JP2019142221A - Image processing apparatus, image processing system, and image processing program - Google Patents

Abstract

To provide an image stabilizing technique for maintaining an initial printing state and to realize stabilization of color reproducibility of a printing job.SOLUTION: A reflection characteristic detection part detects reflection characteristics of respective output images on respective printing media formed successively with time among printing media having output images formed corresponding to input image data, respectively. A gradation characteristic correction part corrects gradation characteristic data of the input image data so that the reflection characteristics of the respective output images on the respective printing media that the reflection characteristic detection part detects are coincident. Consequently, an initial printing state can be maintained, and color reproducibility of a printing job can be stabilized.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an image processing apparatus, an image processing system, and an image processing program.

  Today, digital printing apparatuses such as an electrophotographic system or an inkjet system are known. In such a digital printing apparatus, in the case of a printing apparatus that performs large-scale printing, stability of output color is required at the time of continuous output of hundreds or thousands of sheets. In particular, in a use case in which the same type of manuscript in which some content is replaced every several pages is repeated, or in a use case in which distributed printing is performed at multiple locations, stable management of reproduced colors is important.

  However, unlike full-scale commercial printing, the operating environment in which these digital printers are used is often not strictly managed. For this reason, the digital printing machine is often used in a temperature environment and a humidity environment that affect the printing result.

  On the other hand, there are many unavoidable instability factors that change the state of the apparatus such as the toner supply amount due to mixed printing of various document types. For this reason, when stable management of the output color is required, it is necessary to frequently stop the machine and perform calibration for adjusting the color and the color shift. With regard to calibration, for example, Patent Document 1 (Japanese Patent Laid-Open No. 2017-187585) discloses a printing system that can perform calibration at an appropriate page position.

  The fact that the color to be originally printed is determined means that a reference characteristic that is a correspondence standard of a color to be printed with respect to input data is defined in advance. Usually, calibration is performed for the purpose of matching such reference characteristics with actual characteristics. In this sense, it is ideal to perform calibration every time immediately before a print job.

  However, when the calibration operation is increased, there are problems that the number of waste paper increases and the job is stopped and the number of work steps is increased. In some cases, it is necessary to use calibration information with low freshness.

  In general, color differences are perceived sensitively when viewed side-by-side and less likely to be perceived when compared individually. Accordingly, it is required to manage the color consistency between printed materials in the same job, in which printing results are often compared in parallel, at a stricter level. However, if the actual characteristic at the start of the job deviates from the reference characteristic, a problem arises that the print color drifts until the actual characteristic matches the reference characteristic by feedback.

  The present invention has been made in view of the above-described problems, and in particular, is an image processing apparatus, an image processing system, and an image processing program that can provide an image stabilization method that maintains an initial printing state. An object is to provide an image processing apparatus, an image processing system, and an image processing program capable of stabilizing reproducibility.

  In order to solve the above-described problems and achieve the object, the present invention provides each of the print media formed before and after time among print media on which an output image corresponding to input image data is formed. The reflection characteristic detection unit that detects the reflection characteristic of the output image and the gradation characteristic that corrects the gradation characteristic of the input image data so that the reflection characteristic of each output image of each print medium detected by the reflection characteristic detection unit matches. A tone characteristic correction unit.

  According to the present invention, it is possible to provide an image stabilization method that maintains an initial printing state, and it is possible to stabilize color reproducibility in a print job.

FIG. 1 is a system configuration diagram of an image processing system according to the first embodiment. FIG. 2 is a block diagram illustrating a configuration of a color tone control unit provided in the image processing system according to the first embodiment. FIG. 3 is a vertical sectional view of the laser printer apparatus provided in the image processing system according to the first embodiment. FIG. 4 is a diagram for explaining the mode curve. FIG. 5 is a diagram illustrating an example of a gradation correction curve formed by synthesizing a plurality of mode curves. FIG. 6 is a flowchart showing a flow of operations for estimating the mode parameters in the initial state immediately after calibration in the image processing system according to the first embodiment. FIG. 7 is a flowchart showing a flow of operations for estimating a normal mode parameter in the image processing system according to the first embodiment. FIG. 8 is a block diagram illustrating a configuration of a color tone control unit provided in the image processing system according to the second embodiment. FIG. 9 is a flowchart showing a flow of the gradation correction processing operation of the image processing system according to the second embodiment. FIG. 10 is a diagram for explaining the in-plane deviation. FIG. 11 is a diagram illustrating density characteristics before and after the gradation correction process in the image processing system according to the second embodiment.

  Hereinafter, as an example, an image processing apparatus, an image processing system, and an image processing system according to an embodiment to which an image processing program is applied will be described.

[First Embodiment]
(System configuration of the first embodiment)
FIG. 1 is a system configuration diagram of a main part of the image processing system according to the first embodiment. As shown in FIG. 1, the image processing system according to the first embodiment includes a user's personal computer device (user PC) 1, a server device 7, and an image forming device 8 that are connected to, for example, a LAN (Local Area Network) or the Internet. Are connected to each other via a predetermined network 2. At least one user PC 1 is connected to the network 2 and transmits image data and a print request to the image forming apparatus 8. The server device 7 stores (accumulates) information necessary for color conversion performed by the image processing unit 3.

  The image forming apparatus 8 includes an image processing unit 3 that develops and processes document data 30 input via the network 2, an electrophotographic printer engine 4 that executes printing, and an engine control unit that controls the printer engine 4. 9. The image forming apparatus 8 also outputs a gradation processing unit 31 that converts the pixel arrangement developed by the image processing unit 3 into the number of gradations that can be output by the printer engine 4, and an output image 6 from the printer engine 4. It has an image inspection unit 5 for in-line inspection. In addition, the image forming apparatus 8 detects a color tone variation (density variation or hue variation, etc.) of the output image from the image detected by the image inspection unit 5, and controls color tone control for supplying correction parameters to the gradation processing unit 31. A portion 28 is provided.

  The engine control unit 9 is provided in the same casing as the printer engine 4. The engine control unit 9, the printer engine 4, the image inspection unit 5, and the color tone control unit 28 constitute a main body unit group 32. In the example of FIG. 1, the gradation processing unit 31 is illustrated as being provided outside the main body unit group 32, but the gradation processing unit 31 may be provided inside the main body unit group 32.

  The image processing unit 3 includes software and an expansion board. The image processing unit 3 is separate from the main body unit group 32 and can be exchanged for the main body unit group 32.

  The image inspection unit 5 includes an RGB line sensor (RGB: red, green and blue) serving as an image measurement unit and a scanner 150 having a paper feed mechanism. This image inspection unit 5 makes it possible to measure the color of the image on the surface.

  Normally, the document data 30 transmitted when a print request is issued from the user PC 1 is bitmap data or text data designated by RGB or CMYK (cyan, magenta, yellow, black) as shown in FIG. 2, for example. The data in a complicated data format including a drawing command for graphics is transmitted to the image processing unit 3 via the network 2.

  The image processing unit 3 is also called a digital front end (DFE). The image processing unit 3 expands the received data, and performs a gradation processing unit as pixel array data (bitmap data or data in a compression format equivalent to the bitmap data) configured with the basic colors of the printer engine 4 31. The gradation processing unit 31 converts, for example, each pixel data of the bitmap data into pixel data having the number of gradations that can be expressed by the printer engine 4. The printer engine 4 forms an output image 6 on a sheet based on the bitmap data subjected to such conversion processing.

  The image inspection unit 5 scans the output image of the printer engine 4 and supplies it to the color tone control unit 28. The color tone control unit 28 uses, as a target value, a predicted value obtained by a colorimetric prediction unit (reference numeral 21 in FIG. 2) which is a prediction unit described later or a scan image of an initial print output stored in the image memory 36 as a target value. A gradation correction parameter that minimizes the difference between the color and the color of the image scanned by the image inspection unit 5 is set in the gradation processing unit 31. As a result, the gradation processing unit 31 can perform gradation correction processing on the document data 30 to stabilize the reproduced color of the output image 6.

(Details of color control unit)
FIG. 2 is a block diagram illustrating each function of the color tone control unit 28. As shown in FIG. 2, the tone control unit 28 includes a difference detection unit 40 and a corrected TRC calculation unit 41 (TRC: Tone Reproduction Curve). The difference detection unit 40 includes a registration correction unit 11, a selector 14, a subtracter 15, a colorimetric prediction unit 21, and an image memory 36.

  The correction TRC calculation unit 41 includes a colorimetric region extraction unit 18, an address correction unit 19, a sample extraction unit 20, a mode parameter calculation unit 22, a leveling processing unit 23, a subtractor 24, a TRC synthesis unit 25, a calculation condition selector 35, A sample memory 37, a first mode parameter memory 38, and a second mode parameter memory 39 are included.

  A part or all of the difference detection unit 40 and the corrected TRC calculation unit 41 may be realized by hardware. The registration correction unit 11, the selector 14, the subtractor 15, and the colorimetric prediction unit 21 of the difference detection unit 40 may be realized by software. Similarly, the colorimetric region extraction unit 18, the address correction unit 19, the sample extraction unit 20, the mode parameter calculation unit 22, the leveling processing unit 23, the subtractor 24, the TRC synthesis unit 25, and the calculation of the correction TRC calculation unit 41 are calculated. The condition selector 35 may be realized by software. An image processing program for realizing the difference detection unit 40 and the corrected TRC calculation unit 41 by software is a ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), or the like of the image forming apparatus 8. The above-described functions are realized by being stored in the storage unit and executed by a control unit such as a CPU (Central Processing Unit) of the image forming apparatus 8.

