JP2023035673A - Image forming apparatus and image forming method - Google Patents

Abstract

To provide a technique to achieve color stabilization at a higher speed.SOLUTION: Of areas in a read image obtained by a sensor reading an image formed by using a plurality of colors of recording materials, for a mixed area where the recording materials are mixed in a number of colors exceeding the number of colors read by the sensor, a result obtained by excluding the influence of one recording material of the plurality of colors of recording materials is estimated. The characteristics of the recording materials are estimated from the read image. Correction processing is performed for reproducing characteristics to be a target on a recording medium based on the characteristics of every recording material estimated for the individual areas of the read image. The characteristics of the other recording materials excluding one recording material of the plurality of colors of recording materials are estimated based on a result of estimation for the mixed area.SELECTED DRAWING: Figure 1

Description

The present invention relates to image forming technology.

2. Description of the Related Art Ink jet printers, which form images by ejecting ink from a plurality of nozzles, are widely used as image forming apparatuses for forming arbitrary images on paper. Alternatively, a printer employing an electrophotographic system that forms an image using a laser photoreceptor and charged toner is also widely used.

By the way, in electrophotography, it is known that the color tone of the formed image changes depending on the environment such as the remaining amount of toner in the apparatus and the ambient temperature and humidity. In the ink jet method, it is known that the color changes depending on the surrounding environment such as the aging of the piezo elements and heaters that control the adhesion and ejection of ink around the nozzles, and the temperature and humidity. There is known a technique for continuously suppressing changes in tint by performing stabilization processing at regular intervals in response to changes in the surrounding environment and time.

In the stabilization process, a dedicated chart is often output to measure the characteristics of the recording material such as toner or ink of each color. However, the recording material, paper, and time that are originally used by the user to output the desired image are used for outputting the dedicated chart, leading to an increase in cost. Also, if the chart output interval is widened to avoid an increase in cost, the stabilization accuracy may decrease. Patent Literature 1 discloses a technique of performing stabilization processing based on an output user image to maintain stabilization accuracy while avoiding an increase in cost.

JP 2014-71433 A

In the above-mentioned Patent Document 1, in the color stabilization process, the apparent recording amount of each toner is estimated by searching from the result of colorimetry of the multi-color toner image, and output is performed by changing the image forming conditions of each toner. The image is color-stabilized.

At this time, for colors containing redundancy that cannot be distinguished by the RGB sensor, after exhaustively enumerating candidates, estimation processing is performed by excluding candidates suspected of ink replacement.

However, in the estimation process using the search, the time required for estimation is limited, and there are cases where the printing speed must be reduced or the correction interval must be widened. In particular, in a one-pass ink jet machine using a long head, correction may be made for each head or chip that constitutes the long head, or for each nozzle in the most subdivided unit. As the unit of processing is subdivided in this manner, high-speed processing is required. For this reason, the above-described estimation process, in which candidates are listed exhaustively through searching for colors including redundancy, tends to become a time constraint particularly in a one-pass type inkjet machine using a long head. The present invention provides a technique for attaining color stability at a higher speed.

According to one aspect of the present invention, in each area of a read image obtained by using a sensor to read an image formed using recording materials of a plurality of colors, recording materials that exceed the number of colors read by the sensor are mixed. color reduction means for estimating a result of excluding the influence of one of the recording materials of the plurality of colors, estimation means for estimating characteristics of the recording material from the read image, and the reading correcting means for performing correction processing for reproducing target characteristics on a recording medium based on the characteristics of each recording material estimated by the estimating means for each region in the image, wherein the estimating means It is characterized by estimating the characteristics of the recording materials other than one of the recording materials of the plurality of colors based on the result of the estimation by the color reduction means for the mixed area.

According to the configuration of the present invention, color stability can be achieved at a higher speed.

FIG. 2 is a block diagram showing a hardware configuration example of an image forming system; 2 is a diagram illustrating a printer applied to an image forming unit 107; FIG. 3 is a block diagram showing an example of the functional configuration of an image processing unit 106; FIG. 6 is a flow chart of printing a user image and updating a correction table; FIG. 4 is a diagram showing an example of a correction table; It is a figure explaining color reduction processing. FIG. 16 is a diagram showing an example of primary color characteristics 1608; 10 is a flowchart of primary color estimation processing performed in step S407; FIG. 5 is a diagram for explaining correction table update processing; The figure explaining a target characteristic. The figure explaining 2nd Embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. In addition, the following embodiments do not limit the invention according to the scope of claims. Although multiple features are described in the embodiments, not all of these multiple features are essential to the invention, and multiple features may be combined arbitrarily. Furthermore, in the accompanying drawings, the same or similar configurations are denoted by the same reference numerals, and redundant description is omitted.

[First Embodiment]
<Hardware Configuration Example of Image Forming System>
First, a hardware configuration example of an image forming system according to the present embodiment will be described with reference to the block diagram of FIG. FIG. 1 shows the main configuration related to each process described below, and does not show all the configurations of the image forming system.

A CPU (Central Processing Unit) 100 executes various processes using computer programs and data stored in a RAM (Random Access Memory) 101 and a ROM (Read Only Memory) 102 . Thereby, the CPU 100 controls the operation of the entire image forming system, and executes or controls various processes described as those performed by the image forming system. In this embodiment, the CPU 100 controls the overall image forming system, but the overall image forming system may be controlled by sharing the processing among a plurality of pieces of hardware.

The RAM 101 has an area for storing computer programs and data loaded from the ROM 102 or the external storage device 105 and an area for storing an image read by the image acquisition unit 108 . Further, the RAM 101 has an area for storing data received from the outside via the I/F unit 109 and a work area used when the CPU 100 and the image processing unit 106 execute various processes. Thus, the RAM 101 can appropriately provide various areas.

The ROM 102 stores setting data for the image forming system, computer programs and data for starting the image forming system, computer programs and data for basic operations of the image forming system, and the like.

An operation unit 103 is a user interface such as a keyboard, a mouse, a touch panel, a numeric keypad, and various button groups.

A display unit 104 is a display device having a screen such as a liquid crystal screen or a touch panel screen, and can display processing results by the CPU 100 and the image processing unit 106 in the form of images, characters, and the like.

The external storage device 105 is a large-capacity information storage device such as a hard disk drive. The external storage device 105 stores an OS (operating system), computer programs and data for causing the CPU 100 and the image processing unit 106 to execute various processes, and the like. The data stored in the external storage device 105 includes, for example, various matrices used in later-described processing. Computer programs and data stored in the external storage device 105 are loaded into the RAM 101 under the control of the CPU 100 and are processed by the CPU 100 and the image processing unit 106 .

The image processing unit 106 is implemented by a processor capable of executing a computer program or a dedicated image processing circuit, and performs various image processing for converting an image input as a print target into an image that can be output by the image forming unit 107 . to run. In this embodiment, the image processing unit 106 also executes color stabilization processing based on the result of reading a user image (an image that the user desires to print). Instead of preparing a dedicated processor as the image processing unit 106, the CPU 100 may operate as the image processing unit 106 to perform various processes.

The image forming unit 107 forms an image on a recording medium such as paper using a recording material based on an image acquired from the image processing unit 106, the RAM 101, the external storage device 105, the I/F unit 109, and the like. In this embodiment, the image forming unit 107 uses at least four types of printing materials such as cyan (C), magenta (M), yellow (Y), and black (K).

