Visualized color difference data grading management method and apparatus, device, and medium

Abstract

A visualized color difference data grading management method and apparatus, a device, and a medium. The method comprises: converting respective RGB values of a plurality of peripheral adjacent colors of a standard color to calculate color differences between the peripheral adjacent colors and the standard color, separately; performing color difference grading on the peripheral adjacent colors on the basis of the color differences; and screening for a target color difference grade close to the color difference of a batch color and a target reference color sample having the smallest color difference value from the batch color in the target color difference grade from a plurality of reference color samples respectively corresponding to different color difference grades, and then performing screen display, so that a user performs visual assessment on the basis of an output display result. The effect of providing a reference color sample having a full color difference grade for any color is achieved, the objective of digital color difference visualization is achieved, and the problems of high costs of visual management and insufficient reliability of digital management in color difference management are solved.

Description

Methods, devices, equipment, and media for hierarchical management of visual color difference data Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to a method, apparatus, device, and medium for visual color difference data hierarchical management. Background Technology

[0002] In applications such as textiles, industrial products, printing, and automobiles, color difference management is a crucial component of production management. Currently, there are two relatively mature color difference grading management methods: one is a data-based grading management system, which uses instruments to measure and calculate color difference values ​​and compares them with a set maximum allowable color difference value to determine product qualification. This method is highly dependent on the accuracy of the measuring instruments, and some samples may have measurement data that differs greatly from visual inspection due to unreasonable measurement methods or unsuitable physical structures, seriously affecting the reliability of the data. Furthermore, it requires professionals to set the maximum allowable color difference value. The other method is visual inspection to evaluate color difference. On the one hand, this method requires visual inspectors to directly inspect the samples, and in the current context of international division of labor in the industrial chain, sending samples is time-consuming and costly. On the other hand, color difference grading is difficult to standardize, and developing a large number of physical color difference grading reference standard samples for various colors is too costly and infeasible. Therefore, there are no color difference grading reference standard samples with similar colors available, and the color difference ratings of different personnel, especially those at different times and locations, fluctuate significantly. Summary of the Invention

[0003] In view of this, one of the technical problems solved by the embodiments of this application is to provide a method, apparatus, device and medium for visual color difference data hierarchical management, so as to solve the problems of high cost and low accuracy of color difference evaluation in color difference management.

[0004] A first aspect of this application discloses a method for hierarchical management of visual color difference data, the method comprising:

[0005] Based on CIELAB colorimetric data of the standard color and CIELAB colorimetric data of the batch color, determine the RGB values ​​of the standard color and the batch color, as well as the first color difference between the RGB values ​​of the standard color and the batch color;

[0006] Based on the RGB values ​​of the standard color, determine the RGB values ​​of multiple neighboring colors of the standard color;

[0007] Based on the RGB values ​​of the standard color and the RGB values ​​of multiple neighboring colors, determine the second color difference between the multiple neighboring colors and the standard color;

[0008] According to the preset color difference reference value system classification table, the second color difference between multiple surrounding adjacent colors and the standard color is classified to obtain the reference color set corresponding to each color difference level. The color difference reference value system classification table includes different color difference levels and their corresponding color difference ranges.

[0009] The first color difference is filtered in the color difference reference value system classification table to obtain the target color difference level corresponding to the first color difference. Based on the RGB values ​​of the batch color and the RGB values ​​in the reference color set corresponding to the target color difference level, the third color difference between multiple reference colors and the batch color is determined. The one with the smallest difference is selected as the target reference color.

[0010] The target reference color, standard color, and batch color are controlled for output display processing so that users can make visual evaluations based on the output display results.

[0011] A second aspect of this application discloses a visual color difference data hierarchical management device, the device comprising:

[0012] The color data determination module is used to determine the RGB values ​​of the standard color and the batch color, as well as the first color difference between the RGB values ​​of the standard color and the batch color, based on the CIELAB color measurement data of the standard color and the CIELAB color measurement data of the batch color.

