JP5838733B2 - Image forming apparatus, image forming method, image forming program, and recording medium - Google Patents

Description

The present invention relates to an image forming apparatus, an image forming method, an image forming program, and a recording medium, and more particularly to an image forming apparatus, an image forming method, an image forming program, and a recording medium for realizing highly accurate gradation correction. .

Conventionally, as represented by a laser printer or the like, in an image forming apparatus in which pixels (dots) of a minimum printing unit are quantized into two states of ON / OFF, when expressing an intermediate density, per unit area Image processing called gradation processing that performs intermediate density expression by changing the area ratio of ON pixels is used.

In the above gradation processing, for example, by combining a plurality of pixels, halftone processing that simulates a halftone dot whose area changes according to the input gradation, or a screen line that generates a screen line in a specific direction. There are line gradation processing, error diffusion processing for uniformly increasing the area ratio of ON dots, and the like. Furthermore, there are various gradation patterns depending on the parameters such as the number of halftone dots per unit area in halftone processing, the number of lines per unit area in line gradation processing, and the dither matrix coefficient in error diffusion processing. To do. Since the resolution and gradation differ depending on the gradation pattern, a plurality of gradation patterns are separated and used by one image forming apparatus for different image types such as characters, line drawings, and photographs.

By the way, the area of one pixel, which is the basis of the gradation pattern, is designed to be strictly larger than one pixel so that the solid image covers the entire area. This fat portion of the pixel (dot) is called dot gain. Since the dot gain slightly changes depending on the new and old state of the image forming apparatus and the environmental conditions of temperature and humidity, the density gradation characteristic with respect to the input value changes sensitively, and the change in the characteristic varies depending on the difference in gradation pattern. Therefore, in order to always obtain a constant image reproduction, it is necessary to perform calibration for each gradation pattern. In this calibration, in an electrophotographic image forming apparatus such as a copying machine or a printer, a plurality of correction patches having different gradation patterns and area ratios are generated on a photoconductor and transferred to an intermediate transfer belt or the like. At the same time, the density of the correction patch is measured by a density sensor and compared with a predetermined target value to correct the gradation correction table.

It is not desirable to generate and measure correction patches for all area ratios in all gradation patterns from the viewpoint of an increase in time required for calibration and toner consumption. Therefore, gradation characteristics for each gradation pattern (characteristics of toner density values with respect to the area ratio of ON pixels) are generated by measuring and correcting patches with fewer gradation patterns and area ratios, and interpolating the measured values. Is estimated.

For example, there are the following conventional techniques for reducing the number of area ratios to be measured.
In Patent Document 1, spline interpolation is performed on the measured density value to estimate the overall tone characteristics. In Patent Document 2, other gradations are estimated using correspondence relationships (formulas and models) generated in advance from a specific area ratio, and the estimated values are interpolated by linear interpolation or quadratic curve interpolation. Estimate the overall tone characteristics. The following conventional techniques exist for reducing the number of gradation patterns.
In Patent Document 3, by correcting the gradation characteristics of a pattern having a wide gradation width (2 × 2 halftone dots) and estimating the gradation characteristics of a pattern halftone having a narrow gradation width (1 × 1 halftone dot), A technique for reducing the processing man-hour is disclosed.
Further, in Patent Document 4, gradation characteristics are expressed by a model (function) with parameters, and parameters of other unmeasured gradation patterns are estimated from parameters obtained from the measured gradation patterns. The number of gradation patterns required for measurement is reduced.
Further, in Patent Document 5, using a regression model between patches of the same area ratio of different gradation patterns, the density of another gradation pattern is estimated from the measurement value of one gradation pattern, and the gradation required for the measurement The number of patterns is reduced.

In the conventional techniques as described above, the methods disclosed in Patent Documents 1 to 5 reduce the number of correction patches generated on the intermediate transfer belt in order to reduce processing time and toner consumption. There is a problem that the estimation accuracy of the gradation characteristic is lowered. In particular, if the number of gradation patterns and the number of gradations are reduced at the same time, there is a problem that the estimation accuracy of the gradation characteristics is greatly degraded.

In view of this, the present invention provides an image forming apparatus, an image forming method, an image forming program, and an image forming apparatus for minimizing deterioration in estimation accuracy of gradation characteristics even when the number of gradation patterns to be measured and the number of gradations are reduced. An object is to provide a recording medium.

In order to solve the above-mentioned problems, the present invention estimates the gradation characteristics based on the measured density value of the patch of the gradation pattern formed on the image carrier as claimed in claim 1, an image forming apparatus for generating a tone correction data from the gradation characteristic of the gradation characteristics and objectives, the first-order to estimate the gradation characteristic of the gradation pattern from the density of the patch of the measured gradation pattern a tone estimation unit, a first gradation pattern between estimating means for estimating the tone characteristic of the gradation pattern different from the gradation pattern from the tone characteristic of the gradation pattern estimated by the first gradation estimation means, from the density of the patch of the gradation pattern the measurement, a second tone pattern between estimating means for estimating the concentration of the different gradation pattern area ratio and the area ratio of the gradation pattern the measurement, the second floor the different estimated between tone pattern estimator From the estimated concentration of the tone pattern, the different a second tone estimation means for estimating the tone characteristic of the gradation pattern, the gradation characteristics and estimated by the first gradation pattern between estimating means said second tone and a weighted addition means you weight the summing and estimated gradation characteristics estimating means, a gradation characteristic of said different tone patterns that the pressurized heavy summing means obtained by weighted addition is the estimated It is characterized by gradation characteristics .