  In FIG. 2, the image processing unit 3 develops a user document described in various input formats as described above into a CMYK image 10 in which each CMYK value is an 8-bit field sequential pixel array for each page. .

  The gradation processing unit 31 that functions as a gradation characteristic correction unit includes a gradation correction table 16 and a gradation conversion unit 17. As the gradation correction table 16, a so-called look-up table (LUT) can be used. The gradation conversion unit 17 converts the pixel arrangement of 8 bits for each CMYK color plane by the area gradation method into a pixel arrangement of gradations of the number of bits (for example, 2 bits) that can be drawn by the printer engine 4.

The gradation correction table 16 is an 8-bit input to 8-bit output correction table for each color of CMYK, and is a table that standardizes the density characteristics of the output image 6 corresponding to the input of the gradation processing unit 31 by prior calibration. A value (tone correction data (TRC: Tone Reproduction Curve)) is set.

  The scanner 150 is actually incorporated in the image inspection unit 5 that is directly connected (directly connected) to the printer engine 4. The scanner 150 scans the output image 6 formed by the printing process of the printer engine 4 inline.

  The color tone control unit 28 changes the print reproduction color based on the scan image (RGB) formed by the scanner 150 scanning the output image 6 from the printer engine 4 and the CMYK image 10 from the image processing unit 3. (Difference) is detected. Then, the color tone control unit 28 corrects the gradation correction data (TRC) of the gradation correction table 16 so as to reduce the difference between the detected two. Thereby, the reproduction color of the output image 6 can be stabilized.

  Prior to such a reproduction color stabilization operation, the image processing system according to the first embodiment performs scan image data (RGB values) of the scanner 150 corresponding to the data of the CMYK image 10 by performing calibration in advance. Is set as a multi-dimensional LUT in the colorimetric prediction unit 21 which is a prediction unit. The colorimetric prediction unit 21 predicts RGB measurement values scanned by the scanner 150 from the CMYK values of the CMYK image 10 by the multidimensional LUT and interpolation calculation. As an example, as such a prediction model, for example, a device link model of the international standard ISO15076-1 can be used.

  The registration correction unit 11 corrects a minute image shift (magnification, offset, rotation, distortion) between the predicted image (RGB) 13 of the colorimetric prediction unit 21 and the scan image 12. The auxiliary information (correction parameters regarding magnification, offset, rotation, and distortion) required for correction at this time is shared as address correction information of the address correction unit 19 described later.

  Next, the value n of the repeated page number signal 33 shown in FIG. 2 is supplied from the image processing unit 3. Specifically, when the actual number of repeated pages is larger than a predetermined number set in advance and when not repeated, a repeated page number signal 33 of “n = 0” is supplied from the image processing unit 3. When the repeated page number signal 33 of “n = 0” is supplied, the image data is not read from the image memory 36, and the selector 14 selects the predicted image 13 as a reference image and supplies it to the subtracter 15.

  On the other hand, when the value of the repeated page number signal 33 is “n> 0”, the first n pages of scanned images 12 are sequentially stored in the image memory 36 and supplied to the selector 14. . After the first n pages, the scan image is not stored in the image memory 36, and at the timing when a new scan image 12 is acquired, the image set stored in the image memory 36 is repeatedly read out and output. Is done.

  The subtracter 15 outputs difference image data obtained by subtracting the reference image from the scanned image 12. In parallel with the processing of the subtractor 15, the colorimetric area extraction unit 18 is a colorimetric area having a predetermined size, such as a rectangular area of 2.5 mm square from the CMYK image 10. An image area having a relatively small density change is extracted as an image area suitable for colorimetry, and an address list indicating the position of each extracted image area (colorimetry matching area position) is created.

  The address correction unit 19 associates the colorimetric matching region position registered in the address list with the image position of the difference image data output from the subtracter 15 based on the address correction information from the registration correction unit 11. Based on the corrected address list, the sample extraction unit 20 calculates the colorimetric region average (c, m, y, k, Δr, Δg, Δb) from the output image of the subtractor 15 and the CMYK image 10 by random sampling. It is calculated and stored in a sample memory 37 which is a FIFO (First In First Out) provided as a measurement sample storage unit.

  The mode parameter calculation unit 22 which is a gradation control parameter calculation unit calculates the penalty value (first value and second value) given from the sample stored in the sample memory 37 and the calculation condition selector 35 which is a switching unit. Based on this, the mode parameter update amount Δθ is determined by a calculation method described later.

  Note that the initial mode parameter (θ0) and the mode parameter update amount (Δθ) are calculated by an equivalent algorithm (for example, Equation 8 described later). In order to simplify the description, the mode parameter update amount is sometimes simply referred to as a mode parameter. Also, the tilde symbol (~) in Equation 8 is not essential in the algorithm, so the description is simplified by omitting it.

  The mode parameter that is the gradation control parameter is a synthesis coefficient of the mode curve that best approximates the necessary TRC correction amount. In the case of three modes using three mode curves for each color of CMYK, the mode parameters are configured with a total of 12 parameters. This mode parameter is accumulated in a first mode parameter memory 38 which is a storage unit such as a FIFO.

  The leveling processing unit 23 determines the mode parameter update amount Δθ by removing a sample indicating an abnormal value from each sample stored in the sample memory 37 and averaging a predetermined number of samples. .

  On the other hand, the selection signal 34 instructing switching of the mode parameter calculation conditions is also a signal indicating one of the two states “0” or “1”. Specifically, the calculation condition corresponding to the value “0” of the selection signal 34 is associated with the setting operation of the mode parameter reference “θ0” corresponding to the initial printing state. The calculation condition corresponding to the value “1” of the selection signal 34 is associated with the calculation operation of the mode parameter correction amount Δθ for correcting the printing state change.

  As an example, the setting operation of the reference θ0 is executed at the start of a continuous print job. However, even when a printing state in which it is difficult to obtain an image sample with sufficient reflection characteristics continues at a point in time when an image sample with sufficient reflection characteristics can be obtained, the reference θ0 is reset to rapidly Can prevent the density change. For this reason, in the case of the image processing system of the first embodiment, the value of the selection signal 34 is set when it is difficult to obtain an image sample with sufficient reflection characteristics at a predetermined number of printed sheets or at a predetermined time interval. It is reset to “0”.

  When the selection signal 34 is “0”, the above-described calculation condition selector 35 selects a parameter (a penalty value described later) corresponding to the first calculation condition for giving priority to the estimation accuracy. Next, the value θ0 of the second mode parameter memory 39 that is the gradation control parameter holding unit is updated to “θ0 = Δθ” by the output from the leveling processing unit 23 (however, the initial value is “0”). is there). When the selection signal 34 is “1”, the calculation condition selector 35 selects a parameter corresponding to the second calculation condition for giving priority to the stability of the control result. In this case, the value of the mode parameter memory 39 is not updated.

  The subtracter 24 subtracts the mode parameter θ 0 held in the second mode parameter memory 39 from the output mode parameter Δθ of the leveling processing unit 23. Therefore, especially when the selection signal is “0”, the subtraction value Δθ−θ0 is always “0”.

  The TRC synthesis unit 25 includes an integrator 26, a reference TRC storage unit 42 for each color of CMYK, a mode curve storage unit 43, and a synthesis TRC generation unit 44. The mode curve storage unit 43 functions as a so-called LUT, and the value of the approximate basis mode curve of the TRC change difference is loaded from a predetermined storage unit. The reference TRC storage unit 42 has the same LUT as the gradation correction table 16. The accumulator 26 changes the polarity (sign) of “Δθ−θ0” from the subtractor 24 and accumulates it (corresponding to Equation 9 described later). When the job is started and when the selection signal 34 is “0”, the gradation correction table 16 is stored in a form copied to the reference TRC storage unit 42, and all elements are initialized to “0”.

  The TRC synthesis unit 25 performs the product sum with the mode curve read from the mode curve storage unit 43 using the corresponding element of the accumulator 26 as a coefficient at the timing when the value of the accumulator 26 is updated for each color of CMYK. Is added to the reference TRC stored in the reference TRC storage unit 42 to update the gradation correction table 16 with the synthesized TRC.

(Operation of the first embodiment)
Next, the detailed operation of the image processing system according to the first embodiment having such a configuration will be described. First, in the case where one set is a job in which a document of a predetermined page or less is repeatedly printed, the value n (n> 0) of the repeated page number signal 33 is set by the image processing unit 3. In accordance with this, the value of the selection signal 34 is also set to “1”.

  As a result, the first n pages of scanned images 12 are accumulated in the image memory 36. Further, as described above, the same scanned image 12 is also supplied to the selector 14, and the output result of the subtractor 15 (= output of the difference detection unit 40) is all “0”. This means that the tone correction data (TRC) is not updated by the subsequent correction TRC calculation unit 41 during the first n pages.