The image acquisition unit 108 is an image sensor (line sensor or area sensor) for capturing the image formed on the recording medium by the image forming unit 107 . In the present embodiment, the image acquisition unit 108 (image sensor) has three output values having peaks at different wavelengths (R (red) output value, G (green) output value, and B (blue) output value). output value). The output value is color information such as luminance value.

The I/F unit 109 functions as an interface for connecting the image forming system and external devices. For example, the I/F unit 109 functions as an interface for exchanging data with a communication device using infrared communication, a wireless LAN (Local Area Network), or the like, and as an interface for connecting to the Internet.

All of the units described above are connected to the bus 110 and can exchange data via the bus 110 . However, the image forming system may have a configuration in which the above units (for example, the image forming unit 107) are connected via the I/F unit 109. FIG.

<Image forming unit 107 and image acquiring unit 108>
First, the image forming section 107 will be described. In this embodiment, the image forming unit 107 ejects cyan (C), magenta (M), yellow (Y), and black (K) inks from nozzles onto the recording medium to form an image on the recording medium. It is assumed that the printer is an inkjet type printer that forms a

As shown in FIG. 2(a), the image forming section 107 has recording heads 201 to 204 on a frame forming a structural member of the printer. Each of the recording heads 201 to 204 has a plurality of nozzles for ejecting K, C, M, and Y inks, arranged in a predetermined direction within a range corresponding to the width of a recording paper 206 as a recording medium. It is of line type.

Also, as shown in FIG. 2B, the recording heads 201 to 204 are constructed by combining a plurality of head modules (recording units). For example, the head modules 201a, 201b, and 201c of the print head 201 are arranged alternately with respect to the transport direction of the print medium. The same applies to the head modules 202a, 202b, and 202c of the printhead 202, the head modules 203a, 203b, and 203c of the printhead 203, and the head modules 204a, 204b, and 204c of the printhead 204. FIG.

Further, as shown in FIG. 2(c), the head module 201a further has chip modules 201a-1 to 201a-5 (recording units). At this time, it is assumed that each chip module is connected to an independent substrate. This also applies to other head modules.

FIG. 2D is a diagram of one of the chip modules viewed from the recording medium surface side, and shows that the chip module has a plurality of nozzles (recording units). In the example shown in FIG. 2(d), the chip module has 16 nozzles. The resolution of the nozzle arrangement of the nozzle row for each ink color is, for example, 1200 dpi.

A recording paper 206 as a recording medium is conveyed in a direction indicated by an arrow 207 in FIG. be. While the recording paper 206 is being conveyed, ink is ejected from a plurality of nozzles of each of the recording heads 201 to 204 according to recording data (images converted by the image processing unit 106). An image for one raster corresponding to each of the nozzle arrays 204 to 204 is sequentially formed. By repeating the ink ejection operation from the recording heads 201 to 204 onto the conveyed recording paper 206, for example, one page of image can be recorded on the recording paper 206. FIG.

Further, as shown in FIG. 2A, the image acquisition unit 108 is installed downstream of the recording heads 201 to 204 in the conveying direction indicated by an arrow 207, and covers the entire surface of the recording paper 206 so as to read the entire surface of the recording paper 206. It is a line sensor that

The image acquisition unit 108 sequentially captures images of the conveyed recording paper 206 in parallel with image formation on the recording paper 206 by the recording heads 201 to 204, so that each pixel obtains pixel values of three channels of RGB. generate an image (two-dimensional image) with Then, the CPU 100 saves the generated image in the external storage device 105 as a two-dimensional read image.

Note that the image forming unit 107 is not limited to the full-line type apparatus shown in FIG. For example, the image forming unit 107 may be a so-called serial type printing apparatus that performs printing by scanning a printing head in a direction that intersects the conveying direction of the printing paper. Further, as the image forming method by the image forming unit 107, an electrophotographic method in which an image is formed using a laser photoreceptor and charged toner, or a thermal transfer method in which solid ink is vaporized by heat and transferred to printing paper can be applied. can be done.

Also, the image acquisition unit 108 is not limited to the line sensor as shown in FIG. For example, the image acquisition unit 108 may be a device that includes a carriage for moving in a direction intersecting the conveying direction of the recording paper and has a configuration that acquires an arbitrary area with a width smaller than that of the recording paper 206 .

<Outline of color stabilization processing>
Next, color stabilization processing performed by the image processing unit 106 will be described. Even if each print head forms the same image due to factors such as the adhesion of ink around the nozzles, the aging of the piezo elements and heaters that control ink ejection, and the ambient environment such as temperature and humidity, the image formed on the print medium may be different. It is known that the image density varies. Such changes in image density are visually recognized as density unevenness or color shift, and may impair the quality of the image (the quality of the printed matter on which the image is printed), so it is preferable to suppress them as much as possible.

As shown in FIG. 2, in the image forming system according to the present embodiment, images formed by the recording heads 201 to 204 are captured by the image acquisition unit 108 ( line sensor). That is, by estimating the density change described above from the image read by the image acquisition unit 108 and performing color stabilization processing, the density change can be suppressed. At this time, if a dedicated chart is used in the color stabilization process, costs such as paper, recording material, and time are required. Therefore, it is preferable to estimate from the read image of the user image instead of using the dedicated chart. That is, as shown in FIG. 2, the image forming system according to the present embodiment mixes four color inks of C, M, Y, and K to form an arbitrary image. Therefore, the density change due to aging occurs independently for each of C, M, Y, and K colors. Therefore, by performing independent gamma correction processing corresponding to each color on the recording amount of ink corresponding to each color, it is possible to effectively reduce the change in density. On the other hand, it is not always the case that there exists an area in which each color is formed singly on the user image. In such a case, it is necessary to estimate the density change corresponding to each color ink from reading of a multi-color area in which a plurality of colors are mixed.

At this time, the change in density corresponding to each color of ink often changes for each head module or chip module. Furthermore, even within the same module, the amount of change is often different for each nozzle. In order to correct in units of these modules or nozzles, it is necessary to estimate density changes for each unit to be corrected and perform gamma correction processing. Therefore, it is desirable to estimate the density change for each nozzle and perform gamma correction processing. However, as described below, processing may be performed in units of chip modules or head modules instead of in units of nozzles, depending on the processing load.

For example, in the example shown in FIG. 2, if each of the print heads 201 to 204 is to be corrected independently, four (C, M, Y, and K) density change estimation processes are required. Alternatively, in the case of each head module, as shown in FIG. 2B, three head modules for each color are further independently corrected, so 12 estimation processes are required for four colors×three head modules. Similarly, in the chip module unit shown in FIG. 2(c), since there are 5 more chip modules, 60 times of estimation processing are required. estimation process is required.

As described above, the finer the unit of correction, the more times the estimation process is performed. Therefore, high-speed estimation processing is required in order to perform correction in fine units while maintaining the same printing speed.

Further, if a density change is detected using a dedicated chart in the color stabilization process, it is possible to efficiently obtain desired density information necessary for the color stabilization process. However, from the user's point of view, the dedicated chart, which is not the user image that the user originally wants to output, costs paper, recording material, time, and the like. For this reason, it is preferable to use a user image instead of using a dedicated chart.

In this embodiment, the output values (RGB values ((output value of R, output value of G, output value of B)) output by the image acquisition unit 108 are used as dimensions (color A color conversion matrix (matrix) for conversion into space) is created and stored in advance, and output values (RGB values) output by the image acquisition unit 108 reading the user image are obtained each time the user image is printed. High-speed estimation can be performed by converting using the color conversion matrix and updating the correction table based on the values obtained by the conversion.