Further, the present invention is as claimed in claim 2, in the image forming apparatus according to claim 1, wherein the weight adding means, taking an average of two Kaichotoku property that the pressurized heavy adding means for weighted addition It is characterized by.
Further, the present invention is as claimed in claim 3, in the image forming apparatus according to claim 1, the fitness calculating means for calculating the two Kaichotoku of goodness of fit the weight adding means is weighted addition further comprising, among the two Kaichotoku property, and performs weighted addition of the weight of the higher the goodness of fit 1, the other as 0.

Further, the present invention is as claimed in claim 4, in the image forming apparatus according to claim 1, the fitness calculating means for calculating the two Kaichotoku of goodness of fit the weight adding means is weighted addition further comprising, the two Kaichotoku property, and performing weighted addition with weighting proportional to the goodness of fit.
Further, according to the present invention, as described in claim 5, in the image forming apparatus according to claim 3 or 4, in the fitness calculation unit, the fitness is a monotonically increasing gradation characteristic, smoothness. Now, it is calculated by any one or a combination of appearance probabilities based on past measurement data.

Further, the present invention is as claimed in claim 6, estimates the tone characteristic based on the measured value of the density of the patch of the gradation pattern formed on an image bearing member, estimated tone characteristic and goals an image forming method of generating gradation correction data from the gradation characteristic, a first gradation estimation step of estimating a gradation characteristic of the gradation pattern from the density of the patch of the measured tone pattern, wherein a first gradation pattern between estimation step of estimating the tone characteristics of the different gradation patterns with gray scale pattern from the tone characteristic of the gradation pattern estimated by the first gradation estimation step, the gradation pattern the measurement from the density of the patch, and a second tone pattern between estimation step of estimating the concentration of the different gradation pattern area ratio and the area ratio of the gradation pattern the measurement, by said second tone pattern between estimating step the different estimated From the estimated concentration of the tone pattern, the different a second tone estimation step of estimating a gradation characteristic of the gradation pattern, the estimated gradation characteristics in estimating step between the first gradation pattern the second tone and a weighted addition steps you weighted the summing has been the tone characteristic estimated in estimation step, a gradation characteristic of said different tone patterns the pressurized heavy adding step is obtained by weighted addition is the estimated It is characterized by gradation characteristics .

The present invention, as set forth in claim 7, in the image forming method according to claim 6, wherein the weight adding step, to take the average of two Kaichotoku cause the pressurized heavy adding step is weighted addition Features.
The present invention, as set forth in claim 8, in the image forming method according to claim 6, further fitness calculating step of calculating a two Kaichotoku of goodness of fit the weight adding step is weighted addition It includes, among the two Kaichotoku property, and performs weighted addition of the weight of the higher the goodness of fit 1, the other as 0.

The present invention, as set forth in claim 9, in the image forming method according to claim 6, further fitness calculating step of calculating a two Kaichotoku of goodness of fit the weight adding step is weighted addition provided, the two Kaichotoku property, and performing weighted addition with weighting proportional to the goodness of fit.
Furthermore, according to the present invention, as described in claim 10, in the image forming method according to claim 8 or 9, in the fitness calculation step, the fitness is a monotonically increasing gradation characteristic or smooth. Now, it is calculated by any one or a combination of appearance probabilities based on past measurement data.

In the image forming apparatus according to claim 1, variation in estimation accuracy due to a difference in gradation characteristics and an estimation method thereof is reduced by combining two estimation results having different order of gradation pattern estimation and gradation estimation. Therefore, the estimation accuracy of gradation characteristics can be improved. Therefore, a highly accurate image can be provided.

1 is a diagram illustrating an apparatus configuration example of an image forming apparatus according to the present invention. FIG. 2 is a diagram illustrating a functional configuration example of an image forming apparatus according to the present invention. It is a figure which shows an example of the image processing procedure which concerns on this invention. It is a figure which shows an example of the patch image formed on the photoconductor which concerns on this invention. It is a figure which shows an example of the hardware constitutions which can implement | achieve the image formation process in this invention. It is a figure which shows the structure 1 of the gradation correction data generation means which concerns on this invention. It is a figure which shows the gradation correction data generation process example 1 which concerns on this invention. It is a figure which shows Example 1 of the gradation characteristic estimation which concerns on this invention. It is a figure which shows Example 2 of the gradation characteristic estimation which concerns on this invention. It is a figure which shows the structure 2 of the gradation correction data generation means which concerns on this invention. It is a figure which shows the gradation correction data generation process example 2 which concerns on this invention. It is a figure which shows the structure 3 of the gradation correction data generation means which concerns on this invention. It is a figure which shows the gradation correction data generation process example 3 which concerns on this invention.

Hereinafter, embodiments of the present invention will be described with reference to FIGS. 1 to 13 regarding an image forming apparatus, an image forming method, an image forming program, and a recording medium.

<Basic part>
FIG. 1 is a diagram illustrating a configuration example of an apparatus configuration example of the image forming apparatus according to the present exemplary embodiment. As an example of the image forming apparatus described below, for example, a schematic configuration of a 600 dpi color laser printer is shown, but the image forming apparatus according to the present invention is not limited to this. A printer engine 10 as an image forming apparatus shown in FIG. 1 includes a photosensitive member (photosensitive member) 11, an intermediate transfer member 12, a developing device 13, a charger 14, an exposure device 15, a reflection luminance sensor 16, and a controller. 17, a transfer roller 18, a cassette unit 19, a fixing device 20, and an operation panel (operation means) 21.

