Image formation device, and gradation correction method

Abstract

To enable correcting a gradation, while suppressing consumption of coloring materials.SOLUTION: An image formation device, which updates a gradation correction table on the basis of a gradation characteristic of a print image to correct the gradation characteristic of the image data using the gradation correction table, comprises: a pseudo patch extraction unit that extracts an area composed of a fixed pixel value as a pseudo patch from the image data; a printing unit that prints an image on a medium by use of a coloring material on the basis of the image data having the gradation characteristic corrected; a density reading unit that reads density from the printing image printed on the medium, and generates a read image indicative of a density value for each unit corresponding to a single pixel of the image data; and a gradation characteristic acquisition unit that acquires a density value of a part corresponding to the pseudo patch from the read image, and acquires the gradation characteristic of the printing image on the basis of the density value and the pixel value of the pseudo patch.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to an image forming apparatus and a gradation correction method.

Background Art

[0002] In an image forming apparatus such as a printer that forms (i.e., prints) an image on a medium, gradation correction is performed on the gradation characteristics of the image data that is the source of the printed image so that the gradation characteristics of the printed image match the target gradation characteristics. For gradation correction, a gradation correction table in which corrected gradation values are determined for each gradation value is used.

[0003] The gradation characteristics of a printed image vary due to environmental changes, changes over time, and the like. Therefore, in an image forming apparatus, the gradation characteristics of a printed image are periodically acquired, and the gradation correction table is updated according to the error between the acquired gradation characteristics and the target gradation characteristics. In a conventional image forming apparatus, a gradation patch is printed around the printed image, and the gradation characteristics of the printed image are acquired by reading the gradation patch (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, a conventional image forming apparatus has a problem in that an extra amount of coloring material such as ink or toner is consumed because a gradation patch is printed separately from the printed image.

[0006] The present invention has been made in consideration of the above points, and intends to propose an image forming apparatus and a gradation correction method capable of performing gradation correction while suppressing the consumption of coloring material.

Means for Solving the Problem

[0007] The image forming apparatus of the present invention is an image forming apparatus that updates a tone correction table for correcting the tone characteristics of image data based on the tone characteristics of a printed image, and corrects the tone characteristics of the image data using the tone correction table. The image forming apparatus includes a pseudo-patch extraction unit that extracts a region composed of a certain pixel value from the image data as a pseudo-patch, a printing unit that prints an image on a medium using a coloring material based on the image data with corrected tone characteristics, a density reading unit that reads the density from the printed image printed on the medium and generates a reading image showing the density value for each unit corresponding to one pixel of the image data, and a tone characteristic acquisition unit that acquires the density value of the portion corresponding to the pseudo-patch from the reading image and acquires the tone characteristics of the printed image based on the density value and the pixel value of the pseudo-patch.

[0008] The tone correction method of the present invention is a tone correction method that updates a tone correction table for correcting the tone characteristics of image data based on the tone characteristics of a printed image, and corrects the tone characteristics of the image data using the tone correction table. The tone correction method includes a step of extracting a region composed of a certain pixel value from the image data as a pseudo-patch, a step of printing an image on a medium using a coloring material based on the image data with corrected tone characteristics, a step of reading the density from the printed image printed on the medium and generating a reading image showing the density value for each unit corresponding to one pixel of the image data, and a step of acquiring the density value of the portion corresponding to the pseudo-patch from the reading image and acquiring the tone characteristics of the printed image based on the density value and the pixel value of the pseudo-patch.

[0009] In this way, by extracting a region composed of a certain pixel value from the image data as a pseudo-patch and reading the density value of the portion corresponding to the pseudo-patch from the printed image, it is not necessary to print a tone patch separately from the printed image, and the tone characteristics of the printed image can be acquired without consuming an extra amount of coloring materials such as ink or toner.

Advantages of the Invention

[0010] According to the present invention, it is possible to realize an image forming apparatus and a gradation correction method capable of performing gradation correction while suppressing the consumption of coloring materials.