The color space in which the correction process is performed here can be any color space related to density on the formed image 400, which will be described later. This embodiment will be described using the reflectance at a certain wavelength corresponding to RGB on the recording medium. Still other examples of color spaces include optical density, luminance, lightness, and the like.

Next, the above color conversion matrix (corresponding to the color conversion matrix 1607 described later) will be described. Various kinds of arithmetic processing for obtaining the color conversion matrix 1607 described below may be performed by the CPU 100, may be performed by the image processing unit 106, or may be performed by an apparatus separate from the image forming system according to the present embodiment. The system may go. Also, the color conversion matrix 1607 obtained (generated) by various kinds of arithmetic processing described below is stored in the external storage device 105 . Note that the storage destination of the color conversion matrix 1607 is not limited to the external storage device 105, and the color conversion matrix 1607 is saved in another device that can communicate with the image forming system, such as an external device that can communicate via the I/F unit 109. You can

In this embodiment, prior to printing a user image, a dedicated chart including a uniform pattern of each single ink color is output and read. At this time, the image acquisition unit 108 reads a uniform pattern of different ink usage amounts (application amounts) for each ink, thereby obtaining RGB values for each application amount (RGB values read by the image acquisition unit 108).

Further, the above uniform pattern is read again (with the above reading) by a known colorimeter capable of acquiring spectral information, and the spectral reflectance characteristic ρ for each ink usage amount (application amount) is acquired.

Next, a color conversion matrix is calculated for converting the RGB values into the reflectance of each color of CMY ink. Specifically, first, the wavelength for each color ink is determined from the spectral reflectance characteristics of each color ink of CMY. For this wavelength, a representative wavelength (representative wavelength) that characterizes the color of each ink is selected. For example, a wavelength of 650 nm is selected as a representative wavelength for C ink (ink of color C), a wavelength of 550 nm is selected as a representative wavelength of M ink (ink of color M), and a wavelength of 450 nm is selected for Y ink (ink of color Y). is chosen as the representative wavelength.

Next, at the respective representative wavelengths of C, M, and Y, the change in reflectance with respect to the ink ejection amount of each color is calculated from the output result of the above-mentioned colorimeter as a spectral reflectance characteristic (reflectance) ρ _c (k _c ), ρ _m ( _km ), ρ _y (k _y ).

Here, k _x (where x = c, m, y) represents the amount of ejection for ink color x, and ρ _x (k _x ) is for each ink color x when the amount of ejection of ink color x is k _x . represents the reflectance at representative wavelengths defined in The ejection amount is expressed in [%], and indicates the nozzle resolution and the percentage of dots ejected in each grid of 1200 dpi. For example, the ejection amount k _c =100 [%] represents that the C ink is ejected to all grid points of the nozzle resolution, and ρ _c (100) is the reflectance of the ink color C at the representative wavelength of 650 nm at that time. represents

Next, from the obtained reflectance ρ _x (k _x ) and the RGB values read from the uniform pattern by the image acquisition unit 108, the following formula is established. Let Rx(k _x ), Gx(k _x ), and Bx(k _x ) be the RGB values with respect to the ejection amount k _x of the ink color x. First, focusing on the representative wavelength of the ink color C in the uniform pattern of the ink color C (that is, x=c), the following (Equation 1) is established.

Each row in (Equation 1) is obtained by linearly combining RGB values with unknown coefficients a, b, and c for a patch with a certain amount of exposure. Here, coefficients a, b, and c are common to all rows. Here, (Equation 1) is abbreviated as (Equation 2) below, with the implant amount being represented as a variable _kc .

(Formula 1) and (Formula 2) represent the same formula. Next, similarly, focusing on the representative wavelength of the ink color C in the uniform pattern of the ink color M, the following (Equation 3) is established.

The difference from (Equation 1) is that all reflectances on the left side are set to 1 instead of measured values, and the RGB values on the right side are replaced by R _m , G _m , and B _m , which are values for patches of ink color M. This is the point. Unknown coefficients a, b, and c represent the same coefficients as in (Formula 1). Similar to (Formula 2), this is also abbreviated as (Formula 4) below.

Further, by focusing on the wavelength of the ink color C in the uniform pattern of the ink color Y, an equation similar to (Equation 3) is established. Since it is the same procedure, only the abbreviated description is described as (Formula 5) below.

Unknown coefficients a, b, and c common to (Formula 2), (Formula 4), and (Formula 5) appear. be able to.

Here, the meaning of the formulas that have appeared so far will be explained. (Equation 2) is a formula that linearly combines the RGB values for each ink ejection amount for a single color of C ink (single color of recording material) to equal the actually measured reflectance at that time. This represents the reproducibility assumption that the reflectance can be calculated from the RGB values read by the image acquisition unit 108 . The coefficients for the RGB values at that time are a, b, and c.

On the other hand, (Equation 4) and (Equation 5) indicate that the linear combination of the RGB values using the above coefficients a, b, and c for a single color of C ink yields the same reflectance when M ink and Y ink are targets. 1. That is, the linear combination of the RGB values read by the image acquisition unit 108 and the coefficients a, b, and c represents the representative wavelength of C ink, and the RGB values when targeting M ink and Y ink are It does not respond to input, indicating that it does not have an absorption (non-reflection) component. While (2) had the actual value on the left hand side, the 1 on the left hand side of (4) and (5) is an assumption, which acts as a conceptual constraint.

In (Formula 6) including the reproducibility of (Formula 2) and the constraints of (Formula 4) and (Formula 5), find an approximate solution that minimizes the error for vectors (a, b, c) be able to. Then, using the coefficients a, b, and c obtained in this way, a linear combination can be made again for the RGB values.

The left-hand side ρ′ _c (k _c ) obtained by the following (Equation 7) is a pure element Unlike the ρ _c (k _c ) reproduction of , it takes on the characteristic of being more directional with respect to the representative wavelength of the C ink. Conversion to a reflectance having such characteristics works effectively when a user image, which can be any color as well as a single ink color, is targeted, unlike a dedicated chart. Actually, similar equations can be established not only for the representative wavelength of the C ink, but also for the representative wavelength of the M ink and the representative wavelength of the Y ink. Substituting a 3×3 matrix X for the coefficient matrix (a, b, c) and approximately solving the following (Equation 8), the matrix X is the color conversion matrix 1607 .

By multiplying the RGB values read by the image acquisition unit 108 by the color conversion matrix 1607 obtained by performing arithmetic processing according to each of the above formulas, the color space ρ', which is the directional reflectance to be corrected, is obtained. _c (k _c ), ρ′ _m (k _m ), ρ′ _y (k _y ) can be obtained.

The color space in which the correction process is performed is not limited to the reflectance described above, and a configuration is also possible in which R'G'B' obtained by applying 1DLUT or logarithmic conversion to RGB values is subjected to matrix conversion. For example, when the estimation process is performed using the density d _x (x=c, m, y) of the x ink obtained by logarithmic conversion, the color conversion matrix 1607 is obtained by combining the RGB values and the density d _x according to (Equation 9) below. may be used.

Note that in (Equation 9), instead of the reflectance of 1 in (Equation 8), density 0 is placed in the value at the wavelength different from the ink color on the left side, which is the constraint condition. Further, the matrix side may also include terms of secondary or tertiary terms of RGB values, and for example, it is possible to use a matrix X according to (Equation 10) below.

In the case of (Equation 10), the matrix X has a size of 6 rows and 3 columns. It is the same in that the RGB values are multiplied by this matrix X to obtain ρ′ _c (k _c ), ρ′ _m (k _m ), ρ′ _y (k _y ).