The photoconductor 11 shown in FIG. 1 has a belt shape, for example, and rotates at a predetermined timing and speed in the direction of arrow A shown in FIG.
The intermediate transfer member 12 transfers toner images of four different colors formed one by one on the photosensitive member 11 one by one for each rotation. That is, as an example, the intermediate transfer body 12 employs an intermediate transfer body system that forms one color image by four rotations.

In FIG. 1, the belt-shaped photoconductor 11 is disposed at the center of the printer engine 10, and an intermediate transfer body 12 is disposed in contact with the photoconductor 11 on one surface thereof.

Around the photoconductor 11, the toner adhesion amount on the photoconductor 11, which is a process component that forms a toner image on the photoconductor 11 along the rotation direction, is the developer 13, the charger 14, the exposure device 15. A reflection luminance sensor 16 to be detected is arranged. On the side of the casing of the printer engine 10, a base of a controller 17 is installed as a control means for controlling the entire functional configuration of the printer engine 10 indicated by broken lines.

The developing unit 13 includes four developing units (a black developing unit 13K, a yellow developing unit 13Y, and a magenta developing unit 13M) that store toners of different colors on the side opposite to the intermediate transfer member 12 in the photoconductor 11 that is elongated vertically. , Cyan developing devices 13C) are vertically stacked. The developing unit 13 attaches an image visualization agent such as toner corresponding to each color component of black (K), yellow (Y), magenta (M), and cyan (C) to the photoreceptor 11.
The charger 14 uniformly charges the surface of the photoconductor 11.
The exposure unit 15 exposes the surface of the charged photoconductor 11 by irradiating laser light to form an electrostatic latent image.

That is, the photoconductor 11 to which the image visualization agent corresponding to each color is attached performs transfer of each color to a predetermined position on the intermediate transfer body 12 that rotates at a predetermined timing and speed. As a result, a visible image (color image) is formed on the intermediate transfer body 12.
The reflected luminance sensor 16 emits luminance detection light to a predetermined area of the photoconductor 11 and detects (receives) the reflected light. Note that the luminance detection signal from the reflection luminance sensor 16 is converted into a density value for image output by a conversion table or the like stored (mounted) in advance in the controller 17. In this sense, the reflected luminance sensor 16 has a function as a density detecting means. Thus, the accuracy of image formation can be grasped by detecting the adhesion amount of the image visualization agent on the photoconductor 11 by the reflection luminance sensor 16.

Around the intermediate transfer body 12, a transfer roller 18, which is a process component for forming a toner image and transporting a printing medium (recording medium) such as paper, is disposed. Specifically, the transport path for transporting the paper is configured to discharge from the cassette unit 19 such as a paper cassette disposed at the lower part of the main body to the upper surface of the main body through the outer side of the intermediate transfer body 12. A transfer roller 18 that presses a printing medium such as paper against the intermediate transfer body 12 to transfer a visible image (color image) formed on the intermediate transfer body 12 to the paper and conveys the paper in a predetermined direction. A fixing device 20 is provided for fixing the visible image (toner image) transferred from the intermediate transfer body 12 to the printing medium by passing the printing medium while supplying heat. As another configuration, for example, a sheet neutralizer (not shown) that neutralizes the print medium may be provided at a predetermined position.

An operation panel (operation means) 21 as a user interface having a gradation pattern selection means is provided facing the outside of the housing. A manual calibration command or the like by the user is sent to the controller 17 through the operation panel 21.

<Image forming apparatus: functional configuration example>
Next, a functional configuration example in the image forming apparatus (printer engine) 10 will be described with reference to the drawings. FIG. 2 is a diagram illustrating an example of a functional configuration as a printer engine of the image forming apparatus according to the present invention. The image forming apparatus 10 shown in FIG. 2 includes an input unit 31, an output unit 32, a storage unit 33, an image expansion unit 34, a color correction unit 35, a reference image generation unit 36, and a reference image holding unit 37. 4-color separation and holding means 38, gradation pattern selection means 39, color selection means 40, gradation correction data generation means 41, gradation correction means 42, gradation processing means 43, and density detection means 44. And an image forming unit 45, a transmission / reception unit 46, and a control unit 47.

The input unit 31 receives an input of each instruction such as an instruction to execute an image forming process from the user, an instruction to read or write predetermined data from the storage unit 33, and the like. Note that the input unit 31 includes, for example, an input interface such as a touch panel, and may be a pointing device such as a keyboard or a mouse, a voice input interface such as a microphone, or the like.

The output unit 32 selects the instruction content input by the input unit 31 and the tone correction color generated based on the instruction content, displays the correction result, and forms the image forming process result. Data such as images, messages for notifying the user of the start and end of processing, and the like are displayed and / or output as audio. Note that the output unit 32 includes a monitor, a speaker, and the like.

The storage means 33 includes a gradation correction data table TA, a threshold value array table TB (threshold value array DB), history data DC, a conversion table TD, a reference image (tone value data (patch data) DE), various parameters, an image, which will be described later. Various data necessary for executing each processing such as density detection result (for example, luminance information of the patch image), RGB image data color-corrected by image development, and various data generated after execution of the processing are stored.

The image expansion means 34 expands the input image into, for example, dot sequential RGB image data for one page. The color correction unit 35 performs processing for converting the developed RGB image data into color information that matches the characteristics of the printing device of the color information included in the input drawing command. The RGB image data color-corrected by the color correcting unit is stored in the storage unit 33.

