Color prediction model creating method, color prediction model creating device, printing system, and computer program

Abstract

To provide a technique for creating a color prediction model while taking into consideration the priorities of work time and prediction accuracy.SOLUTION: A method for creating a color prediction model includes a step of (a) accepting process settings for creating a color prediction model, and a step of (b) creating a color prediction model in accordance with the process settings. The step of (b) includes a step of (b1) printing a color chart with a printing device, a step of (b2) acquiring a measurement result of the spectral reflectance of the color chart, a step of (b3) creating learning data including the measurement result of the spectral reflectance, and a step of (b4) executing of learning of the color prediction model using learning data. The process settings include a setting regarding a relative priority between the work time required for the step of (b) and the prediction accuracy of the color prediction model, and the implementation content of the step of (b) is changed according to the relative priority.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to a method for creating a color prediction model, a color prediction model creating device, a printing system, and a computer program. [Background technology]

[0002] In the printing device, a color conversion process is performed to convert the color values ​​of the input image data expressed in a first color system into color values ​​in a second color system corresponding to the type of ink. In the color conversion process, a plurality of color conversion tables for associating the color values ​​of the first color system with the color values ​​of the second color system are referenced. When creating such a color conversion table, a color prediction model is used that predicts the spectral reflectance of a printed matter printed with an arbitrary ink amount set from the ink amount set. Patent Document 1 disclosed by the applicant of the present disclosure discloses a method for creating a teacher data set for a color prediction model by repeating data selection and learning from a group of virtual teacher data candidates created using a pre-model. According to this method, the prediction accuracy of the color prediction model can be efficiently improved by additionally selecting teacher data for the color prediction model. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2023-128280 A Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, it is not always desirable to spend a long time working to create a color prediction model with the highest accuracy, and there are cases where it is desirable to create a color prediction model in a short amount of time even if the prediction accuracy is somewhat inferior. Also, as the use of color prediction models becomes more widespread, it has become necessary to balance prediction accuracy and work time depending on the application. [Means for solving the problem]

[0005] According to a first aspect of the present disclosure, there is provided a method for creating a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set. The method includes the steps of (a) accepting a process setting for creating the color prediction model, and (b) creating the color prediction model in accordance with the process setting. The process (b) includes the steps of (b1) printing a color chart using a printing device, (b2) acquiring a measurement result of the spectral reflectance of the color chart, (b3) creating learning data including the measurement result of the spectral reflectance, and (b4) executing learning of the color prediction model using the learning data. The process setting includes a setting for a relative priority between the work time required for the process (b) and the prediction accuracy of the color prediction model, and the implementation content of the process (b) is changed according to the relative priority.

[0006] According to a second aspect of the present disclosure, there is provided a color prediction model creation device that creates a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set. The color prediction model creation device includes a process setting unit that accepts process settings related to the creation of the color prediction model, and a model creation unit that creates the color prediction model according to the process settings. The model creation unit includes a print execution unit that prints a color chart using a printing device, a measurement result acquisition unit that acquires a measurement result of the spectral reflectance of the color chart, a learning data creation unit that creates learning data including the measurement result of the spectral reflectance, and a learning unit that executes learning of the color prediction model using the learning data. The process settings include a setting related to a relative priority between the work time required for the process of the model creation unit and the prediction accuracy of the color prediction model, and the implementation content of the model creation unit is changed according to the relative priority.

[0007] According to a third embodiment of the present disclosure, a printing system is provided. The printing system includes a color prediction model creation device that creates a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set, and a printing device. The color prediction model creation device includes a process setting unit that accepts process settings related to the creation of the color prediction model, and a model creation unit that creates the color prediction model according to the process settings. The model creation unit includes a print execution unit that prints a color chart using the printing device, a measurement result acquisition unit that acquires a measurement result of the spectral reflectance of the color chart, a learning data creation unit that creates learning data including the measurement result of the spectral reflectance, and a learning unit that executes learning of the color prediction model using the learning data. The process settings include a setting related to a relative priority between the work time required for the process of the model creation unit and the prediction accuracy of the color prediction model, and the implementation content of the model creation unit is changed according to the relative priority.