Basically, the color conversion matrix 1607 needs to be generated at least once in advance for each condition such as a printing medium, and there is no need for reading with a spectral sensor or obtaining the approximate solution for each printing. At each printing, the generated color conversion matrix 1607 is read, and matrix multiplication using the color conversion matrix 1607 is performed on the obtained RGB values. Therefore, when the reading by the spectral sensor and the calculation processing are constrained by cost and speed, color stabilization can be performed at a higher speed or at a lower cost.

However, when using a matrix X that satisfies the above-mentioned (Equation 8) to (Equation 10), the accuracy of estimation processing may decrease in an area where K ink is mixed. Particularly in an area where four CMYK inks are mixed, it is necessary to estimate four values (reflectance for each of CMYK) from three RGB values. At this time, due to redundancy, there are a plurality of reflectance combinations that satisfy the RGB values. However, comprehensively estimating the combinations and analyzing their validity increases the processing load, and may impose a time constraint, especially when correction processing is performed in units of nozzles or chip modules. Although it is possible to skip areas where ink is mixed in excess of the number of sensor outputs, nozzles having only such areas cannot be corrected.

In view of the above points, in the present embodiment, in areas where the number of inks that exceeds the number of sensor outputs is mixed, color reduction processing is performed to exclude the influence of one of the inks, and the number of sensor output values that are not excluded is Corrects ink up to This realizes correction from the four-color mixed area while maintaining the speed.

The configuration of the image processing unit 106 that executes the above processing and the color stabilization processing will be described below with reference to FIGS. 3 and 4. FIG. FIG. 3 is a block diagram showing a functional configuration example of the image processing unit 106. As shown in FIG.

A conversion unit 1601 converts an input image read from the external storage device 105 into an image corresponding to the color reproduction range of the image forming unit 107 . The input image is described, for example, according to color coordinates (R, G, B) in a color space coordinate such as sRGB, which is the expression color of the monitor. A conversion unit 1601 converts an input image into color signals corresponding to a plurality of inks used in the image forming unit 107 . For example, if the image forming unit 107 uses inks of black (K), cyan (C), magenta (M), and yellow (Y), the input image is converted to 8 each of K, C, M, and Y by the conversion unit 1601. It is converted into an image (CMYK image) consisting of bit color signals. The CMYK image output by the conversion unit 1601 represents the amount of ink used (ie, the amount of ink applied) that the image forming unit 107 ejects onto the recording medium to express the image. For the above conversion by the conversion unit 1601, known techniques such as matrix calculation processing and processing using a three-dimensional LUT (lookup table) can be used.

Note that the input image is not limited to an RGB image in which each pixel has R, G, and B pixel values (that is, each pixel has an RGB value), and each pixel has C, M, Y, and K pixel values. It may be an image (CMYK image). However, even in that case, the conversion unit 1601 converts C, M, Y, and K in the input image (CMYK image) into different C', M', Y', and K', respectively, due to restrictions on the total amount of ink and color management. It is preferable to perform processing using a four-dimensional LUT for conversion.

A correction unit 1602 performs correction processing for stabilizing colors against aging. More specifically, the correction unit 1602 performs gamma correction processing on the CMYK image output from the conversion unit 1601 using a correction table in which conversion destination signal values (pixel values) for each module or nozzle are registered. conduct. An example of the correction table according to this embodiment is shown in FIG. The correction table in FIG. 5 is a correction table for performing conversion in units of head modules.

The correction table shown in FIG. Corrected color signal values corresponding to color signal values (0, 16, 32, . . . , 240, 255) are stored. For example, if the pixel value (input color signal value) of the K pixel corresponding to the head module 201a of the printhead 201 is 32, the correction unit 1602 changes the pixel value of the pixel to 28.

As described above, in this embodiment, correction processing is performed by referring to the correction table for each of C, M, Y, and K. FIG. In this way, by correcting the CMYK image representing the ink ejection amount, it is possible to cancel the change in density.

When the correction process is performed in units of chip modules or nozzles instead of in units of head modules, the correction table has the same number of columns as the number of chip modules or the number of nozzles.

In the correction table shown in FIG. 5, input color signal values that do not exist in the LUT are calculated using interpolation processing from neighboring input color signal values stored in the LUT. Of course, the color signal values after conversion may be stored for all input color signal values without using interpolation processing. Alternatively, correction processing can be performed by function conversion or matrix conversion instead of the correction table.

Returning to FIG. 3, an HT (halftone) processing unit 1603 converts a CMYK image corrected by the correction unit 1602 into a CMYK image with the number of gradations that can be directly represented by the image forming unit 107 (HT processing). ) to generate a halftone image. In the present embodiment, "the number of gradations that can be directly expressed by the image forming unit 107" is assumed to be a binary value of ON or OFF of ink dots. Specifically, an 8-bit per pixel image is converted to a 1-bit binary halftone image having a value of either 0 or 1 for each pixel. In this embodiment, the HT process uses a known method such as dithering. Since the threshold matrix necessary for dither processing is created in advance and stored in the external storage device 105, it is read from the external storage device 105 and used as necessary. A method such as an error diffusion method can also be applied instead of the dither processing.

Then, the HT processing unit 1603 outputs the halftone image generated from the CMYK image as described above to the image forming unit 107 and causes the image forming unit 107 to print the halftone image on a recording medium.

The image acquisition unit 108 reads the formed image 400 printed on the recording medium by the image forming unit 107 (the image printed on the recording medium according to the halftone image generated by the HT processing unit 1603) as described above. Get the RGB values of

A color conversion unit 1604 reads out a color conversion matrix 1607 stored in the external storage device 105 . Then, the color conversion unit 1604 uses the read color conversion matrix 1607 to obtain the “directional reflectances of CMY inks (ρ′ _c , ρ′ _m , ρ' _y ).

If the resolution of the read image acquired by the image acquisition unit 108 and the resolution of the CMYK image are different, it is preferable to perform resolution conversion on the read image in order to match the two. A known nearest neighbor method, binary interpolation, bicubic interpolation, or the like can be used for resolution conversion.

Further, when skew of the recording medium or aberration of the spectroscopic sensor is large, it is preferable to perform geometric correction on the sensor output value. Known affine transformation and projective transformation can be used for geometric correction. In that case, the image processing unit 106 needs to have a processing unit that performs resolution conversion and geometric correction. Alternatively, the image acquisition unit 108 may output the sensor output value to the color conversion unit 1604 after performing resolution conversion, geometric correction, and the like in units of a predetermined number of lines when acquiring a raster image. Further, at this time, the image forming unit 107 may add a marker to facilitate the above conversion and form an image on the recording medium.

The color reduction unit 1605 detects that the number of inks that exceeds the number of sensor outputs (the number of colors read by the sensor: 3 in the case of an RGB sensor) is mixed in each area in the read image obtained by the image acquisition unit 108. If so, the area is subjected to the color reduction process described below.

The estimating unit 1606 estimates the reflectance of each ink from the directional reflectance by the number of inks equal to or less than the number of sensor outputs for each area obtained by the conversion unit 1601 . The primary color characteristic 1608 referred to by the color reduction unit 1605 and the estimation unit 1606 will be described later.

<Printing the user image and updating the correction table>
Next, printing of a user image and updating of the correction table by the image forming system according to this embodiment will be described with reference to the flowchart of FIG. The user operates the operation unit 103 to specify the file name (path name) of the image to be printed (user image) among the images saved in the external storage device 105 and the number of prints (number of prints). do. Therefore, in step S401, CPU 100 acquires the print content including the file name of the user image specified by the user and the number of prints.