The reference image generation unit 36 generates gradation value data (patch data) DE composed of gradation patches composed of a plurality of gradations as reference image data. The reference image holding unit 37 holds a reference image composed of gradation patches composed of a plurality of gradations. The reference image may be stored in the storage unit 33.

The four-color separation and holding unit 38 separates the RGB image data stored in the storage unit 33 into four colors of black (K), cyan (C), magenta (M), and yellow (Y). Here, the method of disassembling R (red), G (green), and B (blue) (three colors) into K, C, M, and Y (four colors) is changed depending on the machine's ability and drawing intention. For example, the four-color separation / holding means 38 corresponds to K, C, M, and Y in advance, K [i], C [i], M [i], Y [i] (i = 0). ,..., 255), K = K [max {R, G, B}], C = C [R], M = M [G], Y = Y [ B] can be separated into four colors. Also, K = K [k], C = C [c], M = M [m], Y = Y [y] (where k = min {R, G, B}, c = 255-R, m = 255-G, y = 255-B).

The gradation pattern selection means 39 selects a specific gradation pattern from a plurality of different gradation patterns (halftone dots, lines, error diffusion). The gradation pattern selection means 39 provides a user interface for allowing the user to select a gradation pattern.

In the color selection unit 40, which color is to be subjected to tone correction among the tone pattern selection signal, the color selection signal, and the signal separated by the four-color separation holding unit 38 is preset. Further, the color selection means 40 performs processing such as which signal is selected as an output color among the selected K, C, M, and Y.

The gradation correction data generation unit 41 generates a lookup table (LUT) for performing gradation correction. Specifically, the gradation correction data generation unit 41 performs gradation for each of K, C, M, and Y by a method described later, based on the reflected luminance signal corresponding to each patch of the received patch image. Tone correction data DF corresponding to each pattern is generated. The gradation correction data generation unit 41 stores the generated gradation correction data DF in the storage unit 33 as the gradation correction data table TA. The generated gradation correction data table TA is implemented as a lookup table (LUT) having 256 8-bit entries.

The gradation correcting means 42 similarly corrects an 8-bit image signal of one pixel of 0 to 255 to an 8-bit output gradation value according to the gradation correction data table TA. Here, the gradation correction data DF is implemented as a lookup table (LUT) having 256 8-bit entries.

The gradation processing unit 43 converts the 8-bit gradation value of one pixel output from the gradation correction unit 42 using the threshold value array DB set in advance and stored in the storage unit 33 into halftones using ON / OFF dots. Replace with the pattern. For this processing, for example, a technique disclosed in Patent Document 4 (Japanese Patent Laid-Open No. 2008-244644) can be used.

The density detector 44 detects the brightness of the patch image attached to the photoconductor 11 and the like, and detects the detected brightness information. Further, the detected result is accumulated by the accumulation means 33. The density detection unit 44 is configured by a sensor (reflection luminance sensor 16) that detects the reflected luminance, for example.

The image forming unit 45 develops the input image and character data for each of K, C, M, and Y surfaces (each color), and finally prints them on a print medium such as paper.
The transmission / reception means 46 is a communication interface for acquiring data from other external devices or the like via a communication network and transmitting various data generated such as image formation results to an external terminal.

The control unit 47 controls the entire functional configuration of the image forming apparatus 10. Specifically, the control means 47 is based on the input information from the user input by the input means 31 and the like, image development, color correction, reference image generation, four color separation, gradation pattern selection, output color selection, Control is performed such as generating and displaying a screen in each processing such as generation of gradation correction data DF, gradation processing, density detection, and image formation, and storing information generated in each of the above-described processes.

<Image processing procedure>
Next, an image forming process procedure in the image forming apparatus 10 of the present invention having the above-described functional configuration will be described with reference to the drawings. FIG. 3 is a diagram showing an example of an image forming process procedure in the present embodiment. Also, the alternate long and short dash line in FIG. 3 indicates repetition of processing, not signal flow.

<Image processing procedure during normal printing>
First, the flow of image processing during normal printing will be described. First, image data to be printed is input (S01), the image expansion process is performed by the above-described image expansion unit 34 (S02), and the color correction process is performed by the color correction unit 35. RGB image data is acquired (S03). The acquired result is stored in the image buffer as the storage means 33 (S04).

The RGB image data stored in the image buffer as the storage means 33 is decomposed into signals of four colors K, C, M, and Y by the four-color separation holding means 38 (S05).
Further, according to the color selection signal already set by the color selection means 40, the output values of four colors K, C, M and Y are selected from the outputs of the four-color separation and holding means 38 (S06).

The gradation correcting means 42 similarly corrects the 8-bit image signal of one pixel of 0 to 255 to the 8-bit output gradation value according to the gradation correction data DF (S07).
For the gradation processing, for example, the technique disclosed in Patent Document 4 (Japanese Patent Laid-Open No. 2008-244644) can be used. The 8-bit gradation value of one pixel output from the gradation correction means 42 using the threshold value array N (which can be generated by the method described in Patent Document 4 above) is converted into halftones using ON / OFF dots. Replace with a pattern (S08).

The controller 17 shown in the printer engine 10 of the image forming apparatus in FIG. 1 performs the four processes of K, C, M, and Y in accordance with the color selection signal that automatically switches the processing after the image buffer storage (S04) in FIG. By repeating the minute (four times), data for each color plane necessary for the development process for four colors K, C, M, and Y for the printer engine 10 is generated.

The printer engine 10 forms a full-color image by superimposing these colors (S09), forms it on the paper surface, and outputs it as an image (S10).