Brief Description of the Drawings

[0011]

Figure 1

Figure 2

Figure 3

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Figure 7

Figure 8

Embodiments for Carrying Out the Invention

[0012] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0013] [1. Configuration of Printer] FIG. 1 is a diagram showing the hardware configuration of a printer 101 which is an example of an image forming apparatus according to an embodiment of the present invention. The printer 101 is an electrophotographic color printer, and as an example of the hardware configuration, it has a network I / F (interface) 103, an operation panel 104, a density sensor 105, a printer engine 106, a paper feed tray 107, a CPU 108, a RAM 109, and a ROM 110. Each part of the printer 101 is interconnected via a printer bus (not shown).

[0014] The network I / F 103 is an interface such as a network or USB, and receives the image data sent from the PC 102 as an external device. The operation panel 104 is composed of a display panel for displaying the state and operation instructions of the printer 101 and operation buttons for operating the printer 101.

[0015] The printer engine 106 has, for example, four image forming units that form an image with coloring materials (toners) of cyan, magenta, yellow, and black, and prints an image based on the image data received from the PC 101 on the print medium conveyed along the medium conveyance path. The density sensor 105 is provided, for example, on the downstream side of the printer engine 106 on the medium conveyance path, and measures the density of the image (i.e., the printed image) printed on the print medium by the printer engine 106.

[0016] The paper feed tray 107 accumulates print media such as printing paper, and feeds (papers) the accumulated print media one by one onto the medium conveyance path. The CPU 108 is an arithmetic unit, and controls the operation of the entire printer 101 by reading and executing various programs stored in the ROM 110 into the RAM 109. Specifically, the CPU 108 generates data in a printable format by the printer 101 based on the image data received from the PC 102, and sends this to the printer engine 106. The hardware configuration of the printer 101 is as described above.

[0017] Next, the functional configuration of the printer 101 will be described using the functional block diagram shown in FIG. 2. As an example of the functional configuration, the printer 101 has a reception unit 201, an pseudo patch extraction unit 202, a gradation correction unit 203, a gradation storage unit 204, a binarization unit 205, a printing unit 206, a density reading unit 207, an alignment unit 208, and a density correction unit 209.

[0018] The receiving unit 201 receives image data from an external device such as the PC 102 and sends it to the pseudo-patch extraction unit 202 and the gradation correction unit 203. The pseudo-patch extraction unit 202 extracts, as pseudo-patches, regions of a predetermined size composed of constant pixel values of a single color (i.e., one of cyan, magenta, yellow, and black) from the image data sent from the receiving unit 201, and sends the extracted pseudo-patches to the density correction unit 209. Note that a plurality of pseudo-patches may be extracted from the image data.

[0019] The gradation correction unit 203 acquires gradation correction tables prepared for each of the colors cyan, magenta, yellow, and black from the gradation storage unit 204, and generates image data for each of the colors cyan, magenta, yellow, and black based on the image data sent from the receiving unit 201. Further, the gradation correction unit 203 performs gradation correction on the image data for each color by performing 1D Lut conversion using the gradation correction table for each color. That is, the gradation correction unit 203 corrects each gradation value (i.e., the pixel value for each pixel of the image data for each color) of the image data for each color using the gradation correction table for each color in which the gradation value after correction is determined for each gradation value. Then, the gradation correction unit 203 sends the image data for each color after gradation correction to the binarization unit 205.

[0020] The gradation storage unit 204 stores the gradation correction table and the gradation characteristic data on which the gradation correction table is based. The binarization unit 205 performs halftone processing on each of the image data for each color sent from the gradation correction unit 203 to generate binarized images for each color, and sends these to the printing unit 206 and the alignment unit 208.

[0021] The printing unit 206 prints by overlapping toners of each color on a printing medium by the printer engine 106 based on the binarized images for each color sent from the binarization unit 205.

[0022] The density reading unit 207 obtains density values by reading the printed image printed on the print medium by the printing unit 206 with the density sensor 105. The density sensor 105 reads the density of each color of cyan, magenta, yellow, and black for each predetermined unit (for example, dots) constituting the printed image and outputs it as a density value. Further, the density reading unit 207 generates a reading image indicating the density value for each unit corresponding to one pixel of the image data for each color based on the reading result of the density sensor 105. That is, each color reading image is an image indicating the density at which each pixel constituting the image data is printed when the image data is printed. Then, the density reading unit 207 sends the generated reading images of each color to the alignment unit 208.