In step S<b>402 , the conversion unit 1601 acquires from the external storage device 105 the image (user image) with the file name included in the print content acquired by the CPU 100 . Hereinafter, the user image is assumed to be an "RGB 8-bit format image" in which the R, G, and B pixel values of each pixel are represented by 8 bits. Then, the conversion unit 1601 converts the user image acquired from the external storage device 105 into a CMYK image as described above. A correction unit 1602 acquires the correction table stored in the external storage device 105, and uses the acquired correction table to perform gamma correction processing on the CMYK image as described above. At this time, the correction unit 1602 performs gradation conversion for suppressing density unevenness for each module or each nozzle. The HT processing unit 1603 generates a halftone image by performing the above HT processing on the CMYK image corrected by the correction unit 1602 . The HT processing unit 1603 outputs the generated halftone image to the image forming unit 107 and causes the image forming unit 107 to print the halftone image on a recording medium. The image acquisition unit 108 acquires RGB values for each pixel by reading the formed image 400 printed on the recording medium by the image forming unit 107 .

In step S403, the color conversion unit 1604 selects one unselected rectangular area as an attention area when the read image obtained by the image acquisition unit 108 reading the formed image 400 is divided into a plurality of rectangular areas. . The shape of the rectangular area is not limited to a specific shape, and may be a square, a rectangle, another polygon, or a circle (including an oval). good. Also, the rectangular area may be an area composed of a plurality of pixels, or may be an area of one pixel.

In step S404, the color conversion unit 1604 uses the color conversion matrix 1607 to convert the RGB values of each pixel in the region of interest to the corresponding "CMY ink directional reflectances (ρ' _c , ρ' _m , ρ' _y ) The color conversion unit 1604 reads the color conversion matrix 1607 from the external storage device 105 at any timing up to step S403.

In step S405, the color reduction unit 1605 acquires the number of mixed colors (number of mixed colors) in the corresponding area positionally corresponding to the attention area in the CMYK image converted by the conversion unit 1601 in step S402. For example, the color reduction unit 1605 acquires the number of colors whose color signal value (pixel value) is not 0 in the corresponding area as the number of mixed colors. If the obtained mixed color number is 3 or less, the process proceeds to step S407, and if the mixed color number is 4 or more, the process proceeds to step S406.

In step S407, the color reduction unit 1605 performs primary color estimation processing for estimating the reflectance of each ink forming the mixed color. On the other hand, in step S406, the color reduction unit 1605 performs color reduction processing. Details of the color reduction processing in step S406 and the primary color estimation processing in step S407 will be described later.

In step S408, the color conversion unit 1604 determines whether or not all of the above plurality of rectangular regions have been selected as regions of interest. As a result of this determination, if all of the plurality of rectangular areas are selected as the target area, the process proceeds to step S409. On the other hand, if there remains a rectangular area that has not been selected as a target area among the plurality of rectangular areas, the process proceeds to step S403.

In step S409, the correction unit 1602 updates the above correction table. Details of the processing in step S409 will be described later. In step S410, CPU 100 determines whether or not the user image has been printed by the number of prints included in the print content (printing specified by the user has been completed).

As a result of this determination, when the user image has been printed by the number of prints included in the above print content, the processing according to the flowchart of FIG. 4 ends. On the other hand, if the number of user images printed is less than the number of prints included in the print content, the process proceeds to step S402.

<Color reduction processing>
The color reduction processing in step S406 will be described. In this embodiment, as described above, when the area of interest selected in step S403 contains a mixture of inks exceeding the number of sensor outputs (3 in the case of an RGB sensor), the area of interest is area, and color reduction processing is performed on the mixed area. In the color reduction process, the reflectance of any ink is directly estimated from the input value and excluded from the reflectance after the color conversion process in step S404. After that, based on the reflectance after exclusion, primary color estimation processing in step S407 is performed as a region of interest in which inks less than the number of outputs of the sensor are mixed.

At this time, it is preferable to select a color that is predicted to be the most stable as the color to be excluded (excluded object). For example, based on ink viscosity, pigment concentration, etc., the exclusion priority may be held in advance for each ink type, and color exclusion processing may be performed based on the priority. For example, for areas where CMYK is mixed, it may be determined in advance to exclude K ink, for example, as ink whose ink characteristics are less likely to change over time. Alternatively, it may be determined to exclude Y ink, for example, as the ink with the smallest change in reflectance with respect to ejection amount fluctuation. Alternatively, the usage history of each module may be stored, and ink colors formed by modules with less usage history may be excluded. Alternatively, the colors to exclude can be selected based on a curve 601 as shown in FIG.

The horizontal axis in FIG. 6 represents the ink ejection amount. The vertical axis represents the degree of instability V, which represents the influence of the variation for each ink ejection amount on color development. By using the curve 601, the ink ejection amount can be converted into the instability V of each ink.

At a high ejection amount at which almost the entire surface is covered with dots, or at an ejection amount at which little ink is ejected, the characteristics of nozzles and modules have little effect on color development. In the example shown in FIG. 6, the degree of instability V is set low around 0 or 100, which is such an implantation amount.

On the other hand, with an ejection amount (kh in the example shown in FIG. 6) at which the area covered with dots and the area not covered with dots are almost equal, the difference in landing error and ejection amount has a large effect on color development. Color development is likely to be affected by the characteristics of the nozzle and the module with respect to such an ejection amount, so the degree of instability V is set high in the example shown in FIG.

At this time, by performing exclusion processing on the ink with the lowest obtained instability V, it is possible to perform exclusion processing on the most stable ink.

For example, the curve 601 can be obtained by outputting a uniform pattern for each ejection amount without performing correction processing in the correction unit 1602 . That is, the image acquisition unit 108 reads the output pattern, and the dispersion value of the signal values on the read image data corresponding to each pattern can be used as the degree of instability V. FIG. Alternatively, the dispersion value obtained from the reflectance of the representative wavelength obtained by applying the color conversion matrix X described above to the signal value, or the dispersion value of the density value obtained by logarithmically transforming the reflectance may be used. can also

After determining the colors to be excluded according to the above, the color reduction unit 1605 acquires the amount of exposure of the excluded colors in the region of interest. For example, when excluding the K ink, the K ink application amount kk is calculated by kk=AveK/255×100 from the average color signal value AveK obtained by averaging the color signal values of the K ink in the region of interest. do.

Further, the color reduction unit 1605 refers to the primary color characteristics 1608 created and stored in advance prior to user printing, and calculates the directional reflectance (ρ′ _c , ρ′ _m , ρ′ _y ).

An example of primary color characteristics 1608 is shown in FIG. The table shown in FIG. 7 shows the correspondence of the directional reflectance (ρ′ _c , ρ′ _m , ρ′ _y ) to the K ink ejection amount kk.

To create the table shown in FIG. 7, first, the image acquisition unit 108 reads an image formed by a uniform pattern with a single K ink and different ejection amounts. Then, the directional reflectances ρ′ _c , ρ′ _m , and ρ′ _y obtained by converting the K signal value read by the image acquisition unit 108 with the above-described color conversion matrix X, and the above-described impact amount and , are associated with each other and stored. If ink colors other than K ink may be selected as excluded colors, a table corresponding to each ink color is created and stored in advance.