Next, the operation at the time of calibration will be described mainly according to the flow shown by the broken line in FIG.
The calibration operation is activated when the printer is activated, when the number of output sheets reaches a predetermined value, or by a user instruction from the operation panel 21 (FIG. 1).
During the calibration operation, the gradation value data (patch data) DE generated by the reference image generation unit 36 and stored in the reference image holding unit 37 and the like for the image buffer in the storage unit 33 as shown in S04 of FIG. The patch image generated based on the is directly written.
On the other hand, the four-color separation holding unit 38 performs internal processing on the RGB signal (r, g, b) with (k, c, m, y) = (min {c, m, y}, 255-r. , 255-g, 255-b). Further, the processing of the gradation correction means 42 is passed through without being executed. Thus, for example, as patch data P, g and b are fixed to g = b = 255, and data with r is prepared, so that a cyan monochrome patch image corresponding to a signal value of c = 255-r is prepared. Is sent to the printer engine 10. The above-described processing can be similarly performed for magenta and yellow, but for black, a patch corresponding to a signal value of k is prepared by preparing data of r = g = b = 255-k. The image is sent to the printer engine 10.
In the calibration operation mode, the printer engine 10 executes the same process as the normal printing described above except that the paper is not picked up and the process after the transfer to the printing medium such as the paper is not executed. Is done.

<Example of patch image formed on photoconductor>
FIG. 4 is a diagram illustrating an example of a patch image formed on the photoconductor. As a result of the above-described processing, as shown in FIG. 4, the patch image 57 can be formed at a predetermined position on the photoconductor 11 of the printer engine 10 (for example, a position not in contact with the intermediate transfer body 12). Further, the reflection luminance sensor 16 mounted on the printer engine 10 detects the reflection luminance signal of the patch image 57 and transmits it to the gradation correction data generation means 41. As a result, the reflected luminance signal of the patch image can be detected without performing image output to a print medium such as paper.

The gradation correction data generation unit 41 also adjusts gradation correction data corresponding to the number of gradation patterns based on the density value (converted from the reflected luminance signal) corresponding to each patch of the sent patch image 57. A DF is generated and registered in the gradation correction data table TA. Specifically, the density value f (x) for an arbitrary area ratio x is generated using the density value for the area ratio of the ON pixels of the patch image. A method for generating the density value f (x) will be described later. Assuming that an 8-bit image signal value is s, an 8-bit image signal value to area ratio lookup table is t (s), and a target gradation characteristic is r (s), f (t (s)) = t (s) is determined so as to satisfy r (s). That is, t (s) is generated as t (s) = f ⁻¹ (r (s)). This is registered in the gradation correction data table TA.
In the present embodiment, the generation of the gradation correction data DF is realized by a CPU as the control means 47 mounted on the controller 17 and a peripheral memory as the storage means 33 and a program incorporated therein in advance. The gradation correction data table TA and the history data DC are realized as a specific address space of the peripheral memory in the storage unit 33. Similarly, the reference image generation process is realized by a program for the CPU or the like.

<Hardware configuration example of computer capable of executing image forming process>
A hardware configuration example of a computer capable of executing image forming processing according to the present invention will be described with reference to FIG. FIG. 5 is a diagram illustrating an example of a hardware configuration capable of realizing the image forming process according to the present invention. 5 includes an input device 91, an output device 92, a drive device 93, an auxiliary storage device 94, a memory device 95, a CPU (Central Processing Unit) 96 for performing various controls, and a network connection device. 97, which are connected to each other by a system bus BUS.

The input device 91 includes a keyboard and a pointing device such as a mouse operated by a user, a voice input device, and the like, and inputs various operation signals and voice signals such as a program execution instruction from the user.
The output device 92 has a display, a speaker, and the like that display various windows and data necessary for operating the computer main body for performing the processing according to the present invention. Display or audio output is possible.

Here, in the present invention, the execution program installed in the computer main body is provided by a recording medium 98 such as a CD-ROM or DVD, for example. The recording medium 98 on which the program is recorded can be set in the drive device 93, and the execution program included in the recording medium 98 is installed in the auxiliary storage device 94 from the recording medium 98 via the drive device 93. Further, the drive device 93 can record the execution program according to the present invention in the recording medium 98. Thus, the recording medium 98 can be used for easy installation on a plurality of other computers, and an image forming process can be easily realized.

The auxiliary storage device 94 is a storage means such as a hard disk, and can store an execution program according to the present invention, a control program provided in a computer, and the like, and can perform input / output as necessary. The auxiliary storage device 94 can also be used as a storage means for storing various data according to the present invention described above.
The memory device 95 stores an execution program or the like read from the auxiliary storage device 94 by the CPU 96. The memory device 95 includes a ROM (Read Only Memory), a RAM (Random Access Memory), and the like.
Based on a control program such as an OS (Operating System) and an execution program read from the auxiliary storage device 94 and stored in the memory device 95, the CPU 96 inputs various calculations and data to each hardware component. Each processing in image formation can be realized by controlling processing of the entire computer such as output. Various information necessary during the execution of the program can be acquired from the auxiliary storage device 94 and stored.

The network connection device 97 obtains an execution program from another terminal connected to the communication network or executes the program by connecting to a communication network such as a telephone line or a LAN (Local Area Network) cable. The execution result obtained in this way or the execution program in the present invention can be provided to other terminals or the like.
With the hardware configuration as described above, an image forming process can be realized at a low cost without requiring a special device configuration. Further, by installing the program, the image forming process can be easily realized as software. As a result, the image forming program and various data are loaded into the memory device 95, and the CPU 96 executes the program using the data to perform the image forming process according to the present embodiment. Therefore, highly accurate gradation correction can be realized. In addition, a highly accurate image can be formed. Further, by installing the program, the image formation in the present invention can be easily realized by a general-purpose personal computer or the like.

