JP2010011361A - Image processing system and method thereof, image processing apparatus, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processing system and method thereof, image processing apparatus, and program, in which image quality in printing under a plurality of image processing conditions can be easily evaluated. <P>SOLUTION: The image processing system includes a printing means for performing printing on a recording medium, measures a plurality of evaluation images from the recording medium, on which printing has been performed by the printing means, on the basis of the plurality of evaluation images processed under a plurality of image processing conditions, evaluates each of the plurality of image processing conditions on the basis of a result of the measurement, presents to a user evaluation results of the plurality of image processing conditions obtained by the evaluation, and processes an image to be printed on the basis of an image processing condition instructed by the user from among the presented evaluation results of the plurality of image processing conditions. On the basis of the processed image, the printing performs printing on the recording medium. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

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

Conventionally, a color printer is often used for printing a color document or for printing a photograph as a replacement for a silver salt photograph, and two types of paper, plain paper and glossy paper, are sufficient. In recent years, however, paper has become more and more selectively used depending on the application and preference. Photographic paper is also glossy paper with large reflected light, glossy paper with a clear image of the surroundings on the paper, and the surface is half-silk. Paper with various characteristics such as glossy paper has been used. Furthermore, in applications such as art works synthesized with photographs and CG, printing on thick paper with a rough surface such as drawing paper and thin Japanese paper is also being performed. In the future, the use of color printers in the field of design and art will increase, and along with this, the types of printing paper will also increase.
JP 2000-216924 A

  However, it is difficult for the printer to handle all the papers according to the needs from the user, and although the types of genuine papers are increasing, the papers that can be selected by the printer driver are limited.

  With respect to paper that cannot be selected by the printer driver, printing is performed by selecting paper that seems to have close characteristics from the paper that can be selected, but in this case, printing is not necessarily preferable. Therefore, it has been necessary to perform trial and error by changing the type of paper to be selected or changing the image processing conditions (for example, the type of halftone). In addition, the image processing conditions of genuine paper are optimized at a high level for various image quality items, but there are still few image processing conditions that are excellent for all image quality items. The image processing conditions often differ. For example, an image processing condition having a wide color gamut has poor gradation, and an image processing condition with good gradation has a characteristic that the color gamut is narrow.

  Accordingly, the present invention has been made in view of the above problems, and provides an image processing system and method, an image processing apparatus, and a program capable of easily evaluating the image quality of printing under a plurality of image processing conditions. With the goal.

  In order to achieve the above object, one aspect of the present invention includes: a printing unit that prints on a recording medium; and a recording medium that is printed by the printing unit based on a plurality of evaluation images processed according to a plurality of image processing conditions. Measurement means for measuring the plurality of evaluation images, evaluation means for evaluating each of the plurality of image processing conditions based on a measurement result by the measurement means, and the plurality of image processing conditions obtained by the evaluation by the evaluation means Presenting means for presenting each evaluation result to the user, and processing an image to be printed based on the image processing conditions designated by the user from among the evaluation results for each of the plurality of image processing conditions presented by the presenting means Image processing means for performing printing on the recording medium based on the image processed by the image processing means.

  According to another aspect of the present invention, there is provided a processing method in an image processing system having a printing unit that performs printing on a recording medium, and printing is performed by the printing unit based on a plurality of evaluation images processed under a plurality of image processing conditions. Obtained by the measurement step of measuring the plurality of evaluation images from the recorded recording medium, the evaluation step of evaluating each of the plurality of image processing conditions based on the measurement result in the measurement step, and the evaluation in the evaluation step. A presentation step of presenting the evaluation results of each of the plurality of image processing conditions to the user, and an image processing condition instructed by the user from among the evaluation results of the plurality of image processing conditions presented in the presentation step. An image processing step for processing an image to be printed; and a printing step for printing on a recording medium based on the image processed in the image processing step. That.

  One embodiment of the present invention is based on a result of measuring a printing unit that prints on a recording medium and a recording medium printed by the printing unit based on a plurality of evaluation images processed under a plurality of image processing conditions. An evaluation unit that evaluates each of the plurality of image processing conditions, a presentation unit that presents a user with an evaluation result of each of the plurality of image processing conditions obtained by the evaluation by the evaluation unit, and the presentation unit Image processing means for processing an image to be printed based on an image processing condition designated by the user from among the evaluation results of each of the plurality of image processing conditions, wherein the printing means is processed by the image processing means. Printing on a recording medium based on the printed image.

  According to another aspect of the present invention, there is provided a program stored in a computer built in an image processing apparatus by a printing unit that prints on a recording medium, and the printing unit based on a plurality of evaluation images processed according to a plurality of image processing conditions. An evaluation unit that evaluates each of the plurality of image processing conditions based on a result of measurement of a printed recording medium, and a presentation that presents the evaluation result of each of the plurality of image processing conditions obtained by the evaluation by the evaluation unit to the user And an image processing means for processing an image to be printed based on an image processing condition instructed by a user from among the evaluation results of each of the plurality of image processing conditions presented by the presenting means.