By dividing the directional reflectance of the target area by the directional reflectance of the K ink thus obtained from the input signal value, the color reduction unit 1605 obtains the directional reflectance that does not include the influence of the K ink. calculate. Since the directional reflectance of a region in which a plurality of inks are mixed is determined by the product of the directional reflectance of each ink, the division by the directional reflectance of any ink is This process is based on the assumption that is excluded.

Let ρ′ _c0 , ρ′ _m0 , ρ′ _y0 be the directional reflectances of the region of interest, and ρ′ _ck , ρ′ _mk , ρ′ _yk be the directional reflectances of the K ink obtained from the input signal values. At this time, the reflectances ρ′ _c , ρ′ _m , and ρ′ _y not including the influence of the K ink are respectively ρ′ _c =ρ′ _c0 /ρ′ _ck , ρ′ _m =ρ′ _m0 /ρ′ _mk , It can be calculated by ρ' _y =ρ' _y0 /ρ' _yk .

Note that if the image forming unit 107 is equipped with special color inks such as red, green, and purple in addition to CMYK inks, five or more types of inks may coexist in the region of interest. In this case, the exclusion process may be repeatedly executed in descending order of the instability V until the number of inks is equal to or less than the number of sensor outputs.

<Primary Color Estimation Processing>
The primary color estimation processing in step S407 will be described. In step S407, the estimating unit 1606 estimates the reflectance of each ink from the directional reflectance of the number of inks equal to or less than the number of sensor outputs. The primary color estimation processing performed by the estimation unit 1606 in step S407 will be described with reference to the flowchart in FIG. The processing according to the flowchart of FIG. 8 is processing for a corresponding region that is positionally corresponding to the attention region in the CMYK image converted by the conversion unit 1601 in step S402. However, in practice, the processing according to the flowchart of FIG. 8 is performed for each attention area (that is, each corresponding area in the CMYK image).

In step S801, the estimation unit 1606 determines whether the corresponding area contains K ink. As a result of this determination, if the corresponding area contains K ink, the process proceeds to step S803, and if the corresponding area does not contain K ink, the process proceeds to step S802.

In step S802, the estimation unit 1606 estimates the reflectance of CMY inks in the corresponding area. In this embodiment, the directional reflectances (ρ′ _c0 , ρ′ _m0 , ρ′ _y0 ) of the region of interest obtained in step S404 or step S406 or the directional reflectances after color reduction (ρ′ _c , ρ′ _{m 2} , ρ' _y ) is used as the reflectance of each ink. That is, the reflectance of C ink is ρ′ _c , the reflectance of M ink is ρ′ _m , and the reflectance of Y ink is ρ′ _y , and the estimation process ends.

A function or table that associates the relationship between the directional reflectance and the reflectance at the representative wavelength of each ink is held, and based on this relationship, the reflectance of each ink is converted to the reflectance at the representative wavelength of each ink. You can get the rate.

In step S803, the estimating unit 1606 determines whether the corresponding area is formed by mixing multiple colors, that is, by mixing a plurality of inks. As a result of this determination, if the corresponding area is formed in multinary colors, the process proceeds to step S806, and if the corresponding area is not formed in multinary colors, the process proceeds to step S804.

In this embodiment, the process advances to step S804 when it is determined in step S801 that the corresponding area contains K ink and in step S803 the corresponding area is not formed of multinary colors. This is only when the area is formed with a single K ink color.

In step S804, the estimation unit 1606 acquires the three directional reflectances of C, Y, and M acquired in step S404 or step S406. Hereinafter, the directional reflectances of C, M, and Y obtained in this step are denoted as ρ' _c1 , ρ' _m1 , and ρ' _y1 .

In step S805, the estimation unit 1606 estimates the reflectance ρ _k of the K ink from the directional reflectances ρ′ _c1 , ρ′ _m1 , and ρ′ _y1 of C, M, and Y, respectively.

In this embodiment, the average value of the directional reflectances ρ′ _c1 , ρ′ _m1 , and ρ′ _y1 of C, M, and Y is used as the reflectance of the K ink. That is, the estimation unit 1606 obtains the reflectance ρ _k of the K ink by calculating ρ _k =(ρ' _c1 +ρ' _m1 +ρ' _y1 )/3.

On the other hand, if the corresponding area is made up of multiple colors including K, the estimation unit 1606 determines the number of inks other than K mixed in the corresponding area in step S806. Specifically, if any one of CMY colors other than K is mixed in the corresponding area (primary color), the process proceeds to step S807, and any two colors of CMY are mixed in the corresponding area. If so (secondary color), the process proceeds to step S808.

As for the mixed color area exceeding the number of sensor colors, since the colors are reduced to the number of sensor colors or less in step S406, the number of ink colors other than K is limited to one or two in step S806. .

In step S807, the estimating unit 1606 acquires two directional reflectances corresponding to the non-mixed inks as the reflectances used in the process of estimating the reflectance _ρk of the K ink. That is, if the corresponding area is a mixed area of K ink and C ink, two reflectances ρ′ _m1 and ρ′ _y1 are acquired.

In step S809, the color estimation unit 1606 estimates the remaining one directional reflectance ρ′ _cm from the two directional reflectances ρ′ _m1 and ρ′ _y1 . Specifically, from the primary color characteristic 1608, the remaining one reflectance is estimated by referring to the table shown in FIG. 7 showing the relationship between the amount of K ink applied and the directional reflectance. In the above example, by referring to the table using ρ′ _m1 as a key, the ejection amount k _ρm corresponding to ρ′ _m1 is obtained. Further, by referring to the table using the ejection amount k _ρm as a key, the directional reflectance ρ′ _cm of the representative wavelength of the C ink corresponding to the ejection amount k _ρm is obtained. Similarly, after obtaining the ejection amount k _ρy using ρ′ _y1 as a key, the directional reflectance ρ′ _cy corresponding to the representative wavelength of the C ink is obtained using the ejection amount k _ρy as a key. Then, using the directional reflectance ρ′ _cm and the directional reflectance ρ′ _cy thus obtained, the reflectance ρ _k of the K ink is calculated as ρ _k = ((ρ′ _cm + ρ′ _cy )/2+ρ ' _m1 +ρ' _y1 )/3.

On the other hand, in step S808, the estimating unit 1606 targets the three-color mixed area including K, and similarly acquires the reflectance corresponding to the ink that is not mixed. That is, if the area is a mixture of K ink, C ink, and M ink, ρ' _y1 is acquired.

At this time, in subsequent step S810, estimation section 1606 estimates ρ′ _{cy and ρ′ my from directional} reflectance ρ′ _y1 and the table shown in FIG. do. After that, the average value of ρ' _y1 , ρ' _cy , and ρ' _my is obtained as the reflectance ρ _k of the K ink.

In both steps S811 and S812, the estimating unit 1606 performs processing to exclude the influence of the K ink reflectance on the directional reflectances ρ′ _c1 , ρ′ _m1 , and ρ′ _y1 of the corresponding regions. I do.

In step S811, the estimation unit 1606 divides each of the directional reflectances ρ′ _c1 , ρ′ _m1 , and ρ′ _y1 of the corresponding area by the reflectance used for calculating the average value in step S809. Excludes the effects of K ink. In the mixed region of K ink and C ink described above _, ρ' c1 , ρ' m1 and ρ' _y1 are divided by (ρ' _cm + ρ' _cy )/2, ρ' _m1 and ρ' _y1 , _respectively .

For example, the directional reflectance _ρ'c corresponding to the representative wavelength of C ink can be obtained by calculating _ρ'c =(2× _ρ'c1 )/( _ρ'cm + _ρ'cy ).