<Gradation correction data generation method by gradation correction data generation means>
Hereinafter, a specific example of the gradation correction data generation unit 41 will be described. The density value f (x) with respect to the area ratio x is referred to as “gradation characteristics”. Estimating the density value of a patch with the same area ratio of another gradation pattern from the density value of a patch with a specific area ratio of a certain gradation pattern is “estimation between gradation patterns”. Estimating the overall tone characteristics of the tone pattern from a set of area ratio and density value is called “tone estimation”.

<Averaging gradation estimation results>
In this embodiment, using the measured density of the patch on the intermediate transfer belt, the gradation estimation is performed after the gradation pattern estimation is performed, and the gradation estimation is performed after the gradation estimation is performed. An example is shown in which the tone characteristics are estimated with high accuracy from a small number of measurement patches.
A functional block diagram of the present embodiment is shown in FIG. The gradation correction data generation means 41 includes a measurement unit 101, a gradation pattern estimation unit 102, a gradation estimation unit 103, a gradation estimation unit 104, a gradation pattern estimation unit 105, an averaging unit 106, and a gradation table correction unit. 107.
A processing flow in this embodiment is shown in FIG. A specific example of this process is shown in FIG.

In processing step S101, the measurement unit 101 creates a plurality of patches with different gradations of a specific gradation pattern on the intermediate transfer belt, and measures the density of each patch through the reflection luminance sensor 16 (FIG. 1). In the specific example, four patches having halftone dot area ratios of 0.25, 0.50, 0.75, and 1.00 (representing 25%, 50%, 75%, and 100%, respectively) are generated, Measure its concentration.
In processing step S <b> 102, the inter-tone pattern estimation unit 102 estimates the density of patches with the same area ratio in different tone patterns from the measured patch density through the reflection luminance sensor 16. In a specific example, the area ratios of the lines are 0.25, 0.50, 0.75, and 1. from the densities of the four patches having the dot area ratios of 0.25, 0.50, 0.75, and 1.00. Estimate the density of 4 patches of 00. Here, the area ratio is x, the density of the patch of the halftone dot of area ratio x is f (x), the density of the patch of the line of area ratio x is g (x), and the correction term is h (x). It shall be estimated by the formula.

The estimation formula can be identified using a regression analysis or the like by measuring pairs of halftone dots and parallel patches in the same area ratio in advance.
In processing step S103, the gradation estimation unit 103 interpolates the density in the estimated gradation pattern to obtain an estimated value of density over the entire gradation. In the specific example, the density of the four patches of the area ratios 0.25, 0.50, 0.75, and 1.00 estimated from the four patches of halftone dots is interpolated to estimate the density of an arbitrary area ratio. Get the value. Various methods such as linear interpolation, spline interpolation, and linear regression can be used for this interpolation.
In the processing step S104, the gradation estimating unit 104 interpolates the patch density measured in the processing step S101 to obtain an estimated value of density over the entire gradation. In a specific example, the density of four patches of halftone dot area ratios of 0.25, 0.50, 0.75, and 1.00 is interpolated to obtain an estimated value of the density of an arbitrary area ratio. Various methods such as linear interpolation, spline interpolation, and linear regression can be used for this interpolation.
In processing step S105, the gradation pattern inter-estimation estimating unit 105 estimates the density of the area ratio corresponding to the different gradation patterns from the estimated density value over the estimated gradations. In a specific example, the density g (x) of the line with the area ratio x is estimated from the density f (x) of the halftone dot with the area ratio x using the equation (1).
In the processing step S106, the averaging unit 106 averages the density of the same area ratio with respect to the two gradation characteristics estimated in the processing steps S103 and S105, and obtains a new gradation characteristic.
In processing step S107, the tone correction table correction unit 107 corrects the tone correction data table TA using the newly obtained tone characteristics. The corrected gradation correction data table TA is transferred to the gradation correction means 42.

  The effect of the present invention will be described through an example in which the gradation characteristics of the line are estimated from the measured density value of the halftone patch having the area ratio of 1.00 in FIG. Linear interpolation is used for tone estimation, and equation (1) is used for estimation between tone patterns.

And As can be seen from FIG. 9, the obtained gradation characteristics change when the order of estimation between gradation patterns and the order of gradation estimation are different. If the error in estimation between gradation patterns is sufficiently small, if the true gradation characteristics of the halftone dots are linear, the gradation estimation is performed more linearly when the gradation estimation is performed first. In this case, the estimation error is smaller when the estimation between the gradation patterns is performed first. This is a case of linear interpolation, but in general, gradation estimation is performed with a gradation pattern having gradation characteristics suitable for the estimation method, so that the final estimation error is smaller (if spline interpolation is used, The estimation error is smaller when the gradation estimation is performed with the gradation pattern having smooth gradation characteristics). Therefore, it is preferable to determine the order of the inter-tone pattern estimation and the tone estimation so that the tone estimation is performed with the tone pattern having the tone characteristics suitable for the tone estimation method. However, in practice, the gradation characteristics vary depending on various factors such as temperature and humidity, the charged state of the toner, and the deterioration state of the developer, so it is difficult to know the gradation characteristics of each gradation pattern in advance. Therefore, as in the present embodiment, the order of estimation between the gradation patterns and the order of gradation estimation are interchanged to obtain two gradation characteristics, and averaging them can reduce the risk that the estimation error increases. it can.
By the way, the estimation between gradation patterns is not limited to the equation (1), but can take various function forms. In addition, if an estimation formula cannot be created for all area ratios x (for example, if there is an estimation formula in discrete increments of 0.05), then an estimation can be made with an area ratio that can be estimated, May be interpolated by an interpolation method such as linear interpolation or spline interpolation.