[0008] According to a fourth aspect of the present disclosure, there is provided a computer program for creating a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set. The computer program causes a computer to execute (a) a process of accepting a process setting related to the creation of the color prediction model, and (b) a process of creating the color prediction model in accordance with the process setting. The process (b) includes (b1) a process of printing a color chart by a printing device, (b2) a process of acquiring a measurement result of the spectral reflectance of the color chart, (b3) a process of creating learning data including the measurement result of the spectral reflectance, and (b4) a process of learning the color prediction model using the learning data. The process setting includes a setting related to a relative priority between the work time required for the process (b) and the prediction accuracy of the color prediction model, and the implementation content of the process (b) is changed according to the relative priority. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram of a printing system. [Diagram 2] FIG. 4 is an explanatory diagram showing an example of color chart information. [Diagram 3] 11 is a flowchart showing the procedure of a process for creating a color prediction model. [Figure 4] FIG. 4 is an explanatory diagram showing an example of a print setting window. [Diagram 5] FIG. 4 is an explanatory diagram showing an example of a color measurement setting window. [Figure 6] FIG. 11 is an explanatory diagram showing an example of a window for selecting color chart data. [Figure 7] FIG. 13 is an explanatory diagram showing an example of a priority setting window. [Figure 8] FIG. 13 is an explanatory diagram showing another example of the priority setting window. [Figure 9] 6A and 6B are explanatory diagrams showing differences in color charts printed according to priority settings. [Figure 10] FIG. 1 is an explanatory diagram showing an example of a printing device including a color measurement device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] 1 is a block diagram showing a schematic configuration of a printing system according to an embodiment of the present invention. The printing system 500 includes a color prediction model creation device 100, a printing device 200, a color measurement device 300, and a display device 400.

[0011] The color prediction model creation device 100 creates a color prediction model CM that predicts the spectral reflectance of a printed material printed with an ink amount set used in the printing device 200, from that ink amount set. An "ink amount set" refers to a combination of ink amounts of multiple types of ink that can be used in the printing device 200. A combination of multiple types of ink that can be used in the printing device 200 is called an "ink set."

[0012] The color prediction model creation device 100 is a computer including a CPU 50, a storage unit 60, and an input / output interface 70. The CPU 50, the storage unit 60, and the input / output interface 70 are connected via an internal bus so as to be able to communicate bidirectionally.

[0013] The CPU 50 executes a color prediction model creation program 61 pre-stored in the storage unit 60, thereby functioning as a processing setting unit 51, a print execution unit 52, a measurement result acquisition unit 53, a learning data creation unit 54, and a learning unit 55. Among these, the print execution unit 52, the measurement result acquisition unit 53, the learning data creation unit 54, and the learning unit 55 constitute a model creation unit 56. Note that at least a part of the functions of these units 51 to 55 may be realized by a hardware circuit, or may be realized on the cloud.

[0014] The process setting unit 51 accepts various process settings related to the creation process of the color prediction model CM. The process settings include a setting related to the relative priority between the work time required to create the color prediction model CM and the prediction accuracy of the color prediction model CM. The contents of the process settings will be described further below.

[0015] The model creation unit 56 executes a process of creating a color prediction model CM in accordance with the process settings set by the process setting unit 51. The process contents of the units 52 to 55 included in the model creation unit 56 are as follows.

[0016] The print execution unit 52 prints a color chart CC by the printing device 200 using one color chart data 62 selected from the multiple color chart data 62. The measurement result acquisition unit 53 causes the color measurement device 300 to measure the spectral reflectance R(λ) of the printed color chart CC and acquires the measurement result. The learning data creation unit 54 creates learning data including the measurement result of the spectral reflectance R(λ). The learning data is data indicating the correspondence between the ink amount set and the spectral reflectance R(λ) for each of the multiple color patches represented by the color chart data 62. The learning unit 55 executes learning of the color prediction model CM using the learning data.

[0017] In addition to the color prediction model creation program 61, the storage unit 60 stores a plurality of color chart data 62 and color chart information 63. The color chart data 62 is image data representing a color chart including a plurality of single-color color patch groups and a plurality of mixed-color color patch groups. The pixel values ​​of the color chart data 62 are represented by ink amount sets. In this embodiment, a plurality of color chart data 62 are created in advance and stored in the storage unit 60. The color chart information 63 is information relating to each individual color chart data 62. The contents of the color chart information 63 will be described later.

