2) is UCR 80%, I-3) is skeleton black 1, and I-4) is skeleton black 2. I-3) is an example in which Y = C = M = 25 (about 10%) is replaced with the K component, assuming that Y = M = C = 255.

  On the other hand, I-4) is an example in which the UCR amount is replaced from Y = M = C = 0 (0%) and coincides with I-3) when Y = M = C = 51 (20%). is there. For I-1), UCR 100% is often selected for a character document because black characters are easily reproduced as black for a color document. It can also be called output characteristics when a monochrome original is copied. I-2) may be used for photographic originals. However, in the case of originals such as skin color, there is an effect such as poor stereoscopic effect. Therefore, the skeleton black 1 like I-3) is used. Thus, it is preferable to replace the UCR amount. I-4) has intermediate characteristics between I-2) and I-3).

(Example of Claim 1)
When the printer γ conversion characteristic of the third quadrant (2) processing is III-1) linear, I-1) to I-3) are respectively IV of the fourth quadrant IV) -1 to IV-3). I-1) In the case of UCR 100%, IV-1) is also linear and the gradation characteristics do not change. In the case of I-2) UCR 80%, as in IV-2), the entire concentration is as low as 80% with respect to IV-1) UCR 100%. I-3) In the case of skeleton black 1, as shown in IV-3), it is reproduced from Y = M = C = 25 (about 10%), and the range of Y = M = C = 0-25 is a K component. Therefore, when only the K component image data is used in the monochrome copy and the YMC component is not used, a copy output in which the highlight (low image density) area is not reproduced (is skipped) can be obtained.

  Therefore, as shown in FIG. 27, when it is determined that the document is a monochrome document, the conversion characteristics of the printer γ conversion (2) are changed according to the setting of the UCR amount (vertical axis in the table) III-1) to III-4. ). On the other hand, if it is determined that the document is a color document, III-1) linear characteristics are used (example of claim 2).

  As shown in the image quality mode in FIG. 27, the UCR amount is changed in accordance with the image quality mode that can be selected by the operation unit (first embodiment of claim 5).

(Example of Claim 6)
In the first quadrant of the quaternary chart shown in FIG. 26, the feature quantity I is the above-described high density determination feature quantity extraction threshold value, and when the value is Y = M = C = (a), I -1) to I-4), the K component values correspond to the values a-1), a-2), a-3), and a-2), respectively. .

  The primary differential feature value extraction threshold value and the secondary differential feature value extraction threshold value correspond to the difference and difference of the K components generated by the UCR process, respectively. Although the degree of change is small, changes are made with the same tendency. The horizontal axis in FIG. 28 is the UCR amount, and the vertical axis is the feature amount extraction threshold. When a low UCR amount is used, a lower feature amount extraction threshold is selected as compared to UCR 100% as shown in the monochrome determination.

(Example of Claim 3)
As shown in the operation unit screen of FIG. 5, in the automatic color selection, the items “color priority” and “black and white priority” can be selected in the item “color priority setting”. Example).

  This is to switch the UCR amount in the color correction process described above. As an example, the UCR amount of I-3) in FIG. 26 is used when “color priority” is selected, and the ICR) is used when monochrome priority is given. According to each UCR amount, the conversion characteristic and feature amount of the printer γ conversion (2) described in FIG. 27 are set (Example of claim 4).

  As shown in FIG. 29, it is determined whether the determination result of the automatic color selection is full color (step 1). If it is full color, the feature amount extraction threshold for full color (high density determination feature amount extraction threshold, first derivative) Feature value extraction threshold 1, 2 and secondary differential feature value extraction threshold 1 and 2) are set (step 2). If monochrome, the feature value extraction threshold for monochrome (high density extraction threshold, primary differentiation) Feature amount extraction threshold 1, 2, and second derivative feature amount extraction threshold 1, 2) are set.

(Second Embodiment of Claim 1)
FIG. 30 is a diagram in which a graph of I-5) skeleton black 3 is newly added in the same quaternary chart as FIG. 26 described above.

  The characteristic amount extraction threshold and the conversion characteristics of printer γ conversion (2) when the image quality mode is the character / photo mode will be described with reference to FIG.

  When the UCR amount setting of the character part in the character / photo mode is I-1) and the photo part setting is I-3), the feature amount extraction threshold is set to full color even if the color determination result of the document is monochrome. However, a-1) may be used.