  According to the present invention, since the image quality of printing under a plurality of image processing conditions can be easily evaluated, the image processing conditions can be easily selected. Thereby, for example, suitable image processing conditions can be obtained when printing on an arbitrary sheet.

  Hereinafter, an image processing system and method, an image processing apparatus, and a program according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. In the following embodiments, a color printer to which the image processing apparatus according to the present invention is applied will be described as an example.

(Embodiment 1)
FIG. 1 is a diagram illustrating an example of a configuration of an image processing system configured by arranging an image processing apparatus according to the present embodiment.

  In the image processing system, the information processing apparatus 10, the image processing apparatus 20, and the measurement apparatus 30 are connected to each other via communication means configured by a LAN (Local Area Network), a WAN (Wide Area Network), or the like. Note that the communication means may be configured by, for example, a USB (Universal Serial Bus) or the like, and the method is not particularly limited.

  The information processing apparatus 10 inputs an image to be printed into the image processing apparatus 20 via a communication unit. The image processing apparatus 20 processes an image in accordance with predetermined image processing conditions, forms the processed image on a recording medium such as paper, and performs printing. The measuring device 30 is composed of, for example, a scanner, a digital camera, and the like, and reads an image printed on a recording medium such as paper by the image processing device 20 and performs measurement.

  The above is the description of the overall configuration of the image processing system, but the configuration of the above-described image processing system is merely an example, and is not limited thereto. For example, FIG. 1 shows the measurement device 30 as a separate device from the image processing device 20, but it may be implemented inside the image processing device 20 as a measurement unit.

  Each of the information processing apparatus 10, the image processing apparatus 20, and the measurement apparatus 30 includes a computer. The computer includes, for example, main control means such as a CPU and storage means such as ROM (Read Only Memory) and RAM (Random Access Memory). These constituent units are connected by a bus or the like, and are controlled by the main control unit executing a program stored in the storage unit.

  FIG. 2 is a diagram illustrating an example of a functional configuration of the image processing apparatus 20 illustrated in FIG.

  The control unit 101 performs overall control of processing in the image processing apparatus 20. That is, the various processing functions constituting the image processing apparatus 20 operate according to instructions from the control unit 101. The control unit 101 also controls input / output of data generated between the processing functions.

  The image quality evaluation image generation unit 103 generates an image quality evaluation image, and the image quality evaluation image storage unit 102 stores the generated image quality evaluation image. The measurement image storage unit 106 stores measurement images. The image processing condition storage unit 114 stores image processing conditions suitable for paper. The input image storage unit 115 stores an image to be printed.

  The image processing unit 116 performs image processing such as color mapping, color separation, and halftone according to the image processing conditions stored in the image processing condition storage unit 114. Details of the image processing performed by the image processing unit 116 will be described later.

  The printing unit 104 performs printing on a recording medium such as paper. The printing unit 104 may be configured by an ink jet method or a toner method. The method is not particularly limited. For example, the printing unit 104 prints the image quality evaluation image stored in the image quality evaluation image storage unit 102.

  The input / output unit 105 inputs and outputs various data. For example, a measurement image is input from the measurement device 30 and stored in the measurement image storage unit 106. Also, an image is input from an external storage device (not shown) and stored in the input image storage unit 115.

  The image quality evaluation value calculation unit 107 calculates the image quality evaluation value of each image processing condition from the measurement image stored in the measurement image storage unit 106, and the image quality data storage unit 108 calculates the image quality evaluation of the calculated image processing condition. Stores a value.

  The UI unit 110 includes an input device such as an operation button and a display device such as a display, and functions as a user interface that connects the user and the image processing apparatus 20.

  The image quality priority acquisition unit 109 acquires the image quality priority specified by the user via the UI unit 110 and stores it in the image quality item priority storage unit 111. The image quality priority order is, for example, a ranking of which image quality items are prioritized.

  The image processing condition evaluation unit 112 evaluates the image processing condition from the image quality evaluation value of each image processing condition stored in the image quality data storage unit 108. This evaluation result is stored in the evaluation result storage unit 113. The image processing condition evaluation unit 112 also performs a process of sorting the image processing conditions evaluated according to the image quality priority stored in the image quality item priority storage unit 111.

  The above is the description of the configuration of the image processing apparatus 20. Note that the configuration of the image processing apparatus 20 described above is merely an example, and the present invention is not limited to this. Specifically, the functional configuration provided in the image processing apparatus 20 does not necessarily have to be realized as shown in the drawing, and may be realized in whole or in part in any apparatus in the system. Good. For example, all or part of the functions performed by the image processing unit 116 may be realized as a printer driver in the information processing apparatus 10.