[0018] The printing device 200 has a plurality of ink containers 210, each of which contains one type of ink. In this embodiment, the number of ink containers 210 is six, and an ink set containing six types of ink, CMYKLcLm, can be used. Here, C is cyan, M is magenta, Y is yellow, K is black, Lc is light cyan, and Lm is light magenta process ink. The printing device 200 may be configured to be able to use spot color inks. Also, not only the ink color type but also the number of ink colors can be set arbitrarily.

[0019] The input / output interface 70 transmits images such as the color chart data 62 to the printing device 200, and also receives color measurement results of the print image printed on the printing medium P from the color measurement device 300. The input / output interface 70 further transmits display images to the display device 400, and displays various windows and processing results, which will be described later.

[0020] The printing device 200 is an inkjet printer that prints an image on the printing medium P by ejecting ink onto the printing medium P. Upon receiving color chart data 62 from the color prediction model creation device 100, the printing device 200 prints a color chart CC on the printing medium P in response to the color chart data 62.

[0021] The color measurement device 300 measures the color of a printed matter produced by the printing device 200. The color measurement device 300 measures the spectral reflectance R(λ) of each of a plurality of color patches included in the color chart CC. The measured spectral reflectance R(λ) is supplied to the color prediction model creation device 100.

[0022] 2 is an explanatory diagram showing an example of the color chart information 63. The color chart information 63 is information in which five items are registered for each color chart data 62: (1) media name, (2) media surface type, (3) ink set, (4) color chart data name, and (5) auxiliary information.

[0023] In this disclosure, "media" refers to print media. In the example of Fig. 2, four media names, Photo_A, Photo_B, Mat_A, and Mat_B, are presented. As described in the media surface type column, Photo_A and Photo_B are glossy paper, and Mat_A and Mat_B are matte paper. Two types of ink sets, CMYK and CMYKLcLm, are presented.

[0024] "Ink set CMYK" means one of the following: (a) Ink set for a printing device equipped with only CMYK inks. (b) An ink set used in a printing mode that does not use inks other than CMYK (Lc ink and Lm ink) among the CMYKLcLm inks installed in the printing device. It is usually used in the sense of (a) above, but it may also be used in the sense of (b) above.

[0025] As auxiliary information, whether or not the color chart data for Photo_A and Photo_B can be used to create a color prediction model for Photo_C is registered. Specifically, the color chart data for Photo_A can be used to create a color prediction model for Photo_C, and the color chart data for Photo_B cannot be used to create a color prediction model for Photo_C. Photo_C is a medium that has color development characteristics similar to those of Photo_A.

[0026] The reason why color chart data for Photo_C is not prepared and the fact that it can be substituted with other media is registered in the auxiliary information is that it is practically difficult to prepare color chart data for all media that are expected to be used. For this reason, in this embodiment, it is assumed that color chart data will be prepared for representative media and that the color chart data will be used for media with similar characteristics.

[0027] It should be noted that some of the five items illustrated in FIG. 2 may be omitted, for example, the auxiliary information may be omitted.

[0028] In the embodiment described below, one piece of color chart data 62 is selected using color chart information 63. Furthermore, the selected color chart data 62 is used to sequentially print a color chart CC, measure the spectral reflectance, create learning data, and learn a color prediction model CM. However, it is also possible to automatically select color chart data to be referenced when print settings, which will be described later, are made without using the color chart information 63.

[0029] 3 is a flowchart showing the procedure of the process of creating a color prediction model. In step S10, the process setting unit 51 accepts various process settings related to the process of creating the color prediction model CM. The process settings include (1) print settings, (2) color measurement settings, (3) selection of color chart data, and (4) priority settings. These process settings will be described in order below.

[0030] 4 is an explanatory diagram showing an example of a print setting window W1. Using this window W1, the user can set four items related to printing the color chart CC: (1) media name, (2) number of passes, (3) duty limit value, and (4) whether or not to perform color correction.

[0031] "Number of passes" refers to the number of main scans of the print head required to print all the pixels on one main scan line. For example, "4 passes" means that all the pixels on one main scan line are printed by performing four main scans. It is also possible to select, for example, 1 pass or 2 passes as the number of passes.