[0023] The alignment unit 208 performs alignment of the reading images of each color sent from the density reading unit 207 with respect to the binarized images of each color sent from the binarization unit 205. Specifically, the alignment unit 208 performs a process of aligning the coordinates of each pixel of the reading image with the coordinates of each pixel of the binarized image for each color. Then, the alignment unit 208 sends the aligned reading images of each color to the density correction unit 209.

[0024] The density correction unit 209 selects the reading image of the color corresponding to the pixel value of the pseudo patch sent from the pseudo patch extraction unit 202 from among the reading images of each color sent from the alignment unit 208, and obtains the density value of the portion corresponding to the pseudo patch from the selected reading image. As a result, the density correction unit 209 has obtained the density value of the portion corresponding to the pseudo patch composed of a constant pixel value of a single color (that is, the density value when the pseudo patch is printed) from the printed image printed on the print medium. In this way, the density correction unit 209 obtains the density value for each pseudo patch sent from the pseudo patch extraction unit 202.

[0025] Furthermore, the density correction unit 209 obtains the tone characteristics of each color of the current printer 101 (i.e., the tone characteristics of the printed image) by estimating the pixel values and density values of each pseudo patch and the tone characteristic data of each color stored in the tone memory unit 204. Then, the density correction unit 209 newly generates a tone characteristic table for each color using the obtained tone characteristics of each color, and updates the tone characteristic table of each color stored in the tone memory unit 204 with the newly generated tone characteristic table of each color. The functional configuration of the printer 101 is as described above.

[0026] [2. Operation of Printer] Next, the operation of the printer 101 will be described. Here, as the operation of the printer 101, the operation when printing an image and performing tone correction will be described using the flowchart shown in FIG. 3.

[0027] When the user selects the printer 101 on the PC 102 and performs an operation to execute printing of image data, the image data is transmitted from the PC 102 to the printer 101. At this time, in step SP301, the printer 101 receives the image data transmitted from the PC 102 by the receiving unit 201. Here, for simplicity of explanation, it is assumed that the image data transmitted from the PC 102 is the image data for one page.

[0028] In the subsequent step SP302, the printer 101 searches the received image data by the pseudo patch extraction unit 202 for a region of a predetermined size composed of a constant pixel value of a single color (i.e., one of cyan, magenta, yellow, and black). Here, the predetermined size in this case is the size of the dither matrix used in the halftone process performed by the binarization unit 205. That is, the pseudo patch extraction unit 202 searches the received image data for a region of the same size as the dither matrix used in the halftone process, which is composed of a constant pixel value of a single color.

[0029] Then, the pseudo-patch extraction unit 202 extracts the regions discovered by the search as pseudo-patches, and stores the pixel values and coordinates of the extracted pseudo-patches (i.e., the positions on the received image data). As described above, multiple pseudo-patches may be extracted. Details of the processing in this step SP302 (i.e., the pseudo-patch extraction process) will be described later.

[0030] In the subsequent step SP303, the printer 101 generates image data for each color (cyan, magenta, yellow, black) based on the received image data by the tone correction unit 203, and performs 1DLut conversion using the tone correction table for each color on the generated image data for each color, thereby performing tone correction on the image data for each color.

[0031] In the subsequent step SP304, the printer 101 generates a binarized image for each color by performing halftone processing on the image data for each color after tone correction by the binarization unit 205.

[0032] In the subsequent step SP305, the printer 101 prints by overlapping toner of each color on the printing medium based on the binarized image of each color by the printing unit 206.

[0033] In the subsequent step SP306, the printer 101 reads the density of the printed image on the printing medium with the density sensor 105 by the density reading unit 207, and generates a read image for each color based on the read result.

[0034] In the subsequent step SP307, the printer 101 aligns the positions of the read images for each color with the positions of the binarized images for each color (i.e., the positions on the received image data) by the alignment unit 208, and obtains the density values of the portions corresponding to each pseudo-patch from the aligned read images for each color (i.e., the density values when the pseudo-patch is printed). Details of the processing in this step SP307 (i.e., the alignment process) will be described later.