  Here, an example of a functional configuration realized in the image processing unit 116 will be described with reference to FIG. However, here, only processing functions necessary for realizing the function as a color printer will be described. Note that some or all of these processing functions may be realized by a program stored in a ROM or the like being executed by the CPU, or may be realized by hardware.

  In the image processing unit 116, a color mapping unit 1201, a color separation unit 1202, and a halftone unit 1203 are realized as functional configurations. The image processing unit 116 converts the color signal RGB of the input image into a color signal C′M′Y′K ′ by these processing function units.

  Here, the color mapping unit 1201 converts an input color signal into a device color signal R′G′B ′ for printing with a target color according to the purpose of color reproduction based on the color mapping table 1204. Here, the purpose of color reproduction refers to, for example, performing monitor matching or preferable color reproduction. The target color is a color within the color gamut of a color printer suitable for the purpose of reproducing each color.

  The color mapping table 1204 uses a three-dimensional lookup table (hereinafter abbreviated as 3DLUT) to hold the correspondence between the discrete input color signal RGB and the device color signal R′G′B ′.

  The color separation unit 1202 converts the device color signal R′G′B ′ into a color material color signal CMYK related to the color material amount of the device based on the color separation table 1205. The color separation table 1205 is also composed of a 3DLUT, and holds the correspondence between the discrete device color signal R′G′B ′ and the color material color signal CMYK. Some color printers use four or more colors, but for example, there are printers that use six colors. In this case, the color separation unit 1202 converts the device color signal into six color material color signals corresponding to each color material.

  The halftone unit 1203 converts the color material color signal CMYK into a binary color material signal C′M′Y′K ′. The binary color material signal C′M′Y′K ′ is composed of binary data of a point where ink is applied and a point where ink is not applied. For example, the halftone unit 1203 converts data of one pixel of the color material color signal CMYK indicating information of 8-bit 256 gradation into binary data of 256 pixels in total of 16 pixels vertically and 16 pixels horizontally. For example, when the C signal of the color material color signal CMYK is 10, the C ′ signal of the corresponding binary color material signal C′M′Y′K ′ is a point where 10 pixels out of 256 pixels are subjected to ink. It becomes. In general, a color printer has a color mapping table 1204 and a color separation table 1205 optimized for each sheet, and the halftone unit 1203 also has a plurality of binarization processing methods.

  Next, an example of the flow of processing in the image processing system shown in FIG. 1 will be described using FIG.

  In the image processing apparatus 20, the image quality evaluation image generation unit 103 first generates an image quality evaluation image (step S201). Although details of the image quality evaluation image will be described later, the evaluation image is generated in order to obtain image quality evaluation values for a plurality of printing methods and a plurality of image quality items. The image processing apparatus 20 causes the printing unit 104 to print the generated image quality evaluation image (step S202).

  Here, for example, the measuring apparatus 30 measures the printed evaluation image (step S203). That is, the image quality evaluation image printed in step S202 is scanned or photographed, and color measurement of the image is performed. As described above, if a measurement unit (for example, a scan unit) is provided in the image processing apparatus 20, this measurement may be performed using the measurement unit.

  Next, the image processing apparatus 20 inputs the measured scan or captured measurement image at the input / output unit 105 (step S204). Then, the image quality evaluation value calculation unit 107 calculates an image quality evaluation value under each image processing condition from the input measurement image (step S205).

  Here, in the image processing apparatus 20, the image quality priority acquisition unit 109 acquires the priority of the image quality items according to the purpose of printing (step S206). Then, the image processing condition evaluation unit 112 evaluates each image processing condition based on the image quality evaluation value calculated in step S205 (step S207). At this time, the image processing condition evaluation unit 112 also sorts the image processing conditions evaluated based on the priority order of the image quality items acquired in step S206.

  After this evaluation, the image processing apparatus 20 outputs the evaluation result of the image processing condition in the UI unit 110 and presents it to the user (step S208). The output of the evaluation result may be performed by printing by the printing unit 104.

  Subsequently, the image processing apparatus 20 acquires which image processing condition is suitable (step S209). That is, the evaluation result of each image processing condition is presented to the user, and an instruction from the user based on the presentation is acquired via the UI unit 110. Here, the acquired image processing conditions are image processing conditions suitable for the target paper.

  The image processing apparatus 20 performs printing according to the image processing conditions acquired in step S209. That is, the input / output unit 105 inputs an image to be printed (step S210), and the image processing unit 116 processes the image according to the image processing conditions acquired in step S209 (step S211). Then, in the printing unit 104, the processed image is printed (step S212). Here, it is determined whether printing is finished, that is, whether or not it is the final image. If it is not the final image (NO in step S213), the process returns to step S210, and if it is the final image (YES in step S213), this The process ends.