[0013] The adjacent color data determination module is used to determine the RGB values ​​of multiple adjacent colors of a standard color based on the RGB values ​​of the standard color.

[0014] The adjacent color difference value determination module is used to determine the second color difference between the standard color and the standard color based on the RGB value of the standard color and the RGB values ​​of the multiple adjacent colors.

[0015] The reference color set determination module is used to classify the second color difference between multiple surrounding adjacent colors and the standard color according to the preset color difference reference value system classification table, so as to obtain the reference color set corresponding to each color difference level. The color difference reference value system classification table may include different color difference levels and their corresponding color difference ranges.

[0016] The target reference color determination module is used to filter the first color difference in the color difference reference value system classification table to obtain the target color difference level corresponding to the first color difference. Based on the RGB value of the batch color and the RGB value of each reference color in the reference color set corresponding to the target color difference level, it determines the third color difference between multiple reference colors and the batch color, and selects the one with the smallest difference as the target reference color.

[0017] The color sample display output module is used to control the output display processing of target reference color, standard color and batch color, so that users can make visual evaluations based on the output display results.

[0018] A third aspect of this application discloses an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0019] A fourth aspect of this application discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0020] This application has the following advantages: It determines the RGB values ​​of the standard color and the batch color, as well as the first color difference between them, using colorimetric data of the standard color and batch color. Based on the RGB values ​​of the standard color, it determines the RGB values ​​of multiple neighboring colors. Based on the RGB values ​​of the standard color and the multiple neighboring colors, it determines the second color difference between each of the neighboring colors and the standard color, and classifies them into different color difference levels according to classification requirements. It filters the target color difference level corresponding to the batch color based on the first color difference, and selects the reference color with the smallest color difference from the batch color as the target reference color based on the third color difference between the batch sample and the reference color sample set in that color difference level. It then controls the output display processing of the target reference color, the standard color, and the batch color, allowing users to visually evaluate the output display results. This method, which categorizes all neighboring colors of a standard color using a pre-defined color difference reference value system, achieves a hierarchical management approach that combines color difference data digitization and visualization. It enables any color to have its own adjustable, visualized color difference level reference system, allowing for rapid understanding of the visualization effects of different color difference levels of the standard color. This facilitates accurate management of color difference level requirements and accurately converts standard colors, batch colors, and the most suitable target color difference reference colors into visualized data for remote and rapid management by users. This solves the problem of existing color difference evaluation technologies where high efficiency and high reliability are mutually exclusive. Attached Figure Description

[0021] Figure 1 is a flowchart illustrating a visual color difference data hierarchical management method provided in an embodiment of this application;

[0022] Figure 2 is a schematic diagram of the structure of a visual color difference data hierarchical management device provided in one embodiment of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0024] It should be noted that although functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart.

[0025] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0026] According to one embodiment of this application, a method for hierarchical management of visual color difference data is provided, as shown in Figure 1. The method includes steps S101 to S106.

[0027] Step S101: Based on the CIELAB colorimetric data of the standard color and the CIELAB colorimetric data of the batch color, determine the RGB values ​​of the standard color and the batch color, as well as the first color difference between the RGB values ​​of the standard color and the batch color.

[0028] Specifically, if the screen display effects of the standard sample and the batch sample are visually evaluated to be consistent, the RGB value of the standard color can be determined based on the color parameters of the standard color displayed on the screen; the RGB value of the batch color can be determined using the same method.

[0029] Specifically, the initial color difference between the standard color and the batch color can be calculated using a pre-set data conversion algorithm between RGB and CIELAB. Specifically, the color difference is typically assessed using the ΔE parameter in the CIELAB color space.

[0030] Step S102: Based on the RGB value of the standard color, determine the RGB values ​​of each of the multiple neighboring colors of the standard color.