  Next, after the (n + 1) th page, the scan image 12 of the (n + 1) th page and the scan image of the first page held in the image memory 36 corresponding thereto are compared by the subtractor 15, and the (n + 1) th page and the first page are compared. The difference (ΔRGB) of the scanned images is output from the difference detection unit 40. Similarly, the n + 2 page is compared with the scanned image 12 of the second page. Similarly, the difference (change: ΔRGB) between each scanned image 12 and the initial image is output from the subtracter 15 of the difference detection unit 40.

  Next, the sample extraction unit 20 of the corrected TRC calculation unit 41 samples the RGB change amount of the scan image 12 from the difference image supplied from the difference detection unit 40 based on the address list separately extracted from the CMYK image 10. (Δrgb) is stored in the sample memory 37 in association with the input value (cmyk) of the CMYK image 10.

  As described above, since the value “1” is set in the selection signal 34 in the case of repeated printing, the mode parameter calculation unit 22 sets the second calculation condition that gives priority to the stability of the feedback result over the estimation accuracy. The mode parameter Δθ is calculated based on the penalty value, the integrated value integrated by the integrator 26, and the “θ0 value (where θ0 = 0)” stored in the second mode parameter memory 39.

  Here, the mode parameter Δθ calculated by the mode parameter calculation unit 22 is leveled (averaged) after the abnormal value is excluded by the leveling process 23. On the other hand, since the value of the selection signal 34 is “1”, the value of the second mode parameter memory 39 remains the initial value “0” and is not updated. Therefore, the mode parameter Δθ, which is the processing result of the leveling process, is output from the subtractor 24 as it is.

  In the TRC synthesis unit 25, the table values of the gradation correction table 16 are loaded into the reference TRC storage unit 42 prior to the start of the job. The mode curve storage unit 43 serving as the LUT is loaded with data of three predefined curves. Further, the integrator 26 is initialized to “0”.

  The output value (Δθ−θ0) from the subtractor 24 is subjected to inversion processing of polarity, and is added (= subtracted) by the integrator 26. The cumulative θ value that is the result of the addition process is used as a coefficient corresponding to each of the three colors. The combined TRC generation unit 44 calculates the combined TRC that is the above-described tone correction data by adding the product sum of the data of the mode curve read from the mode curve storage unit 43 for each color component to the reference TRC. . The composite TRC calculated in this way is written back to the gradation correction table 16. That is, the gradation correction data (TRC) stored in the gradation correction table 16 is updated to the synthesized TRC newly calculated by the TRC synthesis unit 25.

  When non-repeated printing or the number of repeated pages exceeds a predetermined upper limit, the value n of the repeated page number signal 33 is set to “n = 0”. The value of the selection signal 34 is set to “0” during the printing of a predetermined number of sheets from the start of the print job. In this case, the selector 14 of the difference detection unit 40 selects the predicted image 13. As a result, the difference detection unit 40 outputs the difference between the scanned image 12 and the predicted image 13 obtained by the colorimetric prediction unit 21. The subsequent processing flow until the data is stored in the sample memory 37 is the same as described above.

  While the value of the selection signal 34 is “0”, the mode parameter calculation unit 22 uses the observed value accumulated in the sample memory 37, the penalty value as the first calculation condition in which accuracy is given priority, and the integrator 26. The mode parameter is calculated based on the integrated value and the “θ0 value (in this state, θ0 = 0)” held in the mode parameter memory, and stored in the first mode parameter memory 38. As described above, when the second mode parameter memory 39 is updated with the mode parameter leveled by the leveling processing unit 23, the value of the selection signal 34 is changed to “1”. In the subsequent processing, the update processing of the tone correction data (TRC) in the tone correction table 16 is performed in the same manner as described above.

(Printer engine)
FIG. 3 is a vertical sectional view of a laser printer apparatus as an example of the printer engine 4. First, the configuration and operation of the developing unit 60k will be described. The photosensitive drum 50k rotates in the direction of arrow A in FIG. This rotational position is detected by a rotation detector 57 provided at the end of the photosensitive drum 50k. The charger 52 applies a uniform charge to the surface of the photosensitive drum 50k cleaned by the cleaning roller 51 with respect to the photosensitive drum 50k.

  Next, an electrostatic latent image is formed on the photosensitive drum 50k by scanning the surface of the photosensitive drum 50k while the laser beam 55 emitted from the laser unit 53 blinks in accordance with a signal from the exposure control device 65. To do. The scanning direction of the laser beam 55 at this time is the main scanning direction, and the rotation direction of the photosensitive drum 50k indicated by the arrow A in FIG.

  The formed electrostatic latent image is developed by a black (K) toner charged by a reverse potential supplied by a developing roller 54 to form a toner image. The toner image obtained by development is transferred to the intermediate transfer belt 61. The configuration and operation of the developing units 60c, 60m, and 60y are the same. That is, the developing units 60c, 60m, and 60y form toner images of cyan (C), magenta (M), and yellow (Y), and sequentially transfer them on the intermediate transfer belt 61. The belt cleaning mechanism 63 removes the color measurement patch on the intermediate transfer belt 61 by contacting the intermediate transfer belt 61 in synchronization with the position of the color measurement patch.

  The transfer roller 62 collectively transfers the C, M, Y, and K toner images superimposed on the intermediate transfer belt 61 onto a sheet conveyed on the sheet conveyance path 59. The fixing device 56 fixes the toner image on the paper on the paper surface by heat-pressing.

(TRC correction amount determination operation)
Next, the TRC correction amount determination operation based on the image measurement value of the color measurement region on the user image will be described. In the following description, the variable for each sample is considered as a random variable, and the subscript of the sample number is omitted.

  First, it is assumed that the initial value of the gradation correction data determined by calibration is set in the gradation correction table 16 of FIG. 2 corresponding to the color measurement region on the user image. When the CMYK gradation value on the input side of the gradation processing unit 31 at this time is (tilde c, tilde m, tilde y, tilde k), and each element is corrected by combining two predefined fluctuation modes. And put it as the following formula 1. The reason why the number of variable modes is set to two is to simplify the description. For this reason, the number of variable modes may be set to three or four, for example. For example, in the configuration example of the mode curve described later, the case of 3 modes is illustrated.

  In the above equation 1, c, m, y, and k are CMYK gradation values before correction, c0, m0, y0, and k0 are reference gradation characteristics, M1 is a first variation mode, and M2 is a second variation mode. The variation mode “θij” is a mode parameter (i = {c, m, y, k}, j = {1, 2}). In particular, the mode parameter is a real scalar, and the reference gradation characteristic and each variation mode M1, M2 are independent real vectors of the same dimension defined on the input range D of each c, m, y, k gradation value. It is. Note that the superscript is not an index, but merely a subscript for identification. (Mathematically, the above mode is the basis of the low-dimensional subspace of the vector space formed by the real valued function on D, but on the implementation, it is a curve implemented by an array or a combination of array and interpolation. Will be described later with reference to FIG.

  The input range D is usually implemented by a real number in the [0, 1] interval, an integer in the [0, 100] interval, or an integer in the [0, 255] interval. At this time, the relationship of the primary term related to “θ” in the above equation 1 is expressed as the following equation 2 by matrix notation.

  This Formula 2 becomes the conditions of the following Formula 2-1 and Formula 2-2.

  At this time, the mode parameter θ0 that approximates the initial printing state is calculated by the following equation (4) as a solution of the following equation (3).

  Note that “S” in Equation 3 is S = {(xn, cn) | n = 1, 2,..., Ns}, and the average position x = (i, j) and average of the sample image area A sample set extracted from a user image associated with an input tone value c = (c, m, y, k). Further, p0 = p0 (x) is an actually measured value by the scanner 150 in the initial printing, and L = L (c) is a predicted value by the colorimetric prediction unit 21.

  J (c) in Equation 3 is a Jacobian matrix (Jacobi matrix) for the input value c = (c, m, y, k) of L shown in Equation 5 below.

  In addition, “E” in Equation 3 and Equation 4 is an expected value (for example, sample average). In these mathematical expressions, some obvious arguments are omitted.

  Further, the small positive constants “w1” and “w2” in the following equation 6 are penalties for suppressing the magnitude of the change amount θi, and act as regularization weights that stabilize the solution of equation 4. As this value, an appropriate value is determined in advance based on experiments in relation to the singular value of the matrix JM. Hereinafter, the minute positive constants “w1” and “w2” are also referred to as “penalty value w1” and “penalty value w2”.

  In the process after the mode parameter θ0 in the initial state is determined, the change in the printing state from the initial state is estimated by the following equation (6).

  In Equation (6), “pnew = pnew (x)” is a newly observed user image actual measurement value, and “θold” is the value of the mode parameter immediately before used in this user image output. Further, in the two penalty terms of Equation 6, “w1” is a penalty value for suppressing the magnitude of the updated mode parameter “θnew”, and “w2” is a change from the previous “θold”. The penalty value to suppress. In particular, if the value of “penalty value w2” is set large, a rapid change in the mode parameter can be suppressed, and a more gradual response characteristic can be obtained. At this time, the new mode parameter θnew used in the printing of the next step is given by “θnew = θold−Δθ”.

  By the way, in the above equation 6, the area on the document for comparing pnew and p0 (for taking the difference) needs to be the same area. For this reason, the application of Equation 6 is limited to repeated printing of the same type of document. In order to avoid this restriction, “p0≈L + JMθ0”, which is an approximation based on the above-described equation (3), is used for the equation (6), and “Δ tilde θ = Δθ + θ0” is established. The update difference Δθ is determined.