  Next, the image quality evaluation image generated in step S201 in FIG. 4 will be described with reference to FIGS.

  FIG. 5 is a schematic diagram illustrating an example of an image quality evaluation image. Reference numerals 301 to 316 are evaluation images for evaluating the image quality, and are generated based on different image processing conditions. That is, evaluation images corresponding to 16 image processing conditions are arranged in one image.

  Here, an example of image processing conditions set for each of the evaluation images shown in FIG. 5 will be described with reference to FIG. FIG. 6 shows combinations of processes in the color mapping table 1204, the color separation table 1205, and the halftone unit 1203 when generating each of the evaluation images shown in FIG. In this case, 16 types of image processing conditions are created by combining 4 types of color mapping tables (C1 to C4), 2 types of color separation tables (S1, S2), and 2 types of halftone processing (H1, H2). .

  FIG. 7 is a schematic diagram illustrating an example of an original image of the evaluation images 301 to 316 illustrated in FIG.

  The evaluation image includes a color chart for color gamut evaluation 501 that evaluates how vivid colors can be reproduced (reproducibility), and a color chart for evaluation of graininess 502 that evaluates the roughness (graininess) of the image. And a tone evaluation image portion 503 for evaluating tone jump (gradation). The original image of the evaluation image is composed of, for example, an 8-bit RGB color signal.

  A color chart constituting the color chart for color gamut evaluation 501, for example, 501 a is a grid point of RGB 9 slices, and any one of the R signal, G signal, and B signal has a value of 0 or 255. It is composed of the outermost single color signal. Note that the grid points of RGB 9 slices are (R, G, B) = (0, 0, 0), (0, 0, 32), (0, 0, 64), ... (0, 0, 255), (0, 32, 0), (0, 32, 32), ... (255, 255, 255).

  The color chart constituting the graininess evaluation color chart section 502, for example 502a, is composed of a single color signal corresponding to 16 gray levels of gray or skin color in which graininess is important. Note that the 16 gray levels are (R, G, B) = (0, 0, 0), (32, 32, 32), (64, 64, 64), ... (255, 255). 255). The color chart constituting the graininess evaluation color chart section 502 is configured to have a larger size than the color chart constituting the color gamut evaluation color chart portion 501 in order to extract in-plane variation.

  The above is the description of the original images of the evaluation images 301 to 316, but the original image, that is, the evaluation image is not limited to this configuration. For example, it may be configured to include at least one of the color chart unit for color gamut evaluation 501, the color chart unit for graininess evaluation 502, and the image unit for gradation evaluation 503.

  FIG. 8 is a schematic diagram illustrating an example of a tone evaluation image constituting the tone evaluation image unit 503. The tone evaluation image is, for example, 503a shown in FIG.

  The tone evaluation image is white (255, 255, 255), black (0, 0, 0), six colors, and two colors plus four colors, for example, white (W), black (K) , Red (R) (255, 0, 0) and cyan (C) (0, 255, 255) at the vertices. The color signal on each side of the square is composed of color signals obtained by linearly interpolating the vertex color signals. For example, the color signal at a point A between black (K) and red (R) is (128, 0, 0). Similarly, the color signal on the diagonal line connecting white (W) and black (K) is composed of a color signal obtained by linearly interpolating white and black, and further, the color between the diagonal line and each side of the square. The signal is composed of a color signal obtained by linearly interpolating the diagonal line and the color signal of each side. For example, the color signal B shown in FIG. 8 is obtained by linear interpolation from the color signal at the point C on the side of the square and the color signal at the point D on the diagonal line. An area surrounded by a dotted line in the figure indicates an evaluation area used for calculation of a gradation evaluation value described later.

  As described above, the evaluation images 301 to 316 shown in FIG. 5 are composed of the binary color material signals C′M′Y′K ′ obtained by processing the original image shown in FIG. 7 according to the corresponding image processing conditions. . For example, the evaluation image 301 is subjected to color mapping using the C1 color mapping table, color separation using the S1 color separation table, and H1 halftone processing (see FIG. 6).

  Next, the measurement in step S203 in FIG. 4 will be described.

  As described above, in this embodiment, the image quality when the image processing apparatus 20 performs printing under predetermined image processing conditions is evaluated by scanning or photographing an evaluation image printed using a scanner or a digital camera. To obtain a measurement result. Since this measurement requires an image in which color charts are arranged closely, a scanner or digital camera having a high resolution is used. The scanner and the digital camera use those that can convert RGB color signals constituting a measurement image that has been calibrated in advance and scanned or photographed into colorimetric color signals, for example, LAB color signals of the CIELAB color system. Further, it is preferable that the scanner or digital camera has an input RGB color signal having an accuracy of 12 bits or more.