<Selection of gradation estimation result>
In this embodiment, as will be described with reference to FIGS. 10 and 11, using the measured density of the patch on the intermediate transfer belt, the estimation of the gradation after performing the estimation between the gradation patterns, and the gradation An example of estimating the gradation characteristics with a high degree of accuracy from a small number of measurement patches by calculating the degree of fitness of the estimation between the gradation patterns after estimation and adopting the estimation result with the higher fitness is shown. .
A functional block diagram of this embodiment is shown in FIG. The gradation correction data generation means 41 includes a measurement unit 101, a gradation pattern estimation unit 102, a gradation estimation unit 103, a gradation estimation unit 104, a gradation pattern estimation unit 105, a fitness calculation unit 201, a selection unit 202, A gradation table correction unit 107 is included.

FIG. 11 shows a processing flow in the present embodiment. Hereinafter, processing steps S201 and S202, which are differences from the above-described gradation estimation result averaging processing flow, will be described.
In processing step S <b> 201, the fitness level calculation unit 201 calculates the fitness levels of two tone characteristic estimation results in which the order of tone pattern estimation and tone estimation is different. The degree of conformity is calculated by any one or a combination of the monotonic increase in gradation characteristics, smoothness, appearance probability based on past measurement data. The gradation characteristic of the fitness calculation target is expressed as g (x) with respect to the area ratio x.
In the calculation of the fitness based on monotonic increase, the prior knowledge that “the gradation density increases monotonously with the increase in the area ratio” is used to reduce the fitness when this characteristic is not observed. Set the degree calculation function. An example of a specific configuration is given. First, consider the following penalty function φ (x).

Then, the adaptability J (g) of the gradation characteristic g is calculated as follows.

In this way, taking the adaptability, the value is 1 if the gradation characteristic is monotonously increasing, and is smaller than 1 depending on the degree of the decrease if there is a decreasing section. Here, it is assumed that g (x) is defined in the interval [0 1], but even when g (x) is discrete, it can be dealt with by substituting the difference with the difference and the integration with the sum.
In the fitness calculation based on smoothness, using the prior knowledge that “the gradation density changes smoothly with respect to the area ratio”, the fitness is calculated so that the fitness is reduced when this characteristic is not observed. Set the function. As a specific configuration example of the adaptability J (g) of the gradation characteristic g, the following equation is given.

In this formulation, the fitness is high when the integral value over the entire gradation of the square value of the second derivative is small.
It is also possible to create a probability model based on the past measurement data and use the appearance probability of the target gradation characteristic in the probability model as the fitness. For example, when using a Gaussian distribution for the probability model, the gradation characteristics are appropriately discretized, the average gradation characteristics μ of the past measurement data, and the variance-covariance matrix Σ are calculated, and the goodness of fit J (g) is as follows: Is calculated.

In the processing step S202, the selection unit 202 selects the one having the higher matching degree from the two gradation characteristic estimation results in which the order between the gradation pattern estimation and the gradation estimation is different, and selects the final gradation characteristic. Estimated result.
According to the method of this embodiment, since the two gradation characteristic estimation results having different order of gradation pattern estimation and gradation estimation are selected according to the fitness, the above-described gradation estimation result averaging method is used. In this way, an increase in estimation error is not prevented, but a result with a small estimation error can be positively obtained.

<Gradation estimation result weighted addition>
In this embodiment, as will be described with reference to FIGS. 12 and 13, using the measured patch density on the intermediate transfer belt, the estimation of gradation between the gradation patterns is performed and the gradation is estimated. Estimate and then perform the inter-tone pattern estimation, calculate the goodness of fit, and add the two estimation results according to the goodness-of-fit ratio to estimate the tone characteristics from a small number of measurement patches with high accuracy An example is shown.
A functional block diagram of this embodiment is shown in FIG. The gradation correction data generation means 41 includes a measurement unit 101, an estimation unit between gradation patterns 102, a gradation estimation unit 103, a gradation estimation unit 104, an estimation unit between gradation patterns 105, a fitness calculation unit 201, and a weighted addition unit 301. The tone table correction unit 107 is configured.
FIG. 13 shows a processing flow in the present embodiment. Hereinafter, processing step S301 that is a difference from the above-described method of selecting the gradation estimation result will be described.
In the processing step S301, two tone characteristic estimation results g ₁ and g ₂ having different orders of tone pattern estimation and tone estimation are weighted and added in accordance with the ratio of the fitness levels to obtain a final tone characteristic. The estimation result is g. When the goodness of fit J described in the method of selecting the gradation estimation result is used, the estimation formula is as follows.

  According to the method of this embodiment, two tone characteristic estimation results with different order of tone pattern estimation and tone estimation are weighted and added according to the degree of fitness, so that a tone estimation result with a small error can be obtained. Can do.

As described above, according to the image forming apparatus, the image forming method, the image forming program, and the recording medium of the present invention, the variation in the estimation accuracy due to the difference in the gradation characteristic and the estimation method is reduced, and the gradation characteristic is estimated. The accuracy can be increased and it is suitable for maintaining high image quality.