[0031] In this embodiment, the neighboring colors are used to characterize colors that have some continuity with the standard color in both color space and visual perception, and have a small color difference. Specifically, neighboring colors can be obtained by selecting all neighboring RGB values ​​of the standard color in the RGB color space. Since RGB is not a uniform color space, the scale and number of values ​​that can be selected are different in different directions of the RGB color space. For example, when only one or two of the three RGB values ​​change, the color change is large, so the scale of change should be smaller (e.g., ±10), and fewer values ​​should be selected. When all three RGB values ​​change in the same direction (e.g., all increase), the color change is not significant, so a larger change value (e.g., ±15) needs to be selected in that direction, and more neighboring colors need to be selected to determine the RGB values ​​of all neighboring colors.

[0032] Step S103: Determine the second color difference between the standard color and the standard color based on the RGB values ​​of the standard color and the RGB values ​​of the multiple surrounding adjacent colors.

[0033] Specifically, a pre-configured conversion algorithm between RGB and CIELAB can be used to calculate the CIELAB color values ​​of the standard color and multiple surrounding adjacent colors, and then the CIELAB color difference ΔE between the two can be calculated based on the CIELAB color values.

[0034] Step S104: According to the preset color difference reference value system classification table, classify the second color difference between multiple surrounding adjacent colors and the standard color to obtain the reference color set corresponding to each color difference level. The color difference reference value system classification table includes different color difference levels and their corresponding color difference ranges.

[0035] Specifically, the color difference levels included in the color difference reference value system classification table can be set according to preset level increments. For example, starting from a color difference of 0.8, levels can be divided into 0.2 increments, resulting in levels 1.0, 1.2, 1.4, 1.6, 1.8, and 2.0. Alternatively, starting from a color difference of 1.0, levels can be divided into 0.5 increments, resulting in levels 1.5, 2.0, and 2.5. These color difference levels can also be identified using level labels, such as level 1.0 being category A and level 1.4 being category E. More specifically, each level corresponds to a different range of color difference values. For example, assuming the color difference levels include 0.8, 1.2, and 1.6, the color difference value corresponding to level 0.8 is... That is, a color difference of 0.8 level is between 0.7 and 0.9; a color difference of 1.2 level corresponds to a value of That is, a color difference of level 1.2 is between 1.1 and 1.3, and a color difference of level 1.6 corresponds to a value of... That is, the color difference of level 1.6 is between 1.5 and 1.7.

[0036] Step S105: Filter the first color difference in the color difference reference value system classification table to obtain the target color difference level corresponding to the first color difference. Based on the RGB values ​​of the batch color and the RGB values ​​in the reference color set corresponding to the target color difference level, determine the third color difference between multiple reference colors and the batch color, and select the one with the smallest difference as the target reference color.

[0037] Specifically, the color difference level is determined by comparing each color difference with the color difference range of each color difference level in the color difference reference value system classification table. For example, assuming the first color difference between the standard color and the batch color is 1.05, and the color difference level in the color difference reference value system classification table includes levels 1.0, 1.2, and 1.4, then the corresponding color difference level is level 1.0. In this case, the target reference color that is closest to the batch color is selected from the reference color set corresponding to level 1.0.

[0038] Step S106: Control the target reference color, standard color and batch color for output display processing so that the user can make a visual evaluation based on the output display results.