  At this time, the solution of Equation 7 is obtained by Equation 8 below.

  As a result, as shown in the following Expression 9, a mode parameter used for printing in the next step can be obtained.

  Furthermore, since Equation 7 has the same structure as Equation 3, Equation 8 can be used for calculating the initial mode parameter θ0 instead of Equation 4. In particular, by repeatedly using Equations 8 and 9 for the same initial image sample set S = S0 with θ0 = 0 as the initial value, the solution of the penalty is estimated in the estimation of the initial mode parameter θ0. Shrinkage can be relieved. A specific algorithm will be described later.

(Configuration example of fluctuation mode curve (basis function))
Next, FIG. 4 shows an example of the above-described fluctuation mode curve. In the above description, in order to simplify the description, the case of the 2 mode has been described as an example, but FIG. 4 shows an example of selection of the mode curve (basis function) in the case of the 3 mode. In FIG. 4, the horizontal axis represents the input gradation value (%), and the vertical axis represents the gain obtained by normalizing the maximum value to “1”. The curve 47 is the first mode curve M1, the curve 48 is the second mode curve M2, and the curve 49 is the third mode curve M3. As these first to third mode curves M1 to M3, it is preferable to prepare a combination capable of effectively approximating the change in gradation characteristics with as few as possible, but it is not necessarily stuck to the main component. There is no need.

  FIG. 5 shows an example of a gradation correction curve formed by combining these mode curves. A thick curve 44 shown in FIG. 5 represents a gradation correction curve (synthetic TRC) formed by synthesizing the three mode curves of the first to third mode curves M1 to M3 of FIG. In this way, by synthesizing the first to third mode curves M1 to M3, a sufficiently smooth synthesized TRC can be obtained. In the case of the example of the mode curves M1 to M3, a product with a coefficient in which the fluctuation of the assumed gradation characteristic is approximately in the range of −10 to +10 with respect to the identical reference gradation characteristic (y = x). By doing so, it is possible to obtain a synthesized TRC that is not easily broken and approximated as a sufficiently smooth curve.

  For this reason, in this example, a common mode curve can be used for all colors of C, M, Y, and K. In particular, by using the above-described synthetic TRC formed by combining different mode curves specialized to the gradation characteristic change tendency for each color, the gradation characteristic change can be approximated with a smaller number of modes. Further, by approximating the gradation characteristic change with such a small number of modes, it is possible to estimate the gradation characteristic variation from a more biased small number of samples.

(Flow of θ estimation process)
The flowcharts of FIGS. 6 and 7 show the flow of the operation for calculating the mode parameter θ in the corrected TRC calculation unit 41 of FIG. For simplification of description, description of some functions such as the leveling processing unit 23 is omitted.

  First, the flowchart of FIG. 6 is an operation flow for estimating the mode parameter θ0 in the initial state immediately after calibration (when the selection signal 34 is “0”) when the number of repeated pages is “0”. In the flowchart of FIG. 6, in step S100, as described above, the calibration TRC is set in the gradation correction table 16, and output of user images over a large number of pages is started.

  Next, in step S101, the sample memory 37 stores image samples. The gradation correction table 16 and the sample memory 37 may be implemented as software on a personal computer device. The image samples stored in the sample memory 37 are stored as a combination of the difference ΔRGB values between the input CMYK values and the predicted image by the colorimetric prediction unit 21. In particular, the sample memory 37 sets “S0, C” as a mixed color sample set including a single color sufficiently including a cyan component (C), and “S0” as a mixed color sample set including a single color sufficiently including a magenta component (M). , m ”, a mixed color sample set including a single color sufficiently including a yellow component (Y) is“ S0, y ”, and a mixed color sample set including a single color sufficiently including a black component (K) is defined as“ S0, k ”. accumulate.

  Next, each process between step S102 to step S106 is executed for each color mixture sample set “S0, C”, “S0, m”, “S0, y”, and “S0, k”. Specifically, in step S103, the first calculation condition is set for the penalty values rw1 and rw2, and both “θnew” and “θ0” are initialized to “0”.

  In step S104, the process of updating “θnew” is repeatedly executed for a prescribed number of times, for example, N times (N is a natural number), according to the above-described equations (8) and (9). The number of iterations may be one (N = 1). However, at this time, “θ0” in Expression 8 is “0”.

  In step S105, “θnew” obtained as a result of the iteration is held as “θ0, x” (x = c, m, y, k).

  When the processing of step S102 to step S106 is completed for all “S0, x” (x = c, m, y, k), a cyan component is extracted from “θ0, c” in step S107. A magenta component is extracted from “θ0, m”, a yellow component is extracted from “θ0, y”, and a black component is extracted from “θ0, k”. Then, by recombining the extracted components, the initial mode parameter θ0 is constructed, and all the processes in the flowchart of FIG. 6 are completed.

  In the description of the flowchart of FIG. 6, the repeated page number is described as “0”. However, when the repeated page number is not “0”, the difference image stored in the sample memory 37 is the same as the initial print image. Since this is a difference, the value of the initial mode parameter θ0 is fixed to “0”.

  Next, the flowchart of FIG. 7 is a flow of operations for estimating the normal mode parameter θ (when the selection signal 34 is “1”). In this case, printing continues based on the TRC determined based on some “θnew” (step S110). In step S111, the image sample is stored in the sample memory 37 as in the description of FIG. At this time, a mixed color sample set including a single color sufficiently including a cyan component (C) is “SC”, a mixed color sample set including a single color sufficiently including a magenta component (M) is “Sm”, and a yellow component (Y). Are stored as “Sy”, and a mixed color sample set including a single color sufficiently including the black component (K) is stored as “Sk”.

  Next, each process of step S112 to step S116 is executed for each color mixture sample set “SC”, “Sm”, “Sy”, “Sk”. Specifically, in step S113, the second calculation condition is set for the penalty values w1 and w2, θ0 is set to the value obtained in the flow of the flowchart of FIG. 6, and “θold” is changed to “θnew” ( θold = θnew).

  In step S114, “θnew” is updated according to Equation 8 and Equation 9. Then, “θnew” is held as “θx” (x = c, m, y, k).

  When the processing from step S112 to step S116 is completed for Sx (x = c, m, y, k), the processing proceeds to step S117. In step S117, a cyan component is extracted from θc, a magenta component is extracted from θm, a yellow component is extracted from θy, and a black component is extracted from θk. Then, by recombining the components, the update mode parameter θnew is constructed, and all the processes in the flowchart of FIG. 7 are completed.

(Effects of the first embodiment)
As is apparent from the above description, the image processing system according to the first embodiment can maintain the initial printing state, and can perform stable color reproducibility in a print job based on a large number of primary colors. Can be obtained. In particular, even if the actual characteristics at the start of continuous printing are slightly deviated from the calibration, it is possible to maintain the initial printing characteristics by giving priority to color stability. Can provide).

[Second Embodiment]
Next, an image processing system according to the second embodiment will be described. If tone correction is performed in real time based on a printed user image, tone correction accuracy may be reduced due to an insufficient amount of information. Specifically, the tendency of user images to be printed varies, and some images have insufficient information amount due to the image configuration, and it is difficult to obtain sufficient gradation correction accuracy. . If the amount of information is insufficient, the calculation error of the gradation correction amount becomes large, and an unnecessarily strong correction is applied, resulting in a disadvantage that the difference from the target color becomes large (overcorrection). When this overcorrection occurs, the correction accuracy of gradation correction decreases, and it becomes difficult to maintain the reliability of printing.

  In the image processing system of the second embodiment, a plurality of images are set as one set, and an amount of information that is insufficient for a single image is compensated to prevent overcorrection and improve gradation correction accuracy. This is an example.

  In the following, an example in which tone correction is performed with an information amount in which a plurality of images are set as one set in the image system of the first embodiment described above will be described as a second embodiment. However, the gradation correction operation described in the second embodiment can also be applied to a conventional printing system that performs calibration. In this case as well, the same effects as described later can be obtained. For details, refer to the following description.

(Configuration of color control unit)
FIG. 8 is a block diagram showing each function of the color tone control unit 28. As shown in FIG. 8, the color tone control unit 28 includes a difference detection unit 40 and a corrected TRC calculation unit 41 (TRC: Tone Reproduction Curve). The difference detection unit 40 includes an RGB conversion unit 70, alignment units 71 and 72, and a subtractor 73.

  The correction TRC calculation unit 41 includes a region extraction unit 81, a main scanning deviation correction processing unit 82, a local θ calculation unit 83, a storage unit (buffer memory) 84, a sub-scanning deviation correction processing unit 85, a validity determination processing unit 86, and a transfer. A unit 87, a map generation unit 88, a colorimetry list generation unit 89, and a timer 90. The validity determination processing unit 86 includes a validity determination unit 91 and a θ correction unit 92.

  Such a difference detection unit 40 and the corrected TRC calculation unit 41 may be partially or entirely realized by hardware, or may be partially or entirely realized by software. An image processing program for realizing the difference detection unit 40 and the corrected TRC calculation unit 41 by software is a ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), or the like of the image forming apparatus 8. The above-described functions are realized by being stored in the storage unit and executed by a control unit such as a CPU (Central Processing Unit) of the image forming apparatus 8.