Image forming apparatus (printer engine) ... 10, photosensitive member ... 11, intermediate transfer member ... 12, developing device ... 13, charger ... 14, exposure device ... 15, reflection luminance sensor ... 16, controller ... 17, transfer roller ... 18 , Cassette unit 19, fixing device 20, operation panel (operation unit) 21, input unit 31, output unit 32, storage unit 33, image development unit 34, color correction unit 35, reference image generation Means 36, reference image holding means 37, four color separation holding means 38, gradation pattern selecting means 39, color selecting means 40, gradation correction data generating means 41, gradation correcting means 42, floor Adjustment processing means 43, density detection means 44, image forming means 45, transmission / reception means 46, control means 47, input device 91, output device 92, drive device 93, auxiliary storage device 94, memory apparatus 95, CPU ... 96, Network connection device ... 97, System bus ... BUS, Recording medium ... 98, Measurement unit ... 101, Tone pattern estimation unit ... 102, Tone estimation unit ... 103, 104, Estimation between tone patterns Unit 105, averaging unit 106, gradation table correction unit 107, fitness calculation unit 201, selection unit 202, weighted addition unit 301

JP 05-336367 A Japanese Patent No. 4305113 Japanese Patent No. 3738346 JP 2008-244644 A Japanese Patent Application No. 2011-139613

Claims (12)

The gradation characteristic is estimated based on the measured value of the density of the patch of the gradation pattern formed on an image bearing member, and generates a tone correction data from the gradation characteristic of the estimated tone characteristic and goals image A forming device,
First gradation estimating means for estimating gradation characteristics of the gradation pattern from the measured density of the patch of the gradation pattern;
A first gradation pattern between estimating means for estimating the tone characteristics of the different gradation patterns with gray scale pattern from the tone characteristic of the estimated gradation pattern by the first gradation estimation means,
A second gradation pattern estimation means for estimating the density of the different gradation pattern having the same area ratio as the area ratio of the measured gradation pattern from the density of the patch of the measured gradation pattern ;
From the estimated concentration of the different gradation patterns estimated by the second tone pattern between estimating means, and the second tone estimation means for estimating the tone characteristics of the different gradation patterns,
And a weighted addition means you weight the summing and tone characteristic estimated by the estimated gradation characteristic the second tone estimator in the first gradation pattern between estimating means,
An image forming apparatus , wherein the gradation characteristics of the different gradation patterns obtained by weighted addition by the weighted addition means are used as the estimated gradation characteristics . The weighted addition unit, an image forming apparatus according to claim 1, characterized in that taking the average of two Kaichotoku property that the pressurized heavy adding means for weighted addition. Further comprising a matching degree calculation means weighted addition means for calculating a two Kaichotoku of fitness for weighted addition, of the two Kaichotoku property, 1 the weight of the higher the goodness of fit, and the other The image forming apparatus according to claim 1, wherein weighted addition is performed with 0 being zero. The weight adding means further comprises a fitness calculating means for calculating the two Kaichotoku of goodness of fit is weighted addition, the two Kaichotoku properties, by performing weighted addition with weighting proportional to the goodness of fit The image forming apparatus according to claim 1.   4. The fitness level calculation means according to claim 3, wherein the fitness level is calculated by any one or a combination of monotonically increasing gradation characteristics, smoothness, appearance probability based on past measurement data. Item 5. The image forming apparatus according to Item 4. The gradation characteristic is estimated based on the measured value of the density of the patch of the gradation pattern formed on an image bearing member, and generates a tone correction data from the gradation characteristic of the estimated tone characteristic and goals image A forming method comprising:
A first tone estimation step for estimating the tone characteristics of the tone pattern from the measured tone pattern patch density;
A first gradation pattern between estimation step of estimating a gradation characteristic of the gradation pattern different from the gradation pattern from the tone characteristic of the gradation pattern estimated by the first gradation estimation step,
From the density of the patch of the measured gradation pattern, an estimation step between second gradation patterns for estimating the density of the different gradation pattern having the same area ratio as the area ratio of the measured gradation pattern;
From the estimated concentration of the different gradation patterns estimated by the estimating step between the second tone pattern, a second tone estimation step of estimating the tone characteristics of the different gradation patterns,
And a weighted addition step weight the summing and gradation characteristic estimated by the estimated gray level characteristic second tone estimation step in the first gradation pattern between estimation step,
An image forming method , wherein the gradation characteristics of the different gradation patterns obtained by weighted addition in the weighted addition step are used as the estimated gradation characteristics . The image forming method according to claim 6, wherein the weight adding step, the pressurized heavy adding step is characterized by taking the average of two Kaichotoku of weighted addition. Further comprising a fitness calculating step of weighted addition step for calculating a two Kaichotoku of fitness for weighted addition, of the two Kaichotoku property, 1 the weight of the higher the goodness of fit, and the other 7. The image forming method according to claim 6, wherein the weighted addition is performed with 0 being zero. The weight adding step further comprises a fitness calculating step of calculating a two Kaichotoku of fitness for weighted addition, the two Kaichotoku properties, by performing weighted addition with weighting proportional to the goodness of fit The image forming method according to claim 6.   9. The suitability calculation step, wherein the suitability is calculated by one or a combination of monotonically increasing gradation characteristics, smoothness, appearance probability based on past measurement data, or a combination thereof. Item 10. The image forming method according to Item 9. Image forming program for causing the operation of the computer so as to execute the image forming method according to any one of claims 6 to 10. It was recorded image forming program according to claim 11, a computer-readable recording medium.

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