[0039] This application embodiment determines the RGB values ​​of the standard color and the batch color, as well as the first color difference between the standard color and the batch color, using colorimetric data of the standard color and batch color. Based on the RGB values ​​of the standard color, the RGB values ​​of multiple neighboring colors are determined. Based on the RGB values ​​of the standard color and the multiple neighboring colors, the second color difference between each of the neighboring colors and the standard color is determined, and they are classified into different color difference levels according to classification requirements. The target color difference level corresponding to the batch color is selected according to the first color difference. Based on the third color difference between the batch sample and the reference color sample set in the color difference level, the reference color with the smallest difference from the batch color is selected as the target reference color. The target reference color, standard color, and batch color are controlled. The secondary color is processed for output display, allowing users to visually evaluate based on the output results. This method, which categorizes all neighboring colors of the standard color using a preset color difference reference value system, achieves a hierarchical management approach that combines color difference data digitization and visualization. It enables any color to have an adjustable visual color difference level reference system, allowing for quick understanding of the different color difference levels of the standard color and accurate management of color difference level requirements. It also accurately converts the standard color, batch color, and the most suitable target color difference reference color into visual data for users to manage remotely and quickly, solving the problem of the incompatibility between high efficiency and high reliability in existing color difference evaluation methods.

[0040] In some embodiments, step S101 further includes:

[0041] Step S1011 (not shown in the figure): Obtain CIELAB colorimetric data for the standard color and CIELAB colorimetric data for the batch color;

[0042] Step S1012 (not shown in the figure): According to the preset CIELAB color measurement data and RGB value conversion algorithm, the CIELAB color measurement data of the standard color and the CIELAB color measurement data of the batch color are converted into the format respectively to obtain the RGB standard color and the RGB batch color of the screen display.

[0043] Step S1013 (not shown in the figure): If the standard color is visually consistent with the RGB standard color displayed on the screen and the batch color is visually consistent with the RGB batch color displayed on the screen, then determine the RGB value of the standard color and the RGB value of the batch color based on the RGB standard color displayed on the screen and the RGB batch color displayed on the screen.

[0044] In this embodiment, CIELAB colorimetric data is used to characterize color values ​​measured using the color space of the colorimetric device. Specifically, the colorimetric device is connected to a terminal, enabling the terminal to acquire the colorimetric data collected by the device. Specifically, CIELAB colorimetric data for standard colors and batch colors can be acquired using a colorimeter (i.e., the colorimetric device, typically using the CIELAB color space) connected to the terminal device. In application, a preset sampling frequency can be set to acquire CIELAB colorimetric data for standard colors and batch colors, or the CIELAB colorimetric data for standard colors and batch colors can be obtained after sending a data acquisition command to the colorimeter.

[0045] Since the colorimeter uses the CIELAB color space, the L, a, b, and other color values ​​from CIELAB in step S101 are processed using a pre-configured CIELAB-RGB color space conversion algorithm. This yields the RGB values ​​for the standard color and the batch color, which are then output and displayed. This allows users to evaluate the display effect on the screen against the actual standard and batch colors to determine their consistency. In practice, a third-party color space conversion algorithm can also be called using a preset interface to complete the conversion.

[0046] When applying this method, the first color difference (CIEΔE) between the standard color and the batch color is not calculated directly using CIELAB color measurement data. This is because the data must be consistent with the visualization effect. Therefore, RGB values ​​are used as the standard, and the data must be converted back to CIELAB based on the RGB values ​​before calculating the first color difference CIEΔE between the standard color and the batch color. This introduces a small error to the data, but it also avoids the large errors caused by the CIELAB color measurement data itself in situations such as s1014, s1015, and S1016 described below. Thus, the visualization processes described below (s1014, s1015, and S1016) are used to improve the consistency between the data and visual inspection, thereby increasing the reliability of the digitization.

[0047] This application embodiment displays standard color and batch color on the screen by converting RGB values, allowing users to visually evaluate whether the screen display effect is consistent with the actual object, thus avoiding the impact of inconsistent displayed colors with the sample on subsequent visual color difference data classification management.

[0048] In some embodiments, step S101 further includes:

[0049] Step S1014 (not shown in the figure): If the standard color is visually inconsistent with the RGB standard color displayed on the screen, or the batch color is inconsistent with the RGB batch color displayed on the screen, adjust the measurement conditions or conversion algorithm, and re-execute the steps of obtaining CIELAB colorimetric data of the standard color and CIELAB colorimetric data of the batch color. According to the preset conversion algorithm between CIELAB colorimetric data and RGB values, convert the CIELAB colorimetric data of the standard color and CIELAB colorimetric data of the batch color to obtain the RGB standard color and RGB batch color displayed on the screen, until the standard color is consistent with the RGB standard color displayed on the screen and the batch color is consistent with the RGB batch color displayed on the screen.