On the other hand, in step S812, the estimating unit 1606 calculates ρ _{′ cy} and ρ′ _my obtained using the impact amount k _ρy as a key, and the directional reflectance ρ′ used as a key for calculating the impact amount k ρy Divide the directional reflectances ρ′ _c1 , ρ′ _m1 , ρ′ _y1 by _y1 . For example, the directional reflectance ρ′ _c corresponding to the representative wavelength of C can be obtained by calculating ρ′ _c =(ρ′ _c1 )/(ρ′ _cy ).

Then, in step S813, the estimation unit 1606 estimates the reflectance of the CMY inks in the corresponding area in the same manner as in step S802 described above. By performing the processing described above, the reflectance of each ink can be calculated based on the RGB values of the user image read by the image acquisition unit 108 .

<Update processing of correction table>
The update processing of the correction table in step S409 will be described with reference to FIG. 9 as an example. FIG. 9A shows the relationship ( Each point in FIG. 9(a)) is plotted for the module or nozzle of interest. Note that the horizontal axis in FIG. 9 represents one of the color signal values CMYK, and the vertical axis represents the reflection corresponding to the color signal value among the estimated reflectances ρ _c , ρ _m , ρ _y , and ρ _k of each ink. rate. That is, each plotted point indicates the relationship between the signal value and the estimated reflectance in each region. A curve 901 in FIG. 9A is a curve representing the spectral reflectance characteristics of the head module or nozzle calculated based on the plotted points.

Curve 901 can be derived, for example, by fitting polynomial coefficients obtained by the method of least squares to the plotted point cloud in FIG. 9(a) in a polynomial function of a predetermined order. Alternatively, as shown in FIG. 9(b), point groups in intervals separated by constant signal values (for example, 16 or 32) are averaged, and as shown in FIG. Get the values for each interval. By performing an interpolation calculation on the representative values for each section, it is also possible to obtain a "curve 902 showing the spectral reflectance characteristics of the head module or nozzle calculated based on the points plotted above." be. At this time, as an interpolation method, for example, piecewise linear interpolation, a spline curve, or the like can be used.

A curve 903 in FIG. 9(d) is a curve showing the spectral reflectance characteristics of the module or head that performs the correction thus obtained. A dashed line 904 is the spectral reflectance characteristic that is the target of the correction processing. Details of the target characteristics will be described later.

At this time _, in order to create a correction table such as that shown in FIG. Next, the color signal value out corresponding to the target reflectance _ρt is obtained from the curve 903 as a correction value. By storing the obtained correction value out and the input color signal value In in association with each other in this manner, a correction table can be created.

At this time, correction values may be calculated for all values from 0 to 255 as the input signal value In, and stored as a table of the nozzle of interest. Alternatively, as shown in FIG. 5, only values corresponding to predetermined gradations (0, 16, 32, . . . , 240, 255) may be calculated and stored as a table.

Although only one spectral reflectance characteristic is drawn in FIG. 9(d), actually, the number of curves equal to the number of modules or nozzles is obtained. By repeating the above processing for all of them, a correction value corresponding to each module or each nozzle can be calculated.

If a correction table is created in advance using a dedicated chart including uniform patterns of each single color of ink prior to printing the user image, the possibility of falling into a local optimum in correction from the user image can be reduced. Alternatively, it is preferable because it is possible to suppress the possibility that a large amount of correction is applied immediately after the start of printing and the color changes for each printing.

<Target characteristics>
In the correction process described above, for example, a spectral reflectance characteristic that makes the color signal value and the reflectance linear can be used as the target characteristic. Alternatively, any module or nozzle may be used as a reference, and the spectral reflectance characteristic of the module or nozzle may be set as the target characteristic.

In the following description, it is assumed that color matching is performed for each head module, and the case where the target characteristics of C ink are determined from the ink characteristics of the head modules 201a, 201b, and 201c will be described as an example.

Curves 1001a-1001c in FIG. 10 show the relationship between the color signal value and the spectral reflectance characteristic ρ of the head modules 201a-201c, respectively. For example, in the estimation process described above, the wavelength λc=700 [nm] is used for C ink. At this time, the spectral reflectance characteristic .rho. can be calculated by using a known interpolation method with respect to the injection amount and the spectral reflectance characteristic .rho.c (kc, 700) for each color signal value.

At this time, in order to determine the target characteristics so that the color signal value and the reflectance are linear, first, the reflectance ρ _min of the head having the highest reflectance with respect to the maximum color signal value is obtained. In the example shown in FIG. 10, let ρ _min be the reflectance corresponding to the color signal value 255 of the curve 1001a corresponding to the head module 201a (1002 in the figure). Then, a straight line 1003 connecting two points at which the reflectance is 1.0 for the color signal value of 0 and the reflectance ρ _min for the maximum color signal value of 255 may be set as the target characteristic.

Alternatively, in the configuration of the head shown in FIG. 2B, the curve 1001b corresponding to the head module 201b located in the center may be used as the target characteristic. Alternatively, it is possible to set the average value of all modules or some modules as the target characteristic. For example, a curve obtained by averaging the curves 1001a, 1001b, and 1001c for each color signal value may be used as the target characteristic.

Also, the target characteristic may be determined based on another value instead of the spectral reflectance characteristic. For example, based on the density characteristic obtained by logarithmically transforming the spectral reflectance characteristic, it is possible to determine the target characteristic so that the input signal value and the density are linear.

Alternatively, the target characteristics can be determined so that the distance D from the recording medium color (paper white) in the CIE Lab space and the color signal value are linear. Note that the distance D from the paper white can be calculated by the following formula. Note that in the following (Equation 11), Lw, La, and Lb are Lab values of recording medium colors, respectively.

[Second embodiment]
Differences from the first embodiment will be described below, and the same as the first embodiment unless otherwise specified. In the first embodiment, an example was described in which redundancies are eliminated by estimating reflectance based on an input image and excluding areas in which inks equal to or greater than the number of sensor outputs are mixed.

By the way, as shown in FIG. 2, when a full-line type recording head covering the width of the recording paper is provided and the recording paper 206 is conveyed in the y direction in the drawing to form an image, the y coordinate is common. If so, the ink characteristics are often the same. That is, since the characteristics of each ink are recorded using the same modules or nozzles in the y direction, they can often be considered to be substantially the same in the y direction regardless of the state of color mixture. Therefore, in the present embodiment, an example of estimating the reflectance from an area other than an area where four colors of ink are mixed will be described.

In FIG. 11, rectangular areas 1101 and 1102 are uniform image areas formed on the print medium. However, the rectangular area 1101 is formed with a single K ink, and the rectangular area 1102 is formed with four CMYK inks.

11 (the region at the upper left corner of the image) is selected as the region of interest in step S403 above, and the processes of steps S403 to S408 are performed for each of the regions 1103 to 1106 (the region at the lower right corner of the image). It shall be done for the area. Assuming that the coordinates of the upper left corner of the image area composed of the rectangular areas 1101 and 1102 are (0, 0), the color conversion unit 1604 converts y as indicated by an arrow 1104 from the coordinates (3, 3) to (0, 0). We refer to each pixel in the direction of the positive axis. Then, when the reference coordinates reach the lower end of the image area, the color conversion unit 1604 moves each color in the positive direction of the y-axis as indicated by an arrow 1105 from the coordinate obtained by incrementing the x-coordinate by one, which is the upper end of the image area. Refer to pixels.

At this time, when the region 1103 is selected as the region of interest, since the region 1103 is formed in a single color of K ink as described above, the reflectances ρ _ck and ρ of the K ink are calculated in step S407 without performing color reduction processing. _mk , ρ _yk can be estimated.