[0035] In the subsequent step SP308, the printer 101 estimates the gradation characteristics of each color of the current printer 101 by using the pixel values and density values of each pseudo patch and the gradation characteristic data of each color stored in the gradation memory unit 204 by the density correction unit 209. Details of the processing of this step SP308 (i.e., gradation characteristic estimation processing) will be described later.

[0036] In the subsequent step SP309, the printer 101 newly generates a gradation characteristic table for each color by using the gradation characteristics of each color estimated in step SP308, and updates the gradation characteristic table of each color stored in the gradation memory unit 204 with the newly generated gradation characteristic table of each color. The outline of the operation of the printer 101 is as described above. Note that the processing of step SP302 and the processing of steps SP306 to SP309, that is, the processing of extracting pseudo patches from the printed image and the processing of reading the printed image and updating the gradation characteristic table, have a high processing load, so they may not be performed every time printing is done, but may be performed every time a predetermined number of sheets are printed, for example, every 100 sheets printed.

[0037] Next, details of the processing of step SP302 described above, that is, the pseudo patch extraction processing, will be described using the flowchart shown in FIG. 4. In the pseudo patch extraction processing, first, in step SP401, the pseudo patch extraction unit 202 detects edges in the received image data. Note that the edge in this case is a location where the color or shading changes in the image data, that is, a location where the pixel value changes in the image data.

[0038] In the subsequent step SP402, the pseudo patch extraction unit 202 assigns a search exclusion flag to white pixels in the image data. Since white pixels in the image data are not subject to gradation correction, they are excluded from the search target for pseudo patches.

[0039] In the subsequent step SP403, the pseudo-patch extraction unit 202 sets one of the pixels in the image data that does not have a search exclusion flag as the target pixel for search. In the subsequent step SP404, the pseudo-patch extraction unit 202 searches for edges within a region of a predetermined size (the size of the dither matrix) starting from the target pixel for search.

[0040] In the subsequent step SP405, the pseudo-patch extraction unit 202 determines whether an edge exists as a result of the search in step SP403. Here, if it is determined that no edge exists, this means that the region of a predetermined size starting from the current target pixel for search is composed of a single pixel value. In this case, the pseudo-patch extraction unit 202 obtains an affirmative result in step SP405 and proceeds to step SP406.

[0041] In step SP406, the pseudo-patch extraction unit 202 extracts the region of a predetermined size starting from the current target pixel for search as a pseudo-patch, and stores the pixel values and coordinates of the extracted pseudo-patch. Note that the coordinates of the pseudo-patch in this case are, for example, the coordinates of the pixel located at the center of the pseudo-patch (i.e., the target pixel for search when the pseudo-patch was extracted). In the subsequent step SP407, a search exclusion flag is assigned to the pixels within the extracted pseudo-patch, and the process proceeds to the subsequent step SP408. At this time, a search exclusion flag may also be assigned to the pixels outside the pseudo-patch that have the same pixel value as the pixel values of the extracted pseudo-patch.

[0042] On the other hand, if it is determined in step SP405 described above that an edge exists, this means that the region of a predetermined size starting from the current target pixel for search is not composed of a single pixel value. In this case, the pseudo-patch extraction unit 202 obtains a negative result in step SP405, skips steps SP406 and SP407 described above (i.e., does not extract a pseudo-patch), and proceeds to step SP408.

[0043] In step SP408, the pseudo-patch extraction unit 202 determines whether the search has been completed for all pixels in the image data (that is, whether a search exclusion flag is assigned to all pixels in the image data). Here, if there are still pixels for which the search has not been completed, the pseudo-patch extraction unit 202 obtains a negative result in this step SP408, returns to step SP403, and continues the pseudo-patch extraction process.