  In FIG. 8, the image processing unit 3 converts the original data 30 described in various input formats as described above as a CMYK master image in which each CMYK value is an 8-bit frame sequential pixel array for each page. This is supplied to the detection unit 40, the corrected TRC calculation unit 41, and the gradation processing unit 31.

  The gradation processing unit 31 converts, for example, a pixel array of 8 bits for each CMYK color plane by the area gradation method into a pixel array of gradations of the number of bits (for example, 2 bits) that can be drawn by the printer engine 4. Output. The image inspection unit 5 is actually directly connected (directly connected) to the printer engine 4 and scans the output image 6 formed by the printing process of the printer engine 4 inline.

  The difference detection unit 40 of the color tone control unit 28 converts the scan image (RGB) formed by the image inspection unit 5 scanning the output image 6 from the printer engine 4 and the CMYK master image from the image processing unit 3 to RGB. Based on the RGB master image converted into an image, a change (difference) in print reproduction color is detected. Then, the correction TRC calculation unit 41 of the color tone control unit 28 sets gradation correction data (TRC) for reducing the detected difference between the two in the gradation processing unit 31. Thereby, the reproduction color of the output image 6 can be stabilized.

  Specifically, the corrected TRC calculation unit 41 performs tone correction processing in real time based on the CMYK master image and data obtained from the difference between the RGB master image and the scan image. The RGB difference data (ΔRGB), which is the difference between the RGB master image obtained from the difference detection unit 40 and the scan image, and the coefficient (hereinafter referred to as θ value) for the color variation model from the CMYK master image obtained from the image processing unit 3. ) Is calculated and the gradation correction data (TRC) is updated and supplied to the gradation processing unit 31.

(Operation of difference detector)
That is, the operation of each unit of the difference detection unit 40 is as follows. The RGB conversion unit 70 has a data table in which CMYK values of the document data 30 and RGB values obtained from the printed document data 30 are associated with each other. The values in this data table are updated for each calibration. The RGB conversion unit 70 converts the CMYK value (CMYK master image) of the document data 30 into an RGB value by referring to the data table, and forms an RGB master image.

  The alignment unit 71 and the alignment unit 72 correct a positional shift between the scan image formed by the image inspection unit 5 scanning the printed material 6 inline and the above-described RGB master image (position Processing). The subtractor 73 detects the difference between the scanned image scanned by the image inspection unit 5 and the RGB master image, and supplies the difference data (ΔRGB) to the region extraction unit 81 of the corrected TRC calculation unit 41.

(Operation of corrected TRC calculation unit)
The operation of each unit of the corrected TRC calculation unit 41 is as follows. The map generation unit 88 extracts a small area that can be used as a color measurement area for each CMYK color from the CMYK master image, and forms a map in which all the extracted color measurement areas are collected. Although it is an example, the map generation part 88 extracts a small area | region based on the following conditions.

1. The size of the small area is 20 x 202 pixels (changeable),
2. The change in density of each color in the expanded area is small.
3. The size of the extended area is 50 x 502 pixels (can be changed),
4). The small area is more than the default value from the edge of the paper,
5. The average density of each color in the small area is within the default range,
6). The total amount of toner in the small area is below a certain value,
7). In the case of the CMY version, the density of the mixed color K is less than a predetermined threshold value.
8). In the case of the K plate, the density is a certain ratio or more with respect to the density of the mixed colors CMY. A map formed based on such conditions is used for generating a colorimetric list.

  The color measurement list generation unit 89 randomly selects a predetermined number of color measurement regions from each segment based on the above-described map to form a “color measurement list”. A segment is each region obtained by dividing an image evenly in the sub-scanning direction. The number of image divisions is, for example, 16 segments per page (changeable). The “θ value” described above is calculated based on the information of the color measurement area registered in the color measurement list.

  Next, the area extraction unit 81 extracts RGB difference data corresponding to the color measurement areas registered in the color measurement list, and supplies them to the main scanning deviation correction processing unit 82 together with the coordinate information and the CMYK gradation information. .

  Here, variation in density in the main scanning direction due to deviation of developer, toner, uneven charging, or the like may cause variation in the color printed in the main scanning direction (main scanning deviation). The main scanning deviation correction processing unit 82 calculates a main scanning deviation amount for the extracted colorimetric region based on the coordinate information and the CMYK gradation information. Then, the main scanning deviation correction processing unit 82 subtracts the calculated main scanning deviation amount from the RGB difference in the colorimetric region, thereby forming RGB difference data from which the influence of the main scanning deviation is removed. This is supplied to the subsequent local θ calculation processing unit 83.

  The local θ calculation unit 83 calculates the local θ for each segment described above based on the coordinate information of the color measurement region registered in the color measurement list, the CMYK information, and the RGB difference information subjected to the main scanning deviation correction process. . The calculated local θ of each segment is stored in the storage unit 84 such as a buffer memory. A segment for which it is difficult to obtain a sufficient number of colorimetric regions is an invalid segment, and the local θ calculated from the invalid segment is not used.

  Next, the photosensitive drum (symbol 50k in FIG. 3 and the like) is usually positioned by strict management. However, due to variations in the management accuracy of parts, a slight eccentricity is caused between the drum rotation axis and the center axis of the drum. Arise. When such eccentricity occurs, a periodic fluctuation (sub-scanning deviation) corresponding to the phase of the photosensitive drum occurs. The sub-scanning deviation appears periodically. For this reason, colors at positions where the drum cycle is shifted by half phase can be reduced by offsetting the influence of the sub-scanning deviation.

  The sub-scanning deviation correction processing unit 85 detects a pair of local θs calculated from an area in which the drum cycle is shifted by half phase among the local θs calculated by the local θ calculation unit 83. At this time, if more than a predetermined number of pairs are detected, the sub-scanning deviation correction processing unit 85 averages these local θ pairs and treats them as one local θ, and further calculates θ calculated from the pairs. Averaged to obtain the final θ value (leveled θ). Further, when the number of pairs is less than the predetermined number, the sub-scanning deviation correction processing unit 85 averages all the local θ to obtain a final θ value (leveled θ). The leveling θ is a gradation correction coefficient that is commonly used for an input image of a plurality of pages forming one set.

  The validity determination processing unit 86 is based on the timer information from the timer 90, the number of drum phase half-cycle pairs detected by the sub-scanning deviation correction processing unit 85, and the color measurement area information from the color measurement list generation unit 89. The validity of the leveled θ value for performing tone correction is determined, and the leveled θ value is corrected based on the determination result. The synthesizer 93 generates (updates) gradation correction data (TRC) based on the corrected θ value, and supplies it to the transfer unit 87. The transfer unit 87 supplies the generated gradation correction data (TRC) to the gradation processing unit 31. As a result, printing can be executed with a CMYK image that has been subjected to gradation correction processing, and an initial printed characteristic can be maintained, and a printed matter with stable color reproducibility can be obtained.

(Overall printing process flow)
Next, the overall print processing flow will be described with reference to the flowchart of FIG. It should be noted that a region extraction unit 81, a main scanning deviation correction processing unit 82, a local θ calculation unit 83, a sub-scanning deviation correction processing unit 85 (including leveling θ calculation), a validity determination processing unit 86, and a map generation described below. Each process of the unit 88, the colorimetric list generation unit 89, and the synthesis unit 93 is executed independently for each color plate of CMYK.

  First, in step S121, the difference detection unit 40 and the corrected TRC calculation unit 41 acquire image data (CMYK image data) of a print image from the image processing unit. In step S122, the RGB conversion unit 70 of the difference detection unit 40 converts the CMYK image data into RGB master data.

  In step S123, the subtractor 73 of the difference detection unit 40 calculates the difference (ΔRGB) between the RGB image data of the print image scanned by the image inspection unit 5 (scanner) and the RGB master data, and the corrected TRC calculation unit. 41.

  In step S124, the map generation unit 88 of the corrected TRC calculation unit 41 extracts a small area that can be used as a colorimetric area for each CMYK color from the CMYK master image based on the above conditions 1 to 8. A map is formed in which all the measured colorimetric areas are collected. In step S124, the color measurement list generation unit 89 of the corrected TRC calculation unit 41 randomly selects a predetermined number of color measurement regions from each segment based on the above-described map to form a “color measurement list”. To do.

  In step S125, the area extraction unit 81 of the corrected TRC calculation unit 41 extracts RGB difference data corresponding to the color measurement area registered in the color measurement list, and together with the coordinate information and the CMYK gradation information, the main scanning deviation. The correction processing unit 82 is supplied. The main scanning deviation correction processing unit 82 calculates a main scanning deviation amount for the extracted colorimetric region based on the coordinate information and the CMYK gradation information. The main scanning deviation correction processing unit 82 subtracts the calculated main scanning deviation amount from the RGB difference in the colorimetric region, thereby forming RGB difference data from which the influence of the main scanning deviation is removed.

  In step S125, the local θ calculation processing unit 83 determines the above-described segment based on the coordinate information of the color measurement region registered in the color measurement list, the CMYK information, and the RGB difference information subjected to the main scanning deviation correction processing. The local θ is calculated every time and stored in the storage unit 84.