[0050] Specifically, the measurement conditions include the measurement aperture, measurement direction, and physical state of the measured object such as light transmittance. After adjusting the measurement conditions, the newly acquired data is converted back into RGB values ​​for display until the visually inspected screen display effect is consistent with the actual sample.

[0051] Specifically, multiple conversion algorithms between CIELAB color measurement data and RGB values ​​can be provided in advance, and one of them can be used as the default algorithm. When the standard color is inconsistent with the RGB standard color displayed on the screen, or the batch color is inconsistent with the RGB batch color displayed on the screen, other conversion algorithms can be set as the default algorithm to re-execute steps S1011 and S1012 to obtain the RGB values ​​of the standard color and the batch color that meet the conditions of step S1013.

[0052] In some embodiments, step S101 further includes:

[0053] Step S1015 (not shown in the figure): If the standard color is visually inconsistent with the RGB standard color displayed on the screen, then visually select the RGB value of the reference color that is closest to the standard color from all surrounding RGB reference colors as the RGB value of the standard color.

[0054] Step S1016 (not shown in the figure): If the batch color is inconsistent with the RGB batch color displayed on the screen, visually select the RGB value of the reference color that is closest to the batch color from all surrounding RGB reference colors as the RGB value of the batch color.

[0055] Specifically, if the standard color is inconsistent with the RGB standard color displayed on the screen, or if the batch color is inconsistent with the RGB batch color displayed on the screen, the surrounding RGB reference color can be obtained by adjusting the RGB parameters of the displayed color on the screen and then displaying the output. This allows the user to select the closest color by visual inspection, and the RGB value of the closest color is used as the RGB value of the standard color or the RGB value of the batch color.

[0056] In some embodiments, step S102 further includes:

[0057] Based on the preset range of variation values ​​for the three components R, G, and B, the combinations of R, G, and B components are arranged, and the RGB values ​​of the standard color are adjusted according to the combinations of R, G, and B components to obtain the RGB values ​​of multiple neighboring colors of the standard color.

[0058] Specifically, the combinations of R, G, and B components can be arranged according to their variation ranges. More specifically, the variation ranges of the three components can be the same or different. For example, all combinations where R, G, and B are within ±a. In application, at least one of the three components (R, G, and B) can be adjusted before combination. For example, one parameter of the standard color's R, G, and B can be adjusted to (a+1) to (a+b) or -(a+1) to -(a+b), while the other two values ​​are taken within a small range of ±c based on this adjusted value. In application, the values ​​of a, b, and c can be determined based on the color difference range. For example, assuming the color difference range CIEΔE is less than 3, the value of a can be referenced to 10, the value of B to 5, and the value of C to 5, etc., and so on.

[0059] In some embodiments, step S104 further includes:

[0060] The standard color and the reference color set corresponding to each color difference level are displayed as images, so that users can visually evaluate the visualization effect of different digital color difference levels by visually evaluating the reference color set corresponding to each color difference level, and analyze or adjust the rationality of the color difference reference value system classification table.

[0061] Specifically, an interactive interface can be provided to obtain the user's visual evaluation results of the reference color sets corresponding to different color difference levels in the displayed output. In application, this interactive interface can provide selection controls for confirming adjustments and selection controls for further adjustment, allowing the user to make their choices.

[0062] In some embodiments, after step S104, the method further includes:

[0063] If an adjustment instruction for the color difference reference value system classification table is detected, the color difference reference value system classification table is updated according to the adjustment instruction, and then the steps of classifying the second color difference between multiple surrounding adjacent colors and the standard color according to the preset color difference reference value system classification table are performed to obtain the reference color set corresponding to each color difference level.