[0044] On the other hand, in step SP408 described above, if the search has been completed for all pixels in the image data, the pseudo-patch extraction unit 202 obtains an affirmative result in this step SP408 and ends the pseudo-patch extraction process. The details of the pseudo-patch extraction process are as described above. Note that the pixel values and coordinates of the pseudo-patches obtained in the pseudo-patch extraction process are passed from the pseudo-patch extraction unit 202 to the alignment unit 208 and the density correction unit 209.

[0045] Next, the details of the process of step SP307 described above, that is, the alignment process, will be described using the flowchart shown in FIG. 5. In the alignment process, first, in step SP501, the alignment unit 208 obtains histograms for the pixel values in the vertical and horizontal directions for each of the cyan, magenta, yellow, and black colors for both the binarized image and the read image. Then, for each color, the alignment unit 208 roughly aligns the position of the read image for each color with the position of the binarized image for each color by moving the position of the read image so that the difference in the shapes of the histograms of the binarized image and the read image is minimized.

[0046] In the subsequent step SP502, the alignment unit 208 designates one of the pseudo-patches extracted from the image data in the pseudo-patch extraction process as the search target. In the subsequent step SP503, the alignment unit 208 extracts a portion corresponding to the pseudo-patch (referred to as the pseudo-patch portion) from the binarized image of the color corresponding to the pixel values of the search target pseudo-patch using the coordinates of the pseudo-patch.

[0047] In the subsequent step SP504, the alignment unit 208 searches for the corresponding position on the read image for the pseudo-patch portion extracted from the binarized image. Note that this search is performed, for example, by known template matching or the like, scanning the read image to obtain the coordinates with the highest similarity to the pseudo-patch portion extracted from the binarized image. Note that the coordinates obtained at this time are, for example, the coordinates of the pixel located at the center of the pseudo-patch.

[0048] In the subsequent step SP505, the alignment unit 208 obtains the density value of the coordinates (that is, the coordinates of the pixel located at the center of the pseudo-patch) obtained in step SP504 on the read image as the density value of the pseudo-patch to be searched. Note that the average of the density values of all the pixels included in the pseudo-patch to be searched on the read image may be obtained as the density value of the pseudo-patch to be searched.

[0049] In the subsequent step SP506, the alignment unit 208 determines whether the search has been completed for all the pseudo-patches extracted in the pseudo-patch extraction process (that is, whether the density values have been obtained for all the pseudo-patches). Here, if there is a pseudo-patch for which the search has not yet been completed, the alignment unit 208 obtains a negative result in this step SP506 and returns to step SP502 to continue the pseudo-patch extraction process.

[0050] On the other hand, in step SP506 described above, if the search has been completed for all the pseudo-patches, the alignment unit 208 obtains an affirmative result in this step SP506 and ends the alignment process. The details of the alignment process are as described above. Note that the density value of the pseudo-patch obtained in this alignment process is passed from the alignment unit 208 to the density correction unit 209.

[0051] Next, the details of the process of step SP308 described above, that is, the gradation characteristic estimation process, will be described using the flowchart shown in FIG. 6. Note that this gradation characteristic estimation process is performed for each color of cyan, magenta, yellow, and black. Here, for the sake of simplicity of explanation, the gradation characteristic estimation process for one color (for example, cyan) will be described.

[0052] In the gradation characteristic estimation process, first, in step SP601, the density correction unit 209 reads out the cyan gradation characteristic data from the gradation storage unit 204. Here, the gradation characteristic data is data indicating the relationship between the pixel value of the image data and the density value of the printed image (that is, the gradation characteristic of the printer 101), as shown in FIG. 7. For example, it shows each pixel value from 0 to 255 and each density value when printed based on each pixel value.

[0053] The density correction unit 209 selects one of the cyan pseudo patches extracted from the image data in the pseudo patch extraction process, and uses two pixel values (that is, a pixel value that is smaller than the pixel value of the pseudo patch and is separated from the pixel value, and a pixel value that is larger than the pixel value of the pseudo patch and is separated from the pixel value) that are separated before and after from the pixel value of the pseudo patch as control points, and obtains the density values of the two control points from the cyan gradation characteristic data. At this time, as shown in FIG. 7, the density correction unit 209 may be configured such that pixel values extracted at regular intervals from each pixel value from 0 to 255 are set as control points, and among the plurality of set control points, two control points that are separated before and after the pixel value of the pseudo patch are used. Further, without being limited to this, two pixel values that are separated by a predetermined interval before and after from the pixel value of the pseudo patch may be used as control points with the pixel value of the pseudo patch as the center.