  In step S126, the color tone control unit 28 determines whether or not the processing in steps S121 to S125 has been completed for all images for one set, which is a predetermined number of images. If the processing of step S121 to step S125 for all images for one set has not been completed, the processing is returned to step S121, and the processing of step S121 to step S125 is repeatedly executed. On the other hand, when the processes in steps S121 to S125 for all images for one set are completed, the process proceeds to step S127. When the processing in steps S121 to S125 is completed for all images for one set, the storage unit 84 stores local θ for each segment of all images for one set.

  Next, when the processing proceeds to step S127 after the processing of step S121 to step S125 for all images for one set is completed, the sub-scanning deviation correction processing unit 85 of the correction TRC calculation unit 41 performs the local θ calculation unit. Of the local θ calculated in 83, a pair of local θ calculated from a region where the drum cycle of the photosensitive drum (for example, the photosensitive drum 50k) is shifted by half phase is detected and averaged, and a final θ value ( The leveling θ) is calculated.

(Details of leveling θ calculation method)
A method for calculating such leveling θ will be described in detail. First, FIG. 10A shows that no in-plane deviation occurs in any of the main operation direction, which is the moving direction of the ink head relative to the paper, and the sub-scanning direction, which is the paper transport direction. An image in an ideal state in which colors are uniformly printed on a sheet is shown.

  However, in actuality, in many cases, periodic in-plane deviations occur in the main scanning direction and the sub-scanning direction as shown in FIG. To do. Such an in-plane deviation becomes noise when calculating the θ value and causes an error.

  For example, the CMYK master image including the object 100 illustrated in FIG. 10C is printed so as to overlap the image illustrated in FIG. In this case, as shown in FIG. 10C, the CMYK master image including the object 100 has no color variation as a whole, but the in-plane deviation shown in FIG. 10B occurs. When the image is overlaid and printed, the influence of the in-plane deviation shown in FIG. 10B appears strongly in the area of the object 100 where the color is printed as shown in FIG. For this reason, the θ value is originally “0”, but the error is influenced by the in-plane deviation. In addition, the same image does not always appear on the next and subsequent pages, and the appearance of in-plane deviations varies depending on the page, so even if tone correction is performed under the influence of in-plane deviation errors, the correct level Key adjustment is difficult.

  For this reason, the image forming system according to the second embodiment uniformly extracts the region where the deviation in which the color becomes dark and the region where the deviation in which the color becomes light are extracted, and cancels the influence of both. The effect of in-plane deviation is reduced.

  Specifically, in the case of the main scanning deviation, as shown in FIG. 10E, the influence of the sub-scanning direction is small. For this reason, the influence of the deviation can be eliminated to some extent by calculating in advance the deviation amount appearing at the coordinates in the main scanning direction and removing it from the RGB difference information of each colorimetric region. However, in order to obtain higher gradation correction accuracy, it is desirable that colorimetric regions are extracted uniformly from the main scanning direction.

  In the case of sub-scanning deviation, the influence of the main scanning direction is small as shown in FIG. 10 (f), but periodicity exists due to the presence of paper between papers, but the phase of deviation changes from page to page. It is difficult to calculate the deviation amount in advance.

  For this reason, the image forming system according to the second embodiment regards the segments at positions shifted by a half phase of the drum cycle as a pair, and uses the average of the local θ calculated by these segments to obtain the deviation. To offset the effects of In addition, since the deviation of the segment that was not selected as a pair remains, the local θ of the segment that was not selected is not used for the leveling θ calculation. Further, when it is difficult to detect a pair of segments due to the arrangement of the images, the sub-scanning deviation correction processing unit 85 does not calculate the average of the local θ between the pairs, but calculates the total average of the local θ of the effective segments. calculate. Thereby, the influence of the whole sub-scanning deviation can be reduced.

  Although it is an example, the sub-scanning deviation correction processing unit 85 detects the segments in which the deviations appear in opposite phases, such as the segment A and the segment B shown in FIG. In addition, the sub-scanning deviation correction processing unit 85 detects the segment C and the segment D having a small deviation as a pair because they are located in opposite phases.

  In the example of FIG. 10 (f), eight segments are illustrated, but the number of segments per page is arbitrary, and may be divided into, for example, 16 segments per page as described above. Moreover, as long as it is in a set, you may detect the segment of another page as a pair.

(Validity judgment operation)
Next, in step S128 of the flowchart of FIG. 9, the validity determination unit 91 of the validity determination processing unit 86 uses the leveling θ value calculated by the sub-scanning deviation correction processing unit 85 for the gradation correction processing. A validity determination process that is a determination of whether or not the value is appropriate is performed. In step S128, the θ correction unit 92 of the validity determination processing unit 86 performs a correction process on the leveled θ value based on the determination result of the validity determination unit 91.

  Specifically, when the validity is determined, the amount of information necessary for calculating the θ value (the amount of information used for calculating the θ value) and the possibility of an error in calculating the θ value are considered. There is a need. In this example, the validity is determined from two factors: the amount of information necessary for calculating the θ value (the amount of information used for calculating the θ value) and the possibility of an error in calculating the θ value. However, the validity may be determined based on one of the factors. In this case, the calculation amount of the validity determination calculation can be reduced, and the determination result can be obtained at high speed.

  The amount of information necessary for calculating the θ value relates to the number of colorimetric regions, the number of segment pairs, and the coverage of gradation colors. If the number of colorimetric areas is large, the amount of information that can be used increases, so the validity improves. The same is true for the number of pairs of segments. The numerical value “25 sets” shown in Table 1 below is a threshold value for determining whether or not there are a sufficient number of pairs, and the validity determination unit 91 has 25 or more pairs. If there is, the average θ is calculated by averaging the local θ for each pair, and if it is less than 25 pairs, the average for each pair is not calculated and the entire segment is averaged to calculate the leveled θ.

  Regarding the completeness of the gradation color, if the gradation of the colorimetric area in the color plate is within the predetermined range, there is not enough information for the gradation outside the predetermined range, and the variation in the color of the range is calculated correctly. It may not be possible. For this reason, it is possible to improve the above-described validity determination accuracy by obtaining information on a wide range of gradations.

  The possibility of the calculation error of the θ value is caused by in-plane deviation, processing time, and the like. As described above, when the in-plane deviation is included, the accuracy of the θ value calculation is reduced. For this reason, it is preferable to obtain a sufficient amount of information from a wide range of colorimetric regions to suppress the influence of in-plane deviation. In the main scanning direction, the validity determination unit 91 divides one page into three parts, and detects the ratio of the number of colorimetric regions existing in each divided range, so that the colorimetric points are widely distributed. Judge whether or not. Also, regarding the sub-scanning deviation, if it is widely distributed, the number of segment pairs is expected to increase according to this distribution. Therefore, the validity determination unit 91 determines the sub-scanning deviation based on the number of segment pairs.

  Regarding the processing time, since the user image is printed in parallel with the calculation of the θ value, the color printed by the printer engine 4 may change over time. For this reason, there is a high possibility that the calculated θ value does not follow the actual color change that varies with time. For this reason, the validity determination unit 91 determines that the processing time is lost if the printing process is not completed within a certain period of time.

  Hereinafter, each condition used for such validity determination processing will be described using Tables 1 to 5 shown as examples. Tables 1 to 5 show specific conditions for determining the validity of the leveling θ calculated for each set of images. The numerical values in each table are the total values for each color plate and each set. Moreover, this numerical value is an example and may be arbitrarily changed according to the design or the like.

  First, the validity determination unit 91 determines that the calculated leveled θ value is “highly valid” when the conditions shown in Table 1 below are met.

  As shown in Table 1, when the color measurement area is classified into three gradation areas of highlight, middle, and shadow according to the color version, there are 187 or more color measurement areas in each gradation area (basic color Gradation distribution) on the left when the image is divided into three in the main scanning direction. Center. There are more than one-sixth of the total number of colorimetric areas in the three areas on the right, and there are more than 25 valid segment pairs located in the opposite phase of the sub-scanning deviation. When the condition that the printing process is completed within the condition is satisfied, since the information of a sufficient amount of information has been acquired and the error has been reduced, the validity determination unit 91 calculates the calculated leveling θ The value of is determined to be “highly valid”.

  In the case of the conditions shown in Table 1, it is considered that errors in both the main scanning deviation and the sub scanning deviation can be sufficiently suppressed. In addition, it is considered that the distribution is in a wide range even when viewed for each gradation. In Table 1, the condition for the number of colorimetric areas is blank, but this means that a colorimetric area that is not used is generated by processing a pair of sub-scanning segments, so designation in this part is meaningful. The reason for this is that there is no such thing, and a specific number is specified by a gradation color instead.

  Next, the validity determination unit 91 determines that the calculated leveled θ value is “highly valid” when the conditions shown in Table 2 below are met.

  As shown in Table 2, when the colorimetric areas are classified into the three gradation areas of highlight, middle, and shadow according to the color version, each of the gradation areas has 1/6 or more of the total number of colorimetric areas. Exists on the left side when the image is divided into three in the main scanning direction. Center. In the three areas on the right side, there are 1/6 or more of the colorimetric areas, the total number of colorimetric areas is 560 or more, and the printing process is completed within the set time. When the condition is satisfied, the validity determination unit 91 determines that the calculated leveling θ value is “highly valid”.

  The conditions in Table 2 were such that the sufficient number of sub-scanning segment pairs could not be acquired, but the colorimetric area was sufficient, and therefore the effect of sub-scanning deviation could be covered. is there. In the conditions of Table 2, since specific numerical values are set for the determination of the number of colorimetric areas, the gradation color is determined by the ratio of the number of colorimetric areas.