[0032] The "duty limit value" is the upper limit of the total amount of ink permitted to be ejected per pixel. In the example of Figure 4, the duty limit value to be used for actual printing can be specified, taking into consideration cases where the media selected in the print settings differs from the media used for actual printing. In this case, the amount of ink ejected per pixel during actual printing is corrected as follows, taking into consideration the specified duty limit value. Vc = V × (Dt_set / Dt_pre) …(q1) Here, Vc is the corrected ink amount, V is the original ink amount, Dt_set is the duty limit value specified in the print settings, and Dt_pre is the duty limit value set when the color chart data 62 was created. Normally, Dt_set is set to a value equal to or less than Dt_pre. However, Dt_set may be set to a value greater than Dt_pre.

[0033] For "color correction," you can specify either no color correction or color correction. The "no color correction" setting means that when using a RIP (Raster Image Processor) or other process to print a color chart CC, the color management function is turned off so that no color correction is performed.

[0034] Note that some of the four items that can be set in the print setting window W1 may be omitted, and other items may be added. This also applies to the windows for other process settings described below.

[0035] 5 is an explanatory diagram showing an example of the color measurement setting window W2. Using this window W2, the user can set three items related to the spectral reflectance measurement of the printed color chart CC: (1) the measurement device, (2) the measurement method, and (3) the number of measurements.

[0036] "Measurement device" is a setting of identification information of the color measurement device 300. As the identification information, a model number or a device name can be used.

[0037] As the "measurement method," a measurement method that can be performed by the colorimetric device 300 can be selected. Two measurement methods are generally known: spot colorimetry and scan colorimetry. Spot colorimetry is a method in which the colorimetric device stops at each color patch to measure the color. Scan colorimetry is a method in which multiple color patches are read continuously while the measurement device is moved. Scan colorimetry can complete the measurement of one page's worth of color patches in significantly less work time than spot colorimetry.

[0038] The "number of measurements" can be set to one, or any number of measurements greater than or equal to two. In general, the more measurements are made, the less variation there is in the measurement results of the spectral reflectance, and the more accurate the predictions of the color prediction model CM will be, but the more time it will take to complete the work. Normally, the color measurement device itself is a measuring instrument that has measurement variations, so it is preferable to perform measurements multiple times and calculate the statistical values ​​of the measurements to suppress the measurement variations. When the number of measurements is set to multiple times, in the case of spot colorimetry, the same color is measured a specified number of times before moving to the next color, but in the case of scan colorimetry, the row is scanned a specified number of times. This is also a factor that affects the work time.

[0039] The color measurement settings in Fig. 5 may be omitted. Also, at least one of the measurement method and the number of measurements may be changed according to the setting of the relative priority between the work time and the prediction accuracy, which will be described later. In this way, it is possible to perform the measurement of the spectral reflectance with a measurement method and the number of measurements suitable for the relative priority. However, when the set values ​​of the measurement method and the number of measurements are specified by the user as in Fig. 5, it is preferable that the measurement method and the number of measurements are not changed from those set values, regardless of the relative priority between the work time and the prediction accuracy.

[0040] FIG. 6 is an explanatory diagram showing an example of a window W3 for selecting color chart data 62. When the user selects an ink set in this window W3, the attributes of multiple color chart data suitable for that ink set are displayed. In this example, the media name, the surface type of the media, and auxiliary information are displayed as attributes of each color chart data. These attributes are information registered in the color chart information 63 shown in FIG. 2. Also, the window W3 is provided with check boxes CB. The user can select one color chart data by checking one check box CB.

[0041] In the print settings in Fig. 4 described above, Photo_C is selected as the media, and the plurality of color chart data 62 in Fig. 2 does not include any data with Photo_C as the media. Even in this case, auxiliary information indicating that it can be used for Photo_C is displayed in window W3 in Fig. 6, so the user can select one color chart data suitable for Photo_C.

[0042] When Photo_C is selected as the medium in the print settings in Fig. 4, the window W3 in Fig. 6 may be displayed in a state where color chart data that can use Photo_C is automatically selected. In this way, it is possible to automatically present candidates for color chart data that are suitable for the medium selected in the print settings.