  Next, calculation of the image quality evaluation value in step S205 in FIG. 4 will be described. In the present embodiment, a case where three image quality evaluation values of color gamut, graininess, and gradation are calculated will be described as an example. Of course, other image quality evaluation values are calculated. Alternatively, at least one of them may be calculated.

  FIG. 9 is a flowchart illustrating an example of a procedure for calculating an image quality evaluation value. This process is mainly performed by the image quality evaluation value calculation unit 107.

  The image quality evaluation value calculation unit 107 first converts the color signal constituting the input measurement image from the RGB color signal to the colorimetric color signal LAB color signal (step S701), and cuts out each evaluation color chart and evaluation image. This is performed (step S702). Each evaluation color chart and evaluation image are cut out except for the edge portion.

  When this processing is completed, the image quality evaluation value calculation unit 107 averages the color charts for color gamut evaluation among the color charts cut out in step S702 (step S703). In the averaging, for example, the L signal average, the A signal average, and the B signal average are calculated with respect to the LAB color signal constituting the cut color chart image. Then, the image quality evaluation value calculation unit 107 calculates a color gamut evaluation value. The color gamut evaluation value is calculated based on the color gamut volume. For example, in the CIALAB color space, the size of the area surrounded by the average LAB of the color gamut evaluation color chart calculated in step S703 is calculated, and this value is normalized so that the sRGB color gamut volume becomes 100.

  Subsequently, the image quality evaluation value calculation unit 107 calculates a granularity evaluation value (step S705). The graininess evaluation value is calculated based on, for example, the color variation of the graininess evaluation color chart. In addition, the image quality evaluation value calculation unit 107 calculates a gradation evaluation value (step S706). The gradation evaluation value is calculated based on, for example, the second derivative of the color signal in the evaluation area indicated by the dotted line in the gradation evaluation image shown in FIG. Preferably, the granularity evaluation value and the gradation evaluation value are normalized so that the granularity and gradation of the reference sheet become 100. Then, this process ends.

  Next, the image processing condition evaluation result output in step S208 in FIG. 4 will be described.

  FIG. 10 is a diagram illustrating an example of an image processing condition evaluation screen displayed (presented) on the UI unit 110 illustrated in FIG.

  The image processing condition evaluation screen includes an image quality display unit 801, a color gamut button 802, a graininess button 803, a gradation button 804, a setting button 805, and a mouse pointer 806.

  The image quality display unit 801 displays a list of image quality for each image processing condition and is used for designating the image processing condition. Corresponding to each image processing condition, its name and the color gamut evaluation value, graininess evaluation value, and gradation evaluation value calculated in step S205 are displayed. Further, as indicated by A in the figure, the line indicating the currently designated image processing condition is displayed in reverse video. The image processing condition can be specified by selecting a line displaying the specified image processing condition with the mouse pointer 806.

  A color gamut button 802, a graininess button 803, and a gradation button 804 are used for designating the priority order of image quality evaluation. For example, when the color gamut button 802 is selected by the mouse pointer 806 or the like, the image processing conditions displayed on the image quality display unit 801 are rearranged in the order of the color gamut evaluation values. Similarly, when the graininess button 803 is selected, the image processing conditions displayed on the image quality display unit 801 are rearranged in the order of the graininess evaluation value, and when the gradation button 804 is selected, the image quality display unit 801 is displayed. The displayed image processing conditions are rearranged in the order of the tone evaluation value.

  A setting button 805 is a button for setting an image processing condition. When the setting button is selected by the mouse pointer 806 or the like, the currently designated image processing condition is set.

  As described above, according to the first embodiment, the image quality of printing under a plurality of image processing conditions can be easily evaluated, so that the image processing conditions can be easily selected. Thereby, for example, suitable image processing conditions can be obtained when printing on an arbitrary sheet. In addition, since the order of the evaluated image processing conditions can be rearranged, the optimum image processing conditions can be easily selected according to the purpose of printing.

(Embodiment 2)
A phenomenon in which the color changes and cannot be seen even under different illumination and viewing conditions is called color constancy. For example, white paper is judged to be white even when viewed under the yellow-red color of the lamp or under pale blue illumination of a fluorescent lamp. When viewed under a lamp and when viewed under a fluorescent lamp, the color of light entering the eyes is different, but if the relative relationship with the illumination is maintained, they are recognized as substantially the same color.

  On the other hand, in the color printed by the color printer, the relative relationship between the illumination and the light from the printed material when observed under the illumination may change depending on the illumination. In this case, even if the color reproduction is suitable under a certain illumination, the evaluation may be lowered under another illumination.