  Next, the validity determination unit 91 determines that the calculated leveled θ value is “medium validity” when the conditions shown in Table 3 below are met.

  As shown in Table 3, when the color measurement area is classified into three gradation areas of highlight, middle, and shadow according to the color version, there is one or more gradation areas where there are 187 or more color measurement areas. When the image is divided into three in the main scanning direction, there are more than 1/8 color measurement areas in the left, center, and right areas, respectively, and the total number of color measurement areas is 360 or more. When the printing process is completed within the set time and each of the conditions in Tables 1 and 2 is not satisfied, the validity determination unit 91 determines that the calculated leveling θ value is , “Relevance is medium”.

  The conditions in Table 3 are conditions indicating that any of main scanning, sub-scanning, and gradation colors may not cover the error occurring in the leveling θ.

  Next, the validity determination unit 91 determines that the calculated leveled θ value is “low validity” when the conditions shown in Table 4 below are met.

  As shown in Table 4, when there are one or more colorimetric areas in total, the printing process is completed within the set time, and the conditions in Tables 1 to 3 above are not satisfied In addition, the validity determination unit 91 determines that the calculated leveling θ value is “low validity”. That is, the conditions in Table 4 are conditions indicating that a minimum number of colorimetric areas exist. Under this condition, there is a high possibility that the error will be considerably large. Therefore, the validity determination unit 91 determines that the calculated leveled θ value is “low validity”.

  Next, the validity determination unit 91 determines that the calculated leveling θ is “invalid” when the conditions shown in Table 5 below are met.

  Table 5 is a condition that does not satisfy any of the conditions in Tables 1 to 4 and indicates that no colorimetric region exists. In this case, since there is no material for determining color variation, the calculated leveling θ is discarded.

  In many cases, the amount of information for accurately calculating the θ value is insufficient with only the colorimetric region obtained for each page. In the case of the image forming system according to the second embodiment, several pages are collected. The θ value is calculated for each set and fed back to the gradation processing unit 31. This facilitates securing the number of colorimetric areas and the number of pairs of sub-scanning segments. In the above-described image forming system, the above-described validity determination process is also performed for each set, so that determination according to the θ value calculation mechanism of the image forming system of the second embodiment can be performed. .

  The number of pages in one set is the number of pages for which the number of colorimetric areas is ensured and the number of pairs of sub-scanning segments can be sufficiently empirically secured with a document such as a general catalog (for example, about 8 pages in A3 size) ) Is set in advance. Alternatively, the number of pages in one set is not set in advance, and the printing and scanning of the document are repeated, and the number of colorimetric areas and the number of pairs of sub-scanning segments corresponding to the conditions in Table 1 or Table 2 described above A dynamic determination method may be used in which the number of pages obtained at one time is set as one set.

(Θ value correction operation)
Next, in step S128 of the flowchart of FIG. 9, the θ correction unit 92 of the validity determination processing unit 86 corrects the value of the leveled θ based on the determination result of the validity determination unit 91, thereby generating an error. To reduce the effects of Tables 6 to 9 shown below are threshold values and correction values for determining whether to correct the θ value according to the conditions described in Tables 1 to 5 above. Note that, as an example, the relationship between the numerical values shown in Tables 6 to 9 is “numerical value A> numerical value B> numerical value C> numerical value D” and “coefficient F> coefficient G> coefficient H”. Such numerical values and coefficients may be set based on how to take a variation model.

  First, Table 6 is a table showing thresholds and correction values for determining whether or not to correct the leveled θ value determined to be “high” based on the conditions of Tables 1 and 2 above. It is. As shown in Table 6, the θ correction unit 92, when the leveling θ value determined to be “high” is a value equal to or greater than the numerical value D, for example, generates a concentration abnormality via the notification unit. Notification (voice message, text error message, electronic sound, etc.) and leveling θ value is corrected to “0”. In this case, the gradation correction data (TRC) is not updated. In addition, when the leveled θ value determined to be “high” is a value that is less than the numerical value D and greater than or equal to the numerical value C, the θ correction unit 92 multiplies the leveled θ value by a coefficient H as an example. To correct. The θ correction unit 92 does not correct the leveled θ value when the leveled θ value determined to be “high” is less than the numerical value C.

  Next, Table 7 is a table showing thresholds and correction values for determining whether to correct the leveled θ value determined to be “medium” based on the conditions of Table 3 above. . As shown in Table 7, if the leveling θ value determined to be “medium” is a value equal to or greater than the numerical value D, the θ correction unit 92, for example, generates a concentration abnormality via the notification unit. Notification (voice message, text error message, electronic sound, etc.) and leveling θ value is corrected to “0”. In this case, the gradation correction data (TRC) is not updated. The θ correction unit 92 multiplies the leveled θ value by a coefficient G as an example when the leveled θ value determined to be “medium” is less than the numerical value D and greater than or equal to the numerical value B. To correct. The θ correction unit 92 does not correct the leveled θ value when the leveled θ value determined to be “medium” is less than the numerical value B.

  Next, Table 8 is a table showing thresholds and correction values for determining whether or not to correct the leveled θ value determined to be “low” based on the conditions of Table 4 above. . As shown in Table 8, if the leveling θ value determined to be “low” is equal to or greater than the numerical value D, the θ correction unit 92 generates a concentration abnormality via a notification unit, for example. Notification (voice message, text error message, electronic sound, etc.) and leveling θ value is corrected to “0”. In this case, the gradation correction data (TRC) is not updated. The θ correction unit 92 multiplies the leveled θ value by a coefficient F as an example when the leveled θ value determined to be “low” is a value less than the numerical value D and greater than or equal to the numerical value A. To correct. The θ correction unit 92 does not correct the leveled θ value when the leveled θ value determined to be “low” is less than the numerical value A.

  Next, Table 9 is a table showing thresholds and correction values for determining whether to correct the leveled θ value determined to be “invalid” based on the conditions of Table 5 above. . As shown in Table 9, the θ correction unit 92 corrects the leveled θ value to “0” when the validity is determined to be “invalid”. In this case, the gradation correction data (TRC) is not updated.

  A large θ value of the leveling θ means that the color fluctuates accordingly. For this reason, the θ correction unit 92 determines that there is a high possibility that the influence of the error is strong if the θ value is equal to or greater than a predetermined threshold, and conversely if the θ value is less than the predetermined threshold, Judgment is weak. If the tone correction data (TRC) is generated as it is due to the influence of the error and the tone correction data (TRC) is generated as it is, there is a high possibility of overcorrection, so the θ correction unit 92 corrects the θ value so that it becomes a small value. .

  On the other hand, when the θ value is small, the possibility of overcorrection is low even if there is an error, and if correction is made, there is a high possibility that control becomes insufficient and it is difficult to eliminate color variation. In this case, the θ correction unit 92 does not correct the θ value.

  In addition, the θ value increases even when a large color variation occurs, not the influence of errors, and correction for the θ value is performed. In this case, too, by repeating the tone correction processing for several sets, The color variation can be gradually restored while preventing the correction. In addition, when a separate function for correcting color variation is provided in addition to a function for performing real-time gradation correction processing in the image forming system of the second embodiment, such as engine process control. The double correction is performed together with the function correction process, so that the disadvantage of overcorrection can be minimized. If the θ value is too large, there is a high possibility that an abnormality has occurred in the printer engine 4, so the θ correction unit 92 notifies the occurrence of an abnormality through the notification unit (voice message, text error) Message or electronic sound, etc.) and processing for eliminating the abnormality of the printer engine 4 is performed.

(Effects of correcting the θ value)
FIG. 11 is a graph showing the relationship between density fluctuation and the number of printed sets. The thick line graph indicates the color variation when the θ value correction is not performed by the validity judgment, and the thin line graph indicates the color variation when the θ value correction is performed by the validity judgment. A dotted line indicates a reference density. In the gradation correction processing in real time, it is preferable to perform the gradation correction processing so that the color variation is close to the reference density indicated by the dotted line.

  If the influence of the error becomes large at a certain point in time, unless the θ value is corrected, the density change becomes larger than the reference density as shown by the bold line graph. If the density change becomes large, the error will become large even when returning to the original value in the next set, and there is a possibility that the correction will be overtaken again.

  On the other hand, if the above-described correction processing is performed on the θ value when the influence of the error becomes large at a certain point in time, the density change can be suppressed small as shown in the thin line graph. Further, before the influence of the error on the θ value becomes large, the control is the same as when the θ value is not corrected, and the control is not insufficient.

(Printing process)
Next, when correction processing according to the validity of the leveled θ value is performed on the leveled θ value in this way, the process proceeds to step S129 in the flowchart of FIG. In step S129, the synthesis unit 93 updates the tone correction data (correction TRC) to the value supplied from the θ correction unit 92. The gradation correction data (correction TRC) is transferred to the gradation processing unit 31 by the transfer unit of the correction TRC calculation unit 41 in step S130. In step S131, the gradation processing unit 31 performs gradation correction processing based on the updated correction TRC on the CMYK master image acquired by the image processing unit 3, and supplies the processed image to the printer engine 4. Thereby, printing reflecting the correction TRC can be executed.