[0043] As a list for selecting color chart data 62, a list as shown in Fig. 2 may be used instead of a list as shown in Fig. 6. All of these lists have in common that they include, as setting information suitable for each color chart data 62, print medium information indicating one print medium among a plurality of print media usable in the printing device 200, and ink set information indicating one ink set among a plurality of ink sets usable in the printing device 200. By using such a list, it is possible to select color chart data 62 suitable for a combination of print medium and ink set as the color chart data 62 to be used in creating the color prediction model CM.

[0044] FIG. 7 is an explanatory diagram showing an example of a priority setting window W4a. Using this window W4a, the user can set the relative priority between the work time required to create the color prediction model CM and the prediction accuracy of the color prediction model CM. The relative priority is also simply called "priority". This window W4a includes a slider SL for specifying the relative priority between the work time and the prediction accuracy, and a graph PG showing the relationship between the work time and the prediction accuracy. When the marker MK of the slider SL is moved closer to the "work time" side, the relative priority of the work time increases, and conversely, when the marker MK is moved closer to the "prediction accuracy" side, the relative priority of the prediction accuracy increases. The graph PG shows the predicted values ​​of the prediction accuracy and the work time for the relative priority set by the slider SL. In the example of FIG. 7, the predicted color difference ΔE is used as an index representing the prediction accuracy. The predicted color difference ΔE is the color difference between the L*a*b* value calculated from the predicted spectral reflectance and the L*a*b* value calculated from the measured value of the spectral reflectance. The higher the prediction accuracy, the smaller the predicted color difference ΔE.

[0045] The predicted values ​​of the prediction accuracy and the operation time are values ​​that take into consideration the setting values ​​in the print settings and the color measurement settings. The reason for using "predicted values" is that, for example, when a color prediction model CM is created for an unknown medium, the deviation between the prediction accuracy calculated in advance and the actual prediction accuracy may become large. The same applies to the operation time. Conversely, when a color prediction model CM is created using the same media and ink set as those assumed in the color chart data 62 created in advance, it is assumed that the risk of deviation between the predicted value and the actual value is reduced. In this case, it is preferable to display the predicted value with a unit on the graph PG, since it makes it easier for the user to understand the prediction accuracy and the operation time. It is preferable that the initial setting value of the relative priority between the operation time and the prediction accuracy is a setting value that balances the operation time and the prediction accuracy, that is, the setting value at the center position of the slider SL.

[0046] FIG. 8 is an explanatory diagram showing another example of the priority setting window W4b. This window W4b may be used instead of the window W4a in FIG. 7. The window W4b in FIG. 8 has a radio button RB for specifying whether to give priority to the work time or the prediction accuracy. In the example in FIG. 8, the work time is specified to be given priority, and the predicted values ​​of the work time and the prediction accuracy in this case are displayed with units. Note that when the prediction accuracy is specified to be given priority, the predicted value of the work time becomes larger than that in the example in FIG. 8, and the predicted value of the prediction accuracy becomes better than that in the example in FIG. 8. This window W4b can also be used to specify the relative priority between the work time and the prediction accuracy, similarly to the window W4a in FIG. 7.

[0047] Among the various process settings described with reference to FIGS. 4 to 8, items other than the relative priority setting may be omitted as appropriate.

[0048] When the above various settings are made by the user, the process proceeds to step S20 in Fig. 3, where the print execution unit 52 supplies the selected color chart data 62 to the printing device 200 to print the color chart CC on the printing medium P. As the printing medium P, the medium set in the print settings in Fig. 4 is used.

[0049] FIG. 9 is an explanatory diagram showing the difference between color charts CC printed according to priority settings. In this example, a first color chart CC1 printed when the relative priority of work time is set higher than that of prediction accuracy, and a second color chart CC2 printed when the relative priority of prediction accuracy is set higher than that of work time are illustrated. These color charts CC1 and CC2 are printed using the same single color chart data 62. The entire color chart data 62 is configured as data for printing a plurality of color patches CP on 10 sheets of printing media. The first color chart CC1 is configured to include only the first five sheets of the 10 sheets, and the second color chart CC2 is configured to include all 10 sheets. As in this example, it is preferable to print the color chart CC so that it includes more color patches as the relative priority of prediction accuracy is higher.