  In this case, if the feature amount extraction threshold value is a-1) in the monochrome mode, the density of the photographic part is lower than IV-1) when compared to the linear mode, so that the gradation processing and printer γ conversion are performed. This makes it easier to determine that the process is a photo-side process, which is closer to the reproducibility when the user designates a monochrome copy in the operation unit.

  On the other hand, the setting of the character portion UCR amount in the character / photo mode may be set as I-5), and the setting of the photo portion may be set as I-3). This is because black characters can be easily colored, but the color reproducibility of a map document or the like is improved. In this case, if the feature amount extraction threshold value in the monochrome mode is changed to a-2), the character portion is determined in the feature amount extraction process / low density determination 412, and the user makes a monochrome copy with the operation unit. It is possible to approach the reproducibility when specifying.

  A block diagram of the image reading system will be described with reference to FIG.

  The document is irradiated by the exposure lamp shown in FIG. 33, and the reflected light is color-separated and read by an RGB filter of a CCD (Charge Coupled Device) 5401 and amplified by an amplification circuit 5402 to a predetermined level.

  A CCD driver 5409 supplies a pulse signal for driving the CCD. A pulse source necessary for driving the CCD driver 5409 is generated by a pulse generator 5410. The pulse generator 5410 uses a clock generator 5411 made of a crystal oscillator or the like as a reference signal.

  The pulse generator 5410 supplies necessary timing for the sample hold (S / H) circuit 5403 to sample and hold the signal from the CCD 5401. The analog color image signal sampled and held by the S / H circuit 5403 is digitized into an 8-bit signal (an example) by the A / D conversion circuit 5404.

  The black correction circuit 5405 reduces variations in the black level (electric signal when the amount of light is small) between CCD chips and between pixels, and prevents streaks and unevenness in the black portion of the image. The shading correction circuit 5406 corrects the white level (electric signal when the amount of light is large). The white level corrects variations in sensitivity of the irradiation system, the optical system, and the CCD 5401 based on white data when the scanner 121 is moved to a uniform white plate position and irradiated. FIG. 34 shows a conceptual diagram of white correction / black correction image signals.

  A signal from the shading correction circuit 5405 is processed by the image processing unit 5407 and output from the printer 412. The above circuit is controlled by the CPU 5414 and stores data necessary for control in the ROM 5413 and the RAM 5415.

  The CPU 5414 communicates with a system controller 419 that controls the entire image forming apparatus through a serial I / F. The CPU 5414 controls a scanner drive device (not shown) and controls the drive of the scanner 121.

  The amplification amount of the amplification circuit 5402 is determined so that the output value of the A / D conversion circuit 5404 becomes a desired value for a specific document density. As an example, a document having a document density of 0.05 (reflectance of 0.891) during normal copying can be obtained as an 8-bit signal value of 240 values.

  On the other hand, at the time of shading correction, the gain is lowered to increase the sensitivity of shading correction. The reason for this is that with an amplification factor during normal copying, if there is a large amount of reflected light, an 8-bit signal that exceeds 255 values will saturate to 255 values, resulting in errors in shading correction. This is because it occurs.

  FIG. 35 is a schematic diagram in which the read signal of the image amplified by the amplifier circuit 5402 is sampled and held by the S / H circuit 5403. The horizontal axis represents the time for the amplified analog image signal to pass through the S / H circuit 5403, and the vertical axis represents the magnitude of the amplified analog signal. An analog signal is sampled and held at a predetermined sample and hold time 5501, and a signal is sent to the A / D conversion circuit 5404.

  The figure shows an image signal obtained by reading the above-described white level. The amplified image signal is, for example, 240 values as the value after A / D conversion at the time of copying and 180 values at the time of white correction. It is an example of an image signal.