  Therefore, in the second embodiment, a description will be given of a case where an illumination condition is added in acquiring an image quality evaluation value, an image quality evaluation value under specified illumination is acquired, and an image processing condition is acquired based on the acquired image quality evaluation value. Note that the configurations of the image processing system and the image processing apparatus 20 according to the second embodiment are the same as the configurations of FIGS. 1, 2, and 3 that explain the first embodiment, and thus the description thereof is omitted.

  First, an example of a processing flow in the image processing system according to the second embodiment will be described with reference to FIG. Here, in order to avoid duplication of description, the same processes as those in FIG. 4 describing the first embodiment are denoted by the same reference numerals, and the description thereof is omitted.

  The image processing device 20 or the measurement device 30 performs the processing from step S201 to step S204 described above. After this processing, the image processing apparatus 20 acquires illumination conditions for evaluating image quality (step S1001). In the process in step S205, in addition to the first embodiment, an image quality evaluation value including color constancy is calculated, and the processes in and after step S207 are performed.

  Next, the measurement in step S203 according to the second embodiment will be described.

  Unlike the first embodiment, the measurement according to the second embodiment needs to acquire spectral data instead of colorimetric data (LAB). Therefore, in this embodiment, a multiband camera is used as a spectroscopic measuring device. A multiband camera acquires colors using four or more filters, whereas a normal camera acquires colors using three filters R, G, and B. If a multi-band camera is used to photograph a reference chart with known spectral reflectance and a subject, spectral reflectance information of the subject can be acquired. The spectral reflectance information is, for example, spectral reflectance at each wavelength in a 10 nm step when the wavelength range is 400 nm to 700 nm. Since the image quality evaluation image according to the second embodiment is the same as that of the first embodiment, the description thereof is omitted.

  Next, calculation of image quality evaluation values according to the second embodiment will be described.

  FIG. 12 is a flowchart illustrating an example of a procedure for calculating an image quality evaluation value. This process is mainly performed by the image quality evaluation value calculation unit 107. Here, in order to avoid duplication of description, the same processes as those in FIG. 9 describing the first embodiment are denoted by the same reference numerals, and the description thereof is omitted.

  The image quality evaluation value calculation unit 107 first calculates a colorimetric value LAB from the spectral reflectance R (λ) (step S1101). As described above, the measurement data in the second embodiment is not the RGB signal but the spectral reflectance signal R (λ). From this spectral reflectance signal and the illumination condition acquired in step S1001 in FIG. 11, a colorimetric value LAB under the illumination condition is calculated. The calculation of LAB may be performed based on, for example, JISZ8701 and JISZ8729. Thereafter, as in the first embodiment, the image quality evaluation value calculation unit 107 performs the processing from step S702 to step S706 to calculate the evaluation values of the color gamut, graininess, and gradation.

  When the processing up to step S706 is completed, the image quality evaluation value calculation unit 107 uses the spectral reflectance of the color gamut evaluation color chart and the predetermined reference illumination information R0 (λ) under the reference illumination in the same manner as in step S1101. The colorimetric value L0A0B0 is acquired (step S1102). Then, an evaluation value of color consistency is calculated from the colorimetric value under the reference illumination (L0A0B0) and the colorimetric value under the illumination (LAB) acquired in step S1001 in FIG. 11 (step S1003). The evaluation value of the color constant is, for example, a color difference or / and a hue difference between the colorimetric value under the reference illumination (L0A0B0) and the colorimetric value under the illumination (LAB) acquired in step S1001 in FIG.

  Next, the image processing condition evaluation result output in step S208 according to the second embodiment will be described.

  FIG. 13 is a diagram illustrating an example of an image processing condition evaluation screen displayed (presented) on the UI unit 110 according to the second embodiment. Here, in order to avoid duplication of description, the same components as those in FIG. 10 describing the first embodiment are denoted by the same reference numerals, and description thereof is omitted.

  The image processing condition evaluation screen according to the second embodiment is different from the first embodiment in the image quality display unit 1101, the illumination condition list box 1102, and the color constant button 1103.

  In the image quality display unit 1101, color constant display is added. The lighting condition list box 1102 is a UI for acquiring the lighting conditions. When the lighting condition list box 1102 is selected with the mouse pointer 806, general lighting conditions can be selected. Typical illumination conditions include, for example, a halogen lamp, a three-wavelength region-emitting fluorescent lamp, a high color rendering fluorescent lamp, CIE daylight (such as D50), and the like. Similar to the color gamut button 802, graininess button 803, and gradation button 804, the color constant button 1103 is used to specify the priority order of image quality evaluation. When the color constant button 1103 is selected by the mouse pointer 806 or the like, the image processing conditions displayed on the image quality display unit 1101 are rearranged in the order of color constant.