[0054] In the subsequent step SP602, the density correction unit 209 corrects the density value for the pixel value on the gradation characteristic data using the density value for the pixel value of the pseudo patch selected in step SP601. Further, using the density value of the selected pseudo patch and the density values of the two control points, the density value for the pixel value located between the pixel value of the pseudo patch and the two control points spaced apart before and after from the pixel value is interpolated by known spline interpolation or the like, thereby correcting the gradation characteristic data as shown in FIG. 8.

[0055] In this way, the density correction unit 209 corrects the gradation characteristic data using the pixel value and density value of the cyan pseudo patch. Incidentally, when there are a plurality of cyan pseudo patches, the density correction unit 209 selects the pseudo patches one by one and corrects the gradation characteristic data using the pixel value and density value of the selected pseudo patch. By doing so, the cyan gradation characteristic data is updated to the one estimated for the cyan gradation characteristic of the current printer 101. In this way, the density correction unit 209 estimates the current cyan gradation characteristic data by correcting the cyan gradation characteristic data.

[0056] Similarly, the density correction unit 209 also estimates the gradation characteristics of other colors using the pixel values and density values of the pseudo patches of other colors. The details of the gradation characteristic estimation process are as described above.

[0057] As described in step SP309 of FIG. 3, the density correction unit 209 newly generates a tone correction table for each color using the tone characteristic data of each color updated by the above-described tone characteristic estimation process, and updates the tone correction table of each color stored in the tone storage unit 204 with the newly generated tone correction table of each color. Here, as a method for generating a tone correction table using tone characteristic data, a known method may be used, and a detailed description thereof will be omitted. Briefly described, the density correction unit 209 generates a tone correction table based on the difference (i.e., error) between the tone characteristics of the printer 101 indicated by the tone characteristic data and the target tone characteristics in which the density value changes linearly with respect to the change in the pixel value.

[0058] [3. Summary and Effects] As described above, in the present embodiment, a printer 101, which is an example of an image forming apparatus that updates a tone correction table for correcting the tone characteristics of image data that is the source of a printed image based on the tone characteristics of the printed image and corrects the tone characteristics of the image data using the tone correction table, is provided with a pseudo-patch extraction unit 202 that extracts a region composed of a certain pixel value from the image data as a pseudo-patch, a printing unit 206 that prints an image on a printing medium, which is an example of a medium, using a coloring material based on the image data with corrected tone characteristics, a density reading unit 207 that reads the density in dot units from the printed image printed on the printing medium by the printing unit 206 and generates a read image indicating the density value for each unit corresponding to one pixel of the image data, and a density correction unit 209, which is an example of a tone characteristic acquisition unit, that acquires the density value of a portion corresponding to the pseudo-patch from the read image and acquires (estimates) the tone characteristics of the printed image based on the density value and the pixel value of the pseudo-patch.

[0059] As described above, in the printer 101 of the present embodiment, by extracting a region composed of certain pixel values from the image data as a pseudo patch and reading the density of the portion corresponding to the pseudo patch from the printed image, it is not necessary to print a tone patch separately from the printed image, and without consuming extra coloring materials such as ink or toner, and even when there is no space for printing a tone patch separately from the printed image on the print medium, the tone characteristics of the printed image can be obtained. Thus, according to the printer 101 of the present embodiment, tone correction can be performed while suppressing the consumption of coloring materials.

[0060] Also, in the printer 101, the pseudo patch extraction unit 202 extracts, from the image data, a region composed of certain pixel values and having the same size as the size of the dither matrix as a pseudo patch. By doing so, in the printer 101, for a region in the image data composed of certain pixel values and having a size equal to or larger than the size of the dither matrix (minimum size), it can be printed with an appropriate density.