[0050] The color patches CP of the color chart CC may be arranged in order of the relative priority of the work time. In this way, color patches suitable for the relative priority of the work time can be easily printed. Specifically, the number of color patches printed when the relative priority of the work time is set high is smaller than the number of color patches printed when the relative priority of the prediction accuracy is set high. In the example of FIG. 9, the color patches CP included in the first five color charts can be considered to have a higher relative priority of the work time than the color patches CP included in the latter five color charts.

[0051] It is also possible to consider that in the color chart data 62, a specific importance is assigned to each color patch CP, and that the color patches CP are arranged in the color chart CC in order of importance. The importance is the degree of contribution to prediction accuracy. In the example of FIG. 9, the importance of the color patch CP arranged in the first color chart CC can be considered to be the highest, and the importance of the color patch CP arranged in the tenth color chart CC can be considered to be the lowest. For example, when creating a color prediction model CM under the condition that the duty limit value of the primary color is 100%, it is preferable that the highest importance is set for the color patch CP printed with duty=100% for each color of CMYK, and that the color patch CP is arranged in the first color chart CC. In this way, the higher the relative priority of the prediction accuracy, the shorter the task of printing the color chart CC so as to include more color patches CP can be performed.

[0052] Note that the difference in the high and low relative priorities may be determined by a specific number of rows in the color chart CC, or by a specific patch position in the color chart CC, instead of by a specific number of sheets of the color chart CC.

[0053] 3, the measurement result acquisition unit 53 causes the colorimetric device 300 to measure the spectral reflectance R(λ) of each color patch CP of the color chart CC and acquires the measurement result. Note that the colorimetric device 300 may be implemented within the printing device 200.

[0054] FIG. 10 is an explanatory diagram showing an example of a printing device 200 including a color measurement device 300. In this example, a plurality of color patches CP of a color chart CC are printed on a printing medium P by a head scanning mechanism 220 of the printing device 200. In the feed direction FD of the printing medium P, the color measurement device 300 is disposed at a position downstream of the head scanning mechanism 220. Therefore, immediately after the color patches CP are printed, it is possible to measure the spectral reflectance R(λ) using the color measurement device 300 in the printing device 200. If the printing device 200 has a configuration capable of connecting to a server via a network, the measured spectral reflectance R(λ) may be transmitted to the server, and a color prediction model creation unit implemented in the server may be used to automatically create a color prediction model CM.

[0055] 3, the learning data creation unit 54 generates learning data including the measurement results of the spectral reflectance R(λ). Each piece of data in the learning data includes an ink amount set and a spectral reflectance R(λ).

[0056] In step S50, the learning unit 55 uses the learning data to learn the color prediction model CM. The color prediction model CM can be, for example, a regression model of multidimensional output configured by a neural network. By executing machine learning using the learning data, such a color prediction model CM becomes an inference model that can predict the spectral reflectance from an arbitrary ink amount set of an ink set.

[0057] As described above, in the above embodiment, it is possible to set the relative priority between the operation time required for processing by the model creation unit 56 and the prediction accuracy of the color prediction model CM. Furthermore, the execution contents of the model creation unit 56 are changed according to the relative priority between the operation time and the prediction accuracy. As a result, it is possible to create a color prediction model taking into account the relative priority between the operation time and the prediction accuracy.

[0058] In the above embodiment, the number of color patches to be printed is changed according to the setting of the relative priority, but other processing contents may be changed. For example, at least one of the measurement method and the number of measurements of the spectral reflectance may be changed according to the setting of the relative priority.

[0059] Other forms: The present disclosure is not limited to the above-mentioned embodiment, and can be realized in various forms without departing from the spirit of the present disclosure. For example, the present disclosure can be realized in the following forms. The technical features in the above-mentioned embodiments corresponding to the technical features in each form described below can be appropriately replaced or combined in order to solve some or all of the problems of the present disclosure, or to achieve some or all of the effects of the present disclosure. Furthermore, if the technical feature is not described as essential in this specification, it can be appropriately deleted.