  Finally, in step S132, the printer engine 4 determines whether printing of all pages designated by the user has been completed. If printing of all pages has not been completed (step S132: No), the process returns to step S122, and the processes after step S122 are repeated. On the other hand, when the printing of all pages is completed (step S132: Yes), the process of the flowchart of FIG. 9 ends.

(Effect of the second embodiment)
As is apparent from the above description, the image processing system according to the second embodiment can compensate for an insufficient amount of information in a single image by setting a plurality of images as one set. In addition, considering the amount of information in the set (the number of colorimetric regions for each density distribution and the amount of in-plane variation considered to be given to the image), the validity of the set (the leveled θ value described above) The adequacy of). A threshold value or adjustment magnification for adjusting the correction amount is determined according to the determination result.

  Specifically, when the correction amount (leveled θ value) exceeds a predetermined threshold value, the correction amount (leveled θ value) is multiplied by the adjustment magnification on the assumption that the influence of the error is high. Thus, it is possible to suppress the correction amount and prevent the inconvenience of overcorrection. For example, if a large correction amount has been calculated due to an actual sudden color change rather than an error, it is difficult to perform sufficient correction within that set, but overcorrection is required in subsequent sets. The gradation correction process can be performed while gradually approaching the correct correction amount.

  For this reason, it is possible to prevent the inconvenience that the correction amount suddenly increases, and to approach the correct correction amount with a small number of sets by comparing the method for determining the upper limit of the correction amount and the method for skipping correction of the set. . Therefore, the gradation correction accuracy can be improved.

  Finally, each of the above-described embodiments has been presented as an example, and is not intended to limit the scope of the present invention. For example, in the description of each of the above-described embodiments, the user image colorimetric RGB by the scanner 150 is used as an evaluation value for the sake of simplicity, but instead of RGB, Lab ( L: brightness, a: green / red, b: blue / yellow), etc. may be used. By using a color value of a uniform color space such as Lab, it becomes possible to perform control more faithful to the color difference. For example, when Lab values are used, the RGB values in the above formulas (1) to (8) are replaced with Lab values, and the Jacobian matrix of RGB → Lab conversion is set to “J ′”, and the Jacobian matrix “J” is changed to “J ′”. Replace with "J'J". In this case, the same effect as described above can be obtained.

  Further, in the description of the above-described embodiment, in order to simplify the description, the user image colorimetry RGB by the image inspection unit 5 is used as an evaluation value. However, instead of RGB, Lab converted RGB is used. (L: brightness, a: green / red, b: blue / yellow) or the like may be used. By using a color value of a uniform color space such as Lab, it becomes possible to perform control more faithful to the color difference. In this case, the same effect as described above can be obtained.

  The above-described novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. Further, the embodiments and modifications of the embodiments are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalent scope thereof.

1 User's personal computer device (user PC)
2 Network 3 Image processing unit 4 Printer engine 5 Image inspection unit 6 Output image 7 Server device 8 Image forming device 9 Engine control unit 10 CMYK image 11 Registration correction unit 12 Scan image 13 Predicted image 14 Selector 15 Subtractor 16 Tone correction table DESCRIPTION OF SYMBOLS 17 Gradation conversion part 18 Colorimetry area extraction part 19 Address correction part 20 Sample extraction part 21 Colorimetry prediction part 22 Mode parameter calculation part 23 Leveling process part 24 Subtractor 25 TRC composition part 26 Accumulator 28 Color tone control part 30 Manuscript Data 31 Gradation processing unit 32 Main unit unit group 33 Repetitive page number signal 34 Selection signal 35 Calculation condition selector 36 Image memory 37 Sample memory 38 First mode parameter memory 39 Second mode parameter memory 40 Difference detection unit 41 Correction TRC calculation Part 42 Quasi-TRC storage unit 43 Mode curve storage unit 44 Composite TRC generation unit 70 RGB conversion unit 71 Registration unit 72 Registration unit 73 Subtractor 81 Area extraction unit 82 Main scanning deviation correction processing unit 83 Local θ calculation unit 84 Storage unit 85 Sub Scanning deviation correction processing unit 86 Validity determination processing unit 87 Transfer unit 88 Map generation unit 89 Colorimetry list generation unit 90 Timer 91 Validity determination unit 92 θ correction unit 93 Composition unit 100 Object 150 Scanner

JP 2017-187585 A JP 2017-64979 A JP 2012-205124 A

Claims (17)

A reflection characteristic detection unit for detecting the reflection characteristic of each output image on each print medium formed before and after the time among print media on which an output image corresponding to input image data is formed;
An image processing apparatus comprising: a gradation characteristic correction unit that corrects gradation characteristics of the input image data so that the reflection characteristics of the output images of the print media detected by the reflection characteristic detection unit match. The reflection characteristic detector is
Gradation control parameter calculation for calculating gradation control parameters for controlling gradation characteristics of basic colors of an output image formed on the print medium based on reflection characteristics of the output image formed on the print medium Part
The gradation characteristic correction unit
A first gradation control parameter which is a gradation control parameter serving as a reference value calculated by the gradation control parameter calculation unit, and a second gradation control parameter newly calculated by the gradation control parameter calculation unit The image processing apparatus according to claim 1, wherein a gradation characteristic of the input image data is corrected based on a comparison result with. The gradation control parameter calculation unit includes the first gradation control parameter and the first gradation control parameter based on a calculation condition switched based on any of the number of printed sheets, a printing time, or an image measurement value of the color measurement region, or a combination thereof. The image processing apparatus according to claim 2, wherein the second gradation control parameter is calculated. The reflection characteristic detector is
When the same image is sequentially formed on each print medium, the gradation control parameter for controlling the gradation characteristic of the basic color of the output image formed on the print medium is set as the reflection characteristic of the initial image set. A gradation control parameter calculation unit that calculates based on the difference between the measurement value and the measurement value of the reflection characteristic of the image set other than the initial image set,
The gradation characteristic correction unit
The image processing apparatus according to claim 1, wherein a gradation characteristic of the input image data is corrected based on a gradation control parameter calculated by the gradation control parameter calculation unit. The image processing apparatus according to claim 2, wherein the gradation control parameter calculation unit calculates three or less gradation control parameters for each basic color. A prediction unit that forms a prediction value that predicts the reflection characteristics of the output image;
The gradation control parameter calculation unit
When different images are sequentially formed on each of the print media, the first gradation control is performed by using the predicted value as the reference value and comparing the measured value of the reflection characteristic of the initial image with the predicted value. A parameter is calculated, the image after the initial image is compared with the predicted value, and the second gradation control parameter is calculated,
When the same image is sequentially formed on each print medium, the first gradation control parameter is calculated from the measurement value of the reflection characteristic of the initial image set, and based on input image data other than the initial image set, The image processing apparatus according to claim 2, wherein the second gradation control parameter is calculated. Based on a predetermined amount of information, the gradation control parameter calculated by the gradation control parameter calculation unit is a reasonable value to be used for correcting the gradation characteristic of the input image data in the gradation characteristic correction unit. A determination unit for determining whether or not there is,
A correction unit that corrects the value of the gradation control parameter based on the determination result of the determination unit;
The image processing apparatus according to claim 2, further comprising: The image processing apparatus according to claim 7, wherein the determination unit performs the determination using the number of colorimetric regions of the input image data as the predetermined amount of information. The image processing apparatus according to claim 7, wherein the determination unit performs the determination using a number of colorimetric areas corresponding to a predetermined gradation of the input image data as the predetermined amount of information. The image processing apparatus according to claim 7, wherein the determination unit performs the determination using a colorimetric region distribution of the output image. The determination unit performs the determination with a predetermined plurality of pages as one set,
The image processing apparatus according to claim 7, wherein the correction unit performs the correction by setting a predetermined plurality of pages as one set. The image processing apparatus according to claim 7, wherein the determination unit performs the determination by setting the number of pages when a predetermined number of colorimetric regions of the output image are obtained as one set. A two-stage threshold value, a first threshold value for the gradation control parameter value and a second threshold value that is higher than the first threshold value;
When the value of the gradation control parameter is greater than or equal to the first threshold value and less than the second threshold value, the correction unit uses a correction value obtained by multiplying a predetermined coefficient to calculate the gradation control parameter value. The image processing apparatus according to claim 7, wherein the value is corrected. A two-stage threshold value, a first threshold value for the gradation control parameter value and a second threshold value that is higher than the first threshold value;
The image processing apparatus according to claim 7, wherein the correction unit does not correct the value of the gradation control parameter when the value of the gradation control parameter is less than the first threshold value. A two-stage threshold value, a first threshold value for the gradation control parameter value and a second threshold value that is higher than the first threshold value;
The image processing apparatus according to claim 7, wherein the correction unit corrects the value of the gradation control parameter to “0” when the value of the gradation control parameter is equal to or greater than the second threshold value. . A gradation processing unit that performs gradation correction of the input image;
A printing unit for printing the input image;
An image reading unit for reading a print image of the input image printed by the printing unit;
An image processing system comprising: the image processing apparatus according to claim 1. Computer
A reflection characteristic detection unit for detecting the reflection characteristic of each output image on each print medium formed before and after the time among print media on which an output image corresponding to input image data is formed;
It is made to function as a gradation characteristic correction part which corrects the gradation characteristic of the input image data so that the reflection characteristic of each output image of each print medium detected by the reflection characteristic detection part matches. Image processing program.