[0061] Also, in the printer 101, tone characteristic data indicating the tone characteristics of the printed image is stored in the tone storage unit 204, and the tone characteristic data stored in the tone storage unit 204 is corrected using the pixel values and density values of the extracted pseudo patch. At this time, using the density value for the pixel value of the extracted pseudo patch and the density values for two pixel values (control points) before and after the pixel value of the pseudo patch obtained from the tone characteristic data, the density value for a pixel value located between the pixel value of the pseudo patch and the two pixel values before and after the pixel value of the pseudo patch is interpolated by spline interpolation or the like to correct the tone characteristic data.

[0062] By doing so, in the printer 101, not only the pixel values of the pseudo patch but also the pixel values before and after the pixel values can be printed with appropriate densities.

[0063] [4. Other Embodiments] [4-1. Other Embodiment 1] In the above-described embodiments, the process of extracting pseudo patches from a printed image and updating the gradation characteristic table is performed in units of image data. However, the present invention is not limited to this, and it may be performed in units of print jobs. Here, when one print job includes image data for a plurality of pages, pseudo patches may be extracted from each of the plurality of printed images printed based on each of the image data for the plurality of pages, and the gradation characteristic table may be updated.

[0064] Also, in the above-described embodiments, the process of extracting pseudo patches from a printed image and updating the gradation characteristic table is performed every time a predetermined number of sheets are printed because the processing load is high. However, the present invention is not limited to this, and the process may be performed, for example, every time a predetermined number of print jobs are printed.

[0065] On the other hand, if the number of pseudo patches extracted from a printed image is too small, the estimation of the gradation characteristics of the printed image will be limited to around specific pixel values. Therefore, for example, the pseudo patch extraction unit 202 may count the number of pseudo patches extracted from the printed image for each color, and continue to extract pseudo patches from the printed image every time printing is performed based on the image data until the number of pseudo patches for each color reaches a predetermined number.

[0066] In addition, as described above, when extracting pseudo patches from a printed image in units of print jobs, the pseudo patch extraction unit 202 may continue to extract pseudo patches from the printed image every time printing is performed based on the print job until the number of pseudo patches for each color reaches a predetermined number.

[0067] [4-2. Other Embodiment 2] Furthermore, in the above-described embodiment, the pseudo-patch extraction unit 202 extracts, from the received image data, a region of a predetermined size composed of a single-color constant pixel value as a pseudo-patch. However, it is not limited to this. For example, a region of a predetermined size composed of a mixed-color constant pixel value, such as a cyan pixel value of 125 and a magenta pixel value of 30, may be extracted as a pseudo-patch. That is, a region of a predetermined size composed of a single-color or mixed-color constant pixel value may be extracted as a pseudo-patch.

[0068] When extracting a region of a predetermined size composed of a mixed-color constant pixel value as a pseudo-patch, the pseudo-patch extraction unit 202 may further extract a pseudo-patch for each color from the extracted mixed-color pseudo-patch. And for the operations after extracting the pseudo-patches for each color, the same operations as those in the above-described embodiment may be performed.

[0069] In this way, by extracting a region of a predetermined size composed of a single-color or mixed-color constant pixel value as a pseudo-patch, the number of pseudo-patches that can be extracted from the printed image increases as compared with the case of extracting a region of a predetermined size composed of a single-color constant pixel value as a pseudo-patch, so that the tone characteristics of the printed image can be estimated more appropriately.

[0070] [4-3. Other Embodiment 3] Furthermore, in the above-described embodiment, the pseudo-patch extraction unit 202 extracts, from the image data, a region of the same size as the dither matrix size composed of a constant pixel value as a pseudo-patch. That is, the size of the pseudo-patch is set to the size of the dither matrix. However, it is not limited to this. The size of the pseudo-patch may be a size different from the dither matrix, for example, a size larger than the dither matrix.