[0064] Specifically, if the user's visual assessment of the reference color sets corresponding to different color difference levels in the display output is reasonable, then there is no need to adjust the color difference reference value system classification table; otherwise, the user can determine whether to adjust it based on their selected adjustment scheme. For example, if the visual assessment result is an update instruction for the color difference level, then the color difference level and its corresponding color difference range are updated according to the adjustment instruction. Alternatively, after step S106 is completed and the visual assessment result from the user is received, corresponding processing can be performed. For example, if the visual assessment result is an update instruction for the color difference level, then the color difference level and its corresponding color difference range are updated according to the adjustment instruction.

[0065] For example, suppose the preset color difference levels and their corresponding color difference ranges are shown in Table 1 below. After displaying multiple reference color samples corresponding to each color difference level, and then displaying the standard color and the multiple reference color samples corresponding to each color difference level, if the user's visual evaluation result indicates that the color difference level needs adjustment, then after receiving the adjustment information input by the user, an update instruction is generated. After adjusting according to the update instruction, the color difference levels shown in Table 2 are obtained. Table 2 adds color difference levels 4+ and 4- to Table 1.

[0066] Table 1

[0067]

[0068] Table 2

[0069]

[0070] This application embodiment achieves the effect of customizing and expanding the color difference levels by updating the instructions, increasing the number of reference color samples for each color difference level, thereby enriching the color difference levels and the number and color gamut of their reference color samples. It solves the problem in related technologies that the physical color difference grading is too few and cannot be adjusted, and provides a data foundation for improving the accuracy of color difference assessment.

[0071] In some embodiments, step S105, which involves filtering the first color difference in a color difference reference value system classification table to obtain the target color difference level corresponding to the first color difference, further includes:

[0072] Calculate the difference between the first color difference and the upper and lower limits of the color difference range of each color difference level, and determine the first predetermined number of color difference levels with the smallest difference as the target color difference level.

[0073] Specifically, the calculated differences can be sorted in ascending order, and the top-ranked color difference levels (a predetermined number of each) can be used as the target color difference levels. In practice, the number of target color difference levels is typically set to 1-2, with 1 being optimal, meaning the color difference level with the smallest difference is selected as the target color difference level.

[0074] Specifically, step S105, which involves determining the third color difference between multiple reference colors and the batch color based on the RGB values ​​of the batch color and the RGB values ​​of each reference color in the reference color set corresponding to the target color difference level, and then selecting the reference color with the smallest difference as the target reference color, further includes:

[0075] Determine the batch color CIELAB value converted from the RGB values ​​of the batch color, and the reference color CIELAB value converted from the RGB values ​​of each reference color in the reference color set corresponding to the target color difference level;

[0076] Calculate the difference between the CIELAB value of the batch color and the CIELAB value of each reference color in the reference color set corresponding to the target color difference level, and obtain the third color difference between the multiple reference colors and the batch color;

[0077] The target reference color is obtained by filtering based on the third color difference between multiple reference colors and the batch color.

[0078] Specifically, multiple reference colors can be sorted in ascending order with the third color difference of the batch color, and a predetermined number of reference colors at the top of the sort can be used as target reference colors. In application, one or several colors with the smallest color difference are generally selected as target reference colors.