  As described above, according to the second embodiment, the image processing condition can be selected based on the image quality evaluation value under the designated illumination. Therefore, the image processing condition more suitable for the purpose of printing can be selected than in the first embodiment. become.

  The above is an example of a typical embodiment of the present invention, but the present invention is not limited to the embodiment described above and shown in the drawings, and can be appropriately modified and implemented without departing from the scope of the present invention. .

  For example, in the first and second embodiments described above, the image processing condition is determined based on the evaluation of the image quality. However, an image to be printed may be taken into account when acquiring the image quality evaluation value. Specifically, an image quality evaluation value of an image to be printed is acquired, and an image processing condition is acquired based on the acquired image quality evaluation value. In this case, for example, the color signal constituting the image to be printed is evaluated as to what percentage is out of the color gamut, and the color constant among the color signals constituting the image to be printed is a predetermined color or more. An evaluation value such as the percentage of the signal is calculated. Further, when obtaining an image quality evaluation value in consideration of an image to be printed, the configuration of the image quality evaluation image may be changed according to the image to be printed. For example, graininess and color constancy may be evaluated using a color signal used in an image to be printed.

  It should be noted that the present invention can take the form of, for example, a system, apparatus, method, program, or recording medium. Specifically, the present invention may be applied to a system composed of a plurality of devices, or may be applied to an apparatus composed of a single device.

  Further, the present invention achieves the functions of the embodiments by supplying a software program directly or remotely to a system or apparatus, and reading and executing the supplied program code by a computer incorporated in the system or apparatus. This includes cases where In this case, the supplied program is a computer program corresponding to the flowchart shown in the drawings in the embodiment.

  Accordingly, since the functions of the present invention are implemented by computer, the program code installed in the computer also implements the present invention. In other words, the present invention includes a computer program itself for realizing the functional processing of the present invention. In that case, as long as it has the function of a program, it may be in the form of object code, a program executed by an interpreter, script data supplied to an OS (Operating System), or the like.

  Examples of the computer-readable recording medium for supplying the computer program include the following. For example, floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, MO, CD-ROM, CD-R, CD-RW, magnetic tape, nonvolatile memory card, ROM, DVD (DVD-ROM, DVD- R).

  As another program supply method, a client computer browser is used to connect to a homepage on the Internet, and the computer program of the present invention is downloaded from the homepage to a recording medium such as a hard disk. In this case, the downloaded program may be a compressed file including an automatic installation function. It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from a different homepage. That is, a WWW server that allows a plurality of users to download a program file for realizing the functional processing of the present invention on a computer is also included in the present invention.

  Further, the program of the present invention may be encrypted, stored in a recording medium such as a CD-ROM, and distributed to users. In this case, a user who has cleared a predetermined condition is allowed to download key information for decryption from a homepage via the Internet, execute an encrypted program using the key information, and install the program on the computer. You can also.

  In addition to the functions of the above-described embodiment being realized by the computer executing the read program, the embodiment of the embodiment is implemented in cooperation with an OS or the like running on the computer based on an instruction of the program. A function may be realized. In this case, the OS or the like performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

  Furthermore, the program read from the recording medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, so that part or all of the functions of the above-described embodiments are realized. May be. In this case, after a program is written to the function expansion board or function expansion unit, the CPU (Central Processing Unit) provided in the function expansion board or function expansion unit is a part of the actual processing or based on the instructions of the program. Do everything.

It is a figure which shows an example of a structure of the image processing system comprised by arranging the image processing apparatus concerning this embodiment. It is a figure which shows an example of a functional structure in the image processing apparatus 20 shown in FIG. It is a figure which shows an example of a functional structure in the image process part 116 shown in FIG. 2 is a flowchart illustrating an example of a processing flow in the image processing system illustrated in FIG. 1. It is a schematic diagram which shows an example of an image quality evaluation image. It is a figure which shows an example of the image processing conditions set to each evaluation image shown in FIG. It is a schematic diagram which shows an example of the original image of the evaluation images 301-316 shown in FIG. It is a schematic diagram which shows an example of the image for gradation evaluation which comprises the image part for gradation evaluation 503 shown in FIG. 5 is a flowchart illustrating an example of a procedure for calculating an image quality evaluation value in step S205 in FIG. 4. FIG. 3 is a diagram showing an example of an image processing condition evaluation screen displayed (presented) on a UI unit 110 shown in FIG. 10 is a flowchart illustrating an example of a processing flow in the image processing apparatus 20 according to the second embodiment. 10 is a flowchart illustrating an example of a procedure for calculating an image quality evaluation value according to the second embodiment. 10 is a diagram illustrating an example of an image processing condition evaluation screen displayed (presented) on a UI unit 110 according to Embodiment 2. FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Information processing apparatus 20 Image processing apparatus 30 Measuring apparatus 101 Control part 102 Image quality evaluation image storage part 103 Image quality evaluation image generation part 104 Printing part 105 Input / output part 106 Measurement image data storage part 107 Image quality evaluation value calculation part 108 Image quality data storage part 109 Image quality priority acquisition unit 110 UI unit 111 Image quality item priority storage unit 112 Image processing condition evaluation unit 113 Evaluation result storage unit 114 Input image storage unit 115 Image processing unit 1201 Color mapping unit 1202 Color separation unit 1203 Halftone unit 1204 Color Mapping table 1205 Color separation table