[0071] [4-4. Other Embodiment 4] Furthermore, in the above-described embodiment, the present invention is applied to an electrophotographic printer 101 which is an example of an image forming apparatus. However, the present invention is not limited thereto, and for example, the present invention can also be applied to a multifunction peripheral having the same configuration as the printer 101, an inkjet printer, or the like. Also, in the printer 101, the density reading unit 207 reads the density of the printed image by the density sensor 105 provided in the conveyance path. However, the present invention is not limited thereto. For example, a scanner connected to the printer 101 may scan the printed image, and the density reading unit 207 may read the density of the printed image from the scanned printed image. Similarly, in a multifunction peripheral equipped with a scanner, the density reading unit 207 provided in the multifunction peripheral may read the density of the printed image from the scanned printed image. When the printed image is scanned by the scanner in this way, the density sensor 105 can be omitted.

[0072] [4-5. Other Embodiment 5] Furthermore, the present invention is not limited to the above-described embodiments. That is, the scope of application of the present invention extends to embodiments in which some or all of the above-described embodiments are arbitrarily combined, and embodiments in which some are different.

Industrial Applicability

[0073] The present invention can be widely used in an image forming apparatus having a gradation correction function.

Explanation of Reference Numerals

[0074] 101... Printer, 102... PC, 103... Network I / F, 105... Density sensor, 106... Printer engine, 108... CPU, 201... Reception unit, 202... Virtual patch extraction unit 202... Gradation correction unit, 204... Gradation storage unit, 205... Binarization unit, 206... Printing unit, 207... Density reading unit, 208... Alignment unit, 209... Density correction unit.

Claims

1. An image forming apparatus that updates a tone correction table for correcting the tone characteristics of image data based on the tone characteristics of a printed image, and corrects the tone characteristics of the image data using the tone correction table, a pseudo patch extraction unit that extracts, as a pseudo patch, a region composed of a certain pixel value from the image data, a printing unit that prints an image on a medium using a coloring material based on the image data with corrected tone characteristics, a density reading unit that reads the density from the printed image printed on the medium and generates a read image showing the density value for each unit corresponding to one pixel of the image data, a tone characteristic acquisition unit that acquires the density value of a location corresponding to the pseudo patch from the read image, and acquires the tone characteristics of the printed image based on the density value and the pixel value of the pseudo patch characterized by comprising an image forming apparatus.

2. comprising a binarization unit that generates a binarized image by performing halftone processing on the image data with corrected tone characteristics, wherein the printing unit prints an image on the medium using the coloring material based on the binarized image, and wherein the pseudo patch extraction unit extracts, as the pseudo patch, a region composed of a certain pixel value and having the same size as the size of the dither matrix used in the halftone processing from the image data The image forming apparatus according to claim 1, characterized in that.

3. wherein the pseudo patch extraction unit extracts, as the pseudo patch, a region composed of a certain pixel value of a single color from the image data The image forming apparatus according to claim 1 or 2, characterized in that.

4. wherein the pseudo patch extraction unit extracts, as the pseudo patch, a region composed of a certain pixel value of a single color or a mixed color from the image data The image forming apparatus according to claim 1 or 2, characterized in that.

5. comprising a tone storage unit that stores tone characteristic data indicating the tone characteristics of the printed image, wherein the tone characteristic acquisition unit acquires the tone characteristics of the printed image by correcting the tone characteristic data stored in the tone storage unit using the density value of the location corresponding to the pseudo patch acquired from the read image and the pixel value of the pseudo patch The image forming apparatus according to claim 1 or 2, characterized in that.

6. wherein the pseudo patch extraction unit extracts the pseudo patch from the image data each time the printing unit prints based on the image data until the number of pseudo patches extracted from the image data reaches a predetermined number The image forming apparatus according to claim 1 or 2, characterized in that...

7. A gradation correction method for updating a gradation correction table for correcting the gradation characteristics of image data based on the gradation characteristics of a printed image, and correcting the gradation characteristics of the image data using the gradation correction table. Extracting, as a pseudo patch, a region composed of a certain pixel value from the image data. Printing an image on a medium using a coloring material based on the image data with corrected gradation characteristics. Reading the density from the printed image printed on the medium, and generating a read image showing the density value for each unit corresponding to one pixel of the image data. Obtaining the density value of the portion corresponding to the pseudo patch from the read image, and obtaining the gradation characteristics of the printed image based on the density value and the pixel value of the pseudo patch. Comprising A gradation correction method, characterized in that...

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