[0079] CIELAB data consists of color values ​​based on the CIELAB color space, including lightness (L) and two chromaticity indices, a and b. The color difference ΔE is a comprehensive value that depends on the coordinate values ​​of the differences in L, a, and b between two colors. The difference ΔE between the chromaticity coordinate values ​​(L*sample, a*sample, b*sample) and (L*standard, a*standard, b*standard) of two colors in the CIELAB color space is calculated using the following formula: ΔE = [(ΔL*)² + (Δa*)² + (Δb*)²]¹ / ². Where: ΔL* = L*sample - L*standard, representing the lightness difference; a positive ΔL* indicates a lighter sample color, while a negative Δa* indicates a darker sample color. Δa* = a*sample - a*standard, representing the red / green difference; a positive Δa* indicates a reddish sample color, while a negative Δa* indicates a greenish sample color. Δb* = b*sample - b*standard, representing the yellow / blue difference; a positive Δb* indicates a yellowish sample color, while a negative Δb* indicates a bluish sample color. When using ΔE to evaluate color difference, a smaller ΔE indicates a closer similarity between the sample and the standard color, and vice versa. Therefore, color bias can be determined based on ΔL*, Δa*, and Δb*. Thus, the target reference color with the smallest color difference from the batch color will visually closely resemble the batch color, and a visual color difference rating system composed of this target reference color and the standard color helps to accurately determine the color difference level of the batch color.

[0080] One embodiment of this application provides a visual color difference data hierarchical management device, as shown in FIG2. The device 20 includes: a color data determination module 201, a neighboring color data determination module 202, a neighboring color difference value determination module 203, a reference color set determination module 204, a target reference color determination module 205, and a color sample display output module 206.

[0081] Color data determination module 201 is used to determine the RGB values ​​of the standard color and the batch color, as well as the first color difference between the RGB values ​​of the standard color and the batch color, based on the CIELAB color measurement data of the standard color and the CIELAB color measurement data of the batch color.

[0082] The adjacent color data determination module 202 is used to determine the RGB values ​​of multiple adjacent colors of the standard color based on the RGB values ​​of the standard color.

[0083] The adjacent color difference value determination module 203 is used to determine the second color difference between the multiple adjacent colors and the standard color based on the RGB value of the standard color and the RGB values ​​of the multiple adjacent colors.

[0084] The reference color set determination module 204 is used to classify the second color difference between multiple surrounding adjacent colors and the standard color according to the preset color difference reference value system classification table, so as to obtain the reference color set corresponding to each color difference level. The color difference reference value system classification table includes different color difference levels and their corresponding color difference ranges.

[0085] The target reference color determination module 205 is used to filter the first color difference in the color difference reference value system classification table to obtain the target color difference level corresponding to the first color difference, and to determine the third color difference between multiple reference colors and the batch color based on the RGB value of the batch color and the RGB value of each reference color in the reference color set corresponding to the target color difference level, and to select the one with the smallest difference as the target reference color.

[0086] The color sample display output module 206 is used to control the output display processing of the target reference color, standard color and batch color, so that the user can make a visual evaluation based on the output display results.

[0087] This application embodiment determines the RGB values ​​of the standard color and the batch color using colorimetric data of the standard color and batch color, as well as the first color difference between the RGB values ​​of the standard color and the batch color. Based on the RGB values ​​of the standard color, the RGB values ​​of multiple neighboring colors are determined. Based on the RGB values ​​of the standard color and the multiple neighboring colors, the second color difference between the multiple neighboring colors and the standard color is determined, and they are divided into different color difference levels according to classification requirements. The target color difference level corresponding to the batch color is selected according to the first color difference. Based on the third color difference between the batch sample and the reference color sample set in the color difference level, the reference color with the smallest difference from the batch color is selected as the target reference color. The target reference color and the standard color are then controlled. The standard color and batch color are output and displayed so that users can visually evaluate based on the output results. This method of classifying all neighboring colors of the standard color through a preset color difference reference value system classification table realizes a hierarchical management method that combines color difference data with visualization. It aims to enable any color to have an adjustable visual color difference level reference system, thereby quickly understanding the visualization effect of different color difference levels of the standard color, achieving accurate management of color difference level requirements, and accurately converting the standard color, batch color, and the most applicable target color difference reference color into visual data for users to remotely and quickly manage. This solves the problem of the incompatibility between high efficiency and high reliability in existing color difference evaluation technologies.