[0060] (1) According to a first aspect of the present disclosure, there is provided a method for creating a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set. The method includes the steps of (a) accepting a process setting for creating the color prediction model, and (b) creating the color prediction model in accordance with the process setting. The process (b) includes the steps of (b1) printing a color chart with a printing device, (b2) acquiring a measurement result of the spectral reflectance of the color chart, (b3) creating learning data including the measurement result of the spectral reflectance, and (b4) executing learning of the color prediction model using the learning data. The process setting includes a setting for a relative priority between the work time required for the process (b) and the prediction accuracy of the color prediction model, and the implementation content of the process (b) is changed according to the relative priority. According to this method, a color prediction model can be created taking into account the relative priority between work time and prediction accuracy.

[0061] (2) In the above method, the step (b1) may include the step of printing the color chart such that the color chart includes a larger number of color patches as the relative priority of the prediction accuracy becomes higher. According to this method, a color chart can be printed to include a number of color patches appropriate for the set relative priorities.

[0062] (3) In the step (b2) of the above method, at least one of a method for measuring the spectral reflectance of the color chart and the number of measurements may be changed in accordance with the relative priority. According to this method, it is possible to perform the measurement of the spectral reflectance using a measurement method and the number of measurements suited to the relative priority between the operation time and the prediction accuracy.

[0063] (4) In the above method, the color chart may include a plurality of color patches, and the plurality of color patches may be arranged in order of increasing relative priority of the work time. This method allows easy printing of color patches appropriate to the relative priorities of work hours.

[0064] (5) In the above method, the processing setting may include a setting indicating selection of one color chart data to be used for creating the color prediction model from a plurality of color chart data created in advance, and the step (a) may include a step of displaying a list indicating the plurality of color chart data, and the list may include, as setting information suitable for each color chart data, printing medium information indicating one printing medium among a plurality of printing media usable in the printing device, and ink set information indicating one ink set among a plurality of ink sets usable in the printing device. According to this method, it is possible to select color chart data suitable for the combination of printing medium and ink set as the color chart data used to create the color prediction model.

[0065] (6) According to a second aspect of the present disclosure, there is provided a color prediction model creation device that creates a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set. The color prediction model creation device includes a process setting unit that accepts process settings related to the creation of the color prediction model, and a model creation unit that creates the color prediction model according to the process settings. The model creation unit includes a print execution unit that prints a color chart using a printing device, a measurement result acquisition unit that acquires a measurement result of the spectral reflectance of the color chart, a learning data creation unit that creates learning data including the measurement result of the spectral reflectance, and a learning unit that executes learning of the color prediction model using the learning data. The process settings include a setting related to a relative priority between the work time required for processing by the model creation unit and the prediction accuracy of the color prediction model, and the implementation content of the model creation unit is changed according to the relative priority.

[0066] (7) According to a third aspect of the present disclosure, a printing system is provided. The printing system includes a color prediction model creation device that creates a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set, and a printing device. The color prediction model creation device includes a process setting unit that accepts process settings related to the creation of the color prediction model, and a model creation unit that creates the color prediction model according to the process settings. The model creation unit includes a print execution unit that prints a color chart using the printing device, a measurement result acquisition unit that acquires a measurement result of the spectral reflectance of the color chart, a learning data creation unit that creates learning data including the measurement result of the spectral reflectance, and a learning unit that executes learning of the color prediction model using the learning data. The process settings include a setting related to a relative priority between the work time required for processing by the model creation unit and the prediction accuracy of the color prediction model, and the implementation content of the model creation unit is changed according to the relative priority.

[0067] (8) According to a fourth aspect of the present disclosure, there is provided a computer program for creating a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set. The computer program causes a computer to execute (a) a process of accepting a process setting related to the creation of the color prediction model, and (b) a process of creating the color prediction model in accordance with the process setting. The process (b) includes (b1) a process of printing a color chart by a printing device, (b2) a process of acquiring a measurement result of the spectral reflectance of the color chart, (b3) a process of creating learning data including the measurement result of the spectral reflectance, and (b4) a process of executing learning of the color prediction model using the learning data. The process setting includes a setting related to a relative priority between the work time required for the process (b) and the prediction accuracy of the color prediction model, and the implementation content of the process (b) is changed according to the relative priority.