Claims (9)

Printing means for printing on a recording medium;
Measuring means for measuring the plurality of evaluation images from a recording medium printed by the printing means based on a plurality of evaluation images processed under a plurality of image processing conditions;
Evaluation means for evaluating each of the plurality of image processing conditions based on a measurement result by the measurement means;
Presenting means for presenting to the user the evaluation results of each of the plurality of image processing conditions obtained by the evaluation by the evaluating means;
Image processing means for processing an image to be printed based on an image processing condition designated by the user from among the evaluation results of each of the plurality of image processing conditions presented by the presenting means,
The printing means includes
An image processing system for performing printing on a recording medium based on an image processed by the image processing means. Each of the evaluation images is
Color chart for color gamut evaluation for evaluating reproducibility of color gamut, Color chart for color grain evaluation for evaluating graininess of image, Image section for gradation evaluation for evaluating gradation The image processing system according to claim 1, comprising at least one of the following. The evaluation means includes
Calculating an evaluation value including at least one of color gamut, graininess, and gradation corresponding to each of the plurality of image processing conditions based on a result of measuring the plurality of evaluation images by the measuring unit; The image processing system according to claim 1, wherein evaluation is performed. The measuring means includes
Measure the spectral reflectance of multiple evaluation images processed under multiple image processing conditions with a spectrometer.
The evaluation means includes
A color generated by the illumination condition corresponding to each of the plurality of image processing conditions based on the illumination condition serving as a reference when evaluating the image quality of the evaluation image and the result of measuring the plurality of evaluation images by the measurement unit The image processing system according to claim 1, wherein the evaluation is performed by calculating an evaluation value including a constant. The presenting means is
The image processing system according to claim 3 or 4, wherein the plurality of image processing conditions are rearranged and presented based on an evaluation value corresponding to each of the plurality of image processing conditions and a predetermined priority. The image processing means includes
Color mapping means for converting color signals based on a color mapping table;
Color separation means for converting the color signal converted by the color mapping means into a color material color signal corresponding to the color material color of the printing means based on a color separation table;
Halftone means for converting the color material color signal converted by the color separation means into a binary color material signal;
The image processing conditions performed by the color mapping means, the color separation means, and the halftone means are changed based on the image processing conditions designated by the user based on the evaluation result presented by the presenting means. The image processing system according to claim 1. A processing method in an image processing system having printing means for printing on a recording medium,
A measuring step of measuring the plurality of evaluation images from a recording medium printed by the printing unit based on a plurality of evaluation images processed under a plurality of image processing conditions;
An evaluation step for evaluating each of the plurality of image processing conditions based on a measurement result in the measurement step;
A presenting step for presenting a user with an evaluation result of each of the plurality of image processing conditions obtained by the evaluation in the evaluation step;
An image processing step of processing an image to be printed based on an image processing condition instructed by a user from among evaluation results of each of the plurality of image processing conditions presented in the presenting step;
A printing step of printing on a recording medium based on the image processed in the image processing step. Printing means for printing on a recording medium;
Evaluation means for evaluating each of the plurality of image processing conditions based on a result of measuring a recording medium printed by the printing means based on a plurality of evaluation images processed under a plurality of image processing conditions;
Presenting means for presenting to the user the evaluation results of each of the plurality of image processing conditions obtained by the evaluation by the evaluating means;
Image processing means for processing an image to be printed based on an image processing condition designated by the user from among the evaluation results of each of the plurality of image processing conditions presented by the presenting means,
The printing means includes
An image processing apparatus for printing on a recording medium based on an image processed by the image processing means. A computer built into the image processing device
Printing means for printing on a recording medium;
An evaluation unit that evaluates each of the plurality of image processing conditions based on a result of measuring a recording medium printed by the printing unit based on a plurality of evaluation images processed under a plurality of image processing conditions;
Presenting means for presenting the evaluation results of each of the plurality of image processing conditions obtained by the evaluation by the evaluating means to the user
A program for causing an image processing unit to function as an image processing unit that processes an image to be printed based on an image processing condition instructed by a user from among evaluation results of a plurality of image processing conditions presented by the presenting unit.

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