On the other hand, when the area 1107 is selected as the target area, the area 1107 is formed with four colors of CMYK inks as described above, so color reduction processing is executed in step S406.

However, in the color reduction process, as described above, if it is assumed that the areas are substantially the same in the y direction, the single-color K ink reflectance calculated for the area 1103 can be used for the exclusion process. That is, the exclusion process in step S810 may be performed using the reflectance estimated in the area 1103 instead of the reflectance estimated from the input signal value and the primary color characteristics 1608. FIG.

In this way, it is possible to eliminate the influence of any ink from an area in which inks equal to or greater than the number of sensor outputs are mixed using the reflectance estimated from other areas. At this time, while there is a limit to the parallel processing of the reflectance estimation, it is possible to perform the exclusion process with higher accuracy than in the case of excluding the influence from the input signal value.

[Third embodiment]
In the above description, the color space before the color conversion process (step S404) is RGB values. Further, color conversion processing (step S404), creation of a color conversion matrix used in the color conversion processing, color space for color reduction processing (step S406), color space for primary color estimation processing (step S407), and updating of the correction table ( It has been described that both the color space of step S409) and the accompanying creation of the target characteristics are reflectance-based color spaces. That is, it is assumed that the color development of the mixed area is calculated by multiplying the color development of the inks mixed in the mixed area, and the color reduction process excludes the influence of any ink by division.

However, the color space in each process is not limited to the above, and all or part of the processes may be performed based on the density obtained by logarithmically transforming the reflectance. In other words, logarithmic conversion for converting reflectance to density or exponential conversion for converting density to reflectance may be included before and after each of the processes described above. Also, when processing is performed based on density, it can be assumed that the coloring of the mixed area is calculated by summing the coloring of the inks mixed in the area, and exclusion of any ink can be performed by subtraction.

In the above description, it is assumed that common target characteristics are set for the modules and nozzles, which are correction units, in step S409. However, it is also possible to set different target characteristics for each module and nozzle. For example, it is possible to calculate the ink characteristics of each module from the reading result of the first image of each output image, and perform correction using the ink characteristics as target characteristics in subsequent printing.

In the above description, the correction unit 1602 performs correction processing on the input CMYK image. However, similar effects can be obtained by performing correction processing on the threshold matrix used by the HT processing unit 403 .

Also, as described above, the image forming unit 107 and the image acquiring unit 108 may be connected to the I/F unit 109 . In this case, an image processing apparatus having a CPU 100, a RAM 101, a ROM 102, an operation unit 103, a display unit 104, an external storage device 105, an image processing unit 106, and an I/F unit 109 transmits an image to be printed through the I/F unit 109. and supplies it to the image forming unit 107 . Also, the image processing apparatus acquires the image read from the recording medium by the image acquisition unit 108 via the I/F unit 109 . Computer devices such as PCs (personal computers), smart phones, tablet terminals, and the like are applicable to such image processing devices.

The numerical values, processing timing, processing order, processing subject, data (information) transmission destination/transmission source/storage location, etc. used in each of the above embodiments are given as an example for specific explanation. , is not intended to be limiting to such an example.

Also, some or all of the embodiments described above may be used in combination as appropriate. Moreover, you may selectively use a part or all of each embodiment demonstrated above.

(Other embodiments)
The present invention supplies a program that implements one or more functions of the above-described embodiments to a system or apparatus via a network or a storage medium, and one or more processors in the computer of the system or apparatus reads and executes the program. It can also be realized by processing to It can also be implemented by a circuit (for example, ASIC) that implements one or more functions.

The invention is not limited to the embodiments described above, and various modifications and variations are possible without departing from the spirit and scope of the invention. Accordingly, the claims are appended to make public the scope of the invention.

100: CPU 101: RAM 102: ROM 103: Operation Unit 104: Display Unit 105: External Storage Device 106: Image Processing Unit 107: Image Forming Unit 108: Image Acquisition Unit 109: I/F Unit 110: Bus

Claims (11)

Among the areas in the read image obtained by using a sensor to read an image formed using recording materials of a plurality of colors, for a mixed area in which the number of colors of recording materials that exceed the number of colors read by the sensor is mixed, a color reduction means for estimating a result of excluding the influence of one of the recording materials of the plurality of colors;
estimating means for estimating characteristics of the recording material from the read image;
correction means for performing correction processing for reproducing target characteristics on a recording medium based on the characteristics of each recording material estimated by the estimation means for each area in the read image,
The image forming apparatus, wherein the estimating means estimates characteristics of recording materials other than one recording material among the recording materials of the plurality of colors based on the result of the estimation by the color reduction means for the mixed area. . the sensor is an RGB sensor;
The color reduction means obtains the estimation result for each of the plurality of color recording materials based on the priority order of each of the plurality of color recording materials for a mixed area in which more than three recording materials are mixed. 2. The image forming apparatus according to claim 1, wherein the estimation result is acquired when three recording materials are mixed. 3. The image forming apparatus according to claim 1, wherein the color reduction unit preferentially estimates a result of excluding the influence of black among the recording materials of the plurality of colors. 3. The image according to claim 1, wherein the color reduction unit preferentially estimates a result excluding the influence of a recording material that is stable against aging among the recording materials of the plurality of colors. forming device. The color reduction means determines the recording material to be excluded based on the amount of impact or the signal value of each recording material in the mixed area, and estimates the result of excluding the influence of the determined recording material. Item 3. The image forming apparatus according to Item 1 or 2. The color reduction means estimates a characteristic of the recording material to be excluded in the mixed area based on the signal value of the recording material to be excluded in the mixed area, and divides or subtracts the estimated characteristic to obtain the excluded recording material. 6. The image forming apparatus according to any one of claims 1 to 5, wherein a result excluding the influence of the target recording material is estimated. The characteristic of the recording material to be excluded is obtained by referring to a LUT (lookup table) storing values read by the sensor from a formed image recorded in a single color of the recording material to be excluded in advance. 7. The image forming apparatus according to claim 6. an image forming unit that forms the image using the recording materials of the plurality of colors, and has a plurality of recording units;
The characteristics of the recording material to be excluded are formed in the same recording unit, and the characteristics of the recording material to be excluded are estimated in an area where recording materials having a number of colors less than the number read by the sensor are mixed are used. 7. The image forming apparatus according to claim 6. an image forming unit that forms the image on a recording medium using the recording materials of the plurality of colors;
the sensor that reads the image formed on the recording medium by the image forming unit;
An image forming system comprising: the image forming apparatus according to claim 1 . An image forming method performed by an image forming apparatus,
The color reduction means of the image forming apparatus uses a sensor to read an image formed using recording materials of a plurality of colors, and the recording material exceeds the number of colors read by the sensor in each area of the read image obtained by using the sensor. a color reduction step of estimating a result of excluding the influence of one recording material among the plurality of recording materials for a mixed area in which
an estimating step in which the estimating means of the image forming apparatus estimates the characteristics of the recording material from the read image;
Correction in which the correction means of the image forming apparatus performs correction processing for reproducing target characteristics on a recording medium based on the characteristics of each recording material estimated in the estimation step for each area in the read image. with a process and
The image forming method, wherein in the estimation step, characteristics of recording materials other than one of the recording materials of the plurality of colors are estimated based on a result of the estimation in the color reduction process for the mixed area. . A computer program for causing a computer to function as each means of the image forming apparatus according to any one of claims 1 to 8.

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