[0068] The present disclosure may be realized in various forms other than an image processing device, a printing system, and a computer program, for example, an image processing method, a non-transitory storage medium on which a computer program is recorded, and the like. [Explanation of symbols]

[0069] 50...CPU, 51...processing setting unit, 52...print execution unit, 53...measurement result acquisition unit, 54...learning data creation unit, 55...learning unit, 56...model creation unit, 60...storage unit, 61...color prediction model creation program, 62...color chart data, 63...color chart information, 70...input / output interface, 100...color prediction model creation device, 200...printing device, 210...ink container, 220...head scanning mechanism, 300...color measurement device, 400...display device, 500...printing system

Claims

1. A method for creating a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set, comprising the steps of: (a) accepting process settings related to the creation of the color prediction model; (b) generating the color prediction model according to the processing settings; Equipped with The step (b) (b1) printing a color chart by a printing device; (b2) obtaining a measurement result of the spectral reflectance of the color chart; (b3) creating learning data including the measurement results of the spectral reflectance; (b4) performing training of the color prediction model using the training data; and Equipped with the process setting includes a setting regarding a relative priority between a work time required for the step (b) and a prediction accuracy of the color prediction model; The method of claim 1, wherein the implementation of step (b) is varied depending on the relative priorities.

2. 2. The method of claim 1 , The method, wherein step (b1) includes printing the color chart to include more color patches the higher the relative priority of the prediction accuracy.

3. 2. The method of claim 1 , The method according to claim 1, wherein in the step (b2), at least one of a method for measuring the spectral reflectance of the color chart and a number of times of measurement is changed depending on the relative priority.

4. 2. The method of claim 1 , The color chart includes a plurality of color patches, The method of claim 1, wherein the plurality of color patches are arranged in order of the relative priority of the work time.

5. 2. The method of claim 1 , the processing setting includes a setting indicating that one color chart data to be used for creating the color prediction model is selected from a plurality of color chart data created in advance, The step (a) includes a step of displaying a list showing the plurality of color chart data, The method, wherein the list includes, as setting information suitable for each color chart data, print medium information indicating one print medium among a plurality of print media usable by the printing device, and ink set information indicating one ink set among a plurality of ink sets usable by the printing device.

6. A color prediction model creation device that creates a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set, comprising: a process setting unit that receives process settings related to the creation of the color prediction model; a model creation unit that creates the color prediction model in accordance with the processing settings; Equipped with The model creation unit is a printing execution unit that prints a color chart using a printing device; a measurement result acquisition unit that acquires a measurement result of the spectral reflectance of the color chart; a learning data creation unit that creates learning data including the measurement results of the spectral reflectance; a learning unit that uses the learning data to learn the color prediction model; Including, the processing setting includes a setting regarding a relative priority between a work time required for processing by the model creation unit and a prediction accuracy of the color prediction model, A color prediction model creation device, wherein the execution content of the model creation unit is changed depending on the relative priority.

7. 1. A printing system comprising: a color prediction model creating device that creates a color prediction model that predicts a spectral reflectance from an ink amount set of a plurality of types of ink that constitute an ink set; A printing device; Equipped with The color prediction model creating device comprises: a process setting unit that receives process settings related to the creation of the color prediction model; a model creation unit that creates the color prediction model in accordance with the processing settings; Equipped with The model creation unit is a printing unit that prints a color chart using the printing device; a measurement result acquisition unit that acquires a measurement result of the spectral reflectance of the color chart; a learning data creation unit that creates learning data including the measurement results of the spectral reflectance; a learning unit that uses the learning data to learn the color prediction model; Including, the processing setting includes a setting regarding a relative priority between a work time required for processing by the model creation unit and a prediction accuracy of the color prediction model, A printing system, wherein the execution content of the model creation unit is changed according to the relative priority.

8. A computer program for creating a color prediction model for predicting a spectral reflectance from an ink amount set of a plurality of types of ink constituting an ink set, comprising: (a) receiving a process setting related to the creation of the color prediction model; (b) creating the color prediction model in accordance with the process settings; Run the following on your computer: The process (b) (b1) printing a color chart by a printing device; (b2) acquiring a measurement result of the spectral reflectance of the color chart; (b3) creating learning data including the measurement results of the spectral reflectance; (b4) a process of executing learning of the color prediction model using the learning data; and Including, the process setting includes a setting regarding a relative priority between a work time required for the process (b) and a prediction accuracy of the color prediction model; The computer program product, wherein the execution content of the process (b) is changed according to the relative priority.

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