FIG. 2 is a schematic diagram for explaining the outline of the mechanism of the copying machine main body 101. Schematic for demonstrating the outline of a control system. The block diagram which showed an example of the laser modulation process. The block diagram which showed an example of the image processing flow. Schematic which showed an example of the whole operation part. Schematic which showed an example of the liquid crystal screen of the whole operation part. The block diagram which showed an example of the adaptive edge emphasis process. Schematic which showed the specific example of the smoothing coefficient of the smoothing filter process 1101, and a Laplacian filter. Schematic which showed the specific example of the edge amount detection filter. The graph figure which showed the example of the table. FIG. 6 is a block diagram showing an example of a color correction UCR process 406. FIG. 3 is a block diagram showing an example of the internal configuration of the image processor 1204. The figure explaining the structure of the SIMD type image data processing part 1500 and the sequential image data calculation processing part 1507. Schematic for demonstrating a pixel line. Explanatory drawing which shows schematic structure of a SIMD type | mold processor. The block diagram for demonstrating a gradation processing system. The block diagram which illustrated the structure of quantization threshold value Thr [C, D] [x, y, i]. Schematic which showed an example of the error diffusion matrix. FIG. 6 is a block diagram showing an example of a feature amount extraction / low density determination unit 4122. Schematic which showed an example of the primary differential filter. Schematic which showed an example of the secondary differential filter. Schematic which showed an example, such as a dither threshold value matrix. Schematic for demonstrating a screen angle and the growth direction of a line. Schematic for demonstrating feature-value extraction. Schematic which showed an example of the selection level of a feature-value extraction threshold value. FIG. 4 is a conceptual diagram illustrating an example of a relationship between a UCR amount and a printer γ characteristic in an automatic color determination mode. The chart which showed an example of characteristic change at the time of judging with a monochrome manuscript. Schematic which showed an example of the relationship between UCR amount and a feature-value extraction threshold value. The flowchart which showed an example of the process according to the determination result of automatic color selection. The conceptual diagram which showed the case where the graph of I-5) skeleton black 3 was newly added with the same 4 element | chart chart as FIG. Schematic which showed an example of the conversion characteristic of a feature-value extraction threshold value and printer gamma conversion (2). The block diagram which showed the structural example of the image reading system. Schematic which showed an example of the scanner optical system. The conceptual diagram for demonstrating the image signal of white correction | amendment and black correction | amendment. FIG. 6 is a schematic diagram illustrating a state in which an image read signal amplified by an amplifier circuit 5402 is sampled and held by an S / H circuit 5403.

Explanation of symbols

130 Main control unit 454 Image processor

Claims (7)

Image reading means for reading a document and outputting image data;
Color discriminating means for discriminating whether the original is a color original or a monochrome original based on the image data read by the image reading means;
Color correction means for generating output image data composed of achromatic components and chromatic components for output by the image output means from the image data read by the image reading means;
Storage means for storing the image data after the color conversion;
Image output means for outputting the stored image data,
If it is determined from the read image data that the document is a color document, an image is output based on the chromatic component of the achromatic component of the stored image data;
An image forming apparatus for outputting the stored achromatic component image data when the original is determined to be a monochrome original from the read image data;
Feature quantity extraction means for extracting the feature quantity of the image data after the color conversion;
A gradation characteristic converting means for converting a gradation characteristic based on a feature amount extraction result of the image data;
Based on the feature value extraction result of the image data, the threshold value applied by the gradation characteristic conversion means is either a threshold value with a periodically varying amplitude, or a threshold value with a small or no variation amplitude. As well as switching
An image processing apparatus, wherein the feature amount extraction threshold of the feature amount extraction unit and the gradation characteristic of the gradation characteristic conversion unit are switched based on the determination result of the color determination unit. Means for setting an image quality mode;
The characteristic value extraction threshold to be applied to the achromatic color component after color correction and the gradation characteristic of the gradation characteristic conversion unit are set from the image quality mode and the color determination result. The image forming apparatus according to 1. A means for setting an achromatic color component amount after color correction;
Based on the set amount of the achromatic color component amount after the previous color correction and the color determination result, the feature amount extraction threshold to be applied to the achromatic color component after the color correction and the gradation property of the gradation property conversion means are obtained. 3. The image forming apparatus according to claim 1, wherein the image forming apparatus is set.   When a small amount of achromatic component is selected, the feature amount extraction threshold is lowered so that it can be easily determined as a character area, and further, the concentration of the achromatic component after gradation conversion is increased. The image forming apparatus according to claim 3.   5. The image forming apparatus according to claim 1, wherein the achromatic color component amount after color correction is an operation unit.   The feature amount extraction threshold is a high density determination threshold, a primary differential extraction threshold for data after primary differential filter processing, or a secondary differential extraction threshold for image data after secondary differential filter processing. Alternatively, the image forming apparatus according to claim 2, claim 3, claim 4, or claim 5. Means for accumulating image data determined to be a color document or a monochrome document;
The determination result as to whether the document is a color document or a monochrome document is stored as bibliographic information. 6. The document according to claim 1, wherein the document is stored as bibliographic information. Item 7. The image forming apparatus according to Item 6.