[0088] Furthermore, the color data determination module includes:

[0089] The colorimetric data acquisition submodule is used to acquire CIELAB colorimetric data for standard colors and batch colors;

[0090] The RGB value conversion and display submodule is used to convert the CIELAB color measurement data of the standard color and the CIELAB color measurement data of the batch color according to the preset CIELAB color measurement data and RGB value conversion algorithm, respectively, to obtain the RGB standard color and the RGB batch color displayed on the screen.

[0091] The first data determination submodule is used to determine the RGB values ​​of the standard color and the batch color based on the RGB standard color and the RGB batch color displayed on the screen if the standard color is visually consistent with the RGB standard color displayed on the screen and the batch color is visually consistent with the RGB batch color displayed on the screen.

[0092] Furthermore, the color data determination module also includes:

[0093] The second data determination submodule is used to adjust the measurement conditions or conversion algorithm if the standard color is visually inconsistent with the RGB standard color displayed on the screen, or if the batch color is inconsistent with the RGB batch color displayed on the screen. It then re-executes the steps of obtaining CIELAB colorimetric data for the standard color and the batch color, and converts the CIELAB colorimetric data for the standard color and the batch color according to the preset conversion algorithm between CIELAB colorimetric data and RGB values, to obtain the RGB standard color and the RGB batch color displayed on the screen, until the standard color is consistent with the RGB standard color displayed on the screen and the batch color is consistent with the RGB batch color displayed on the screen.

[0094] Furthermore, the color data determination module also includes:

[0095] The first adjustment processing unit is used to visually select the RGB value of the reference color that is closest to the standard color from all surrounding RGB reference colors if the standard color is visually inconsistent with the RGB standard color displayed on the screen.

[0096] The second adjustment processing unit is used to visually select the RGB value of the reference color that is closest to the batch color from all surrounding RGB reference colors if the batch color is visually inconsistent with the RGB batch color displayed on the screen.

[0097] Furthermore, the neighboring color data determination module includes:

[0098] The adjustment strategy determination and processing module is used to arrange the combination of R, G, and B components based on the preset range of R, G, and B component variation values, and adjust the RGB value of the standard color according to the combination of R, G, and B components to obtain the RGB values ​​of multiple surrounding neighboring colors of the standard color.

[0099] Furthermore, the reference color set determination module also includes:

[0100] The reference color evaluation submodule is used to display and output images of the standard color and the reference color sets corresponding to different color difference levels. This allows users to visually evaluate the rationality of the color difference reference value system classification table by visually assessing the reference color sets corresponding to different color difference levels.

[0101] Furthermore, the reference color set determination module also includes:

[0102] The classification system adjustment submodule is used to update the color difference reference value system classification table according to the adjustment instruction if an adjustment instruction for the color difference reference value system classification table is detected, and then perform the following steps: classify the second color difference between multiple surrounding neighboring colors and the standard color according to the preset color difference reference value system classification table, and obtain the reference color set corresponding to each color difference level.

[0103] Furthermore, the target reference color determination module includes:

[0104] The difference calculation submodule is used to calculate the difference between the first color difference and the upper and lower limits of the color difference range of each color difference level, and to determine the target color difference level.

[0105] The apparatus described in this embodiment can execute the method shown in the embodiments of this application, and its implementation principle is similar, so it will not be described again here.

[0106] Another embodiment of this application provides a terminal, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method.

[0107] Specifically, the processor can be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0108] Specifically, the processor connects to the memory via a bus, which may include a path for transmitting information. The bus can be a PCI bus or an EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc.

[0109] The memory may be ROM or other types of static storage devices that can store static information and instructions, RAM or other types of dynamic storage devices that can store information and instructions, or EEPROM, CD-ROM or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.

[0110] Optionally, the memory stores the code of a computer program that executes the scheme of this application, and the execution is controlled by a processor. The processor executes the application code stored in the memory to implement the operation of the device provided in the embodiment shown in FIG2.

[0111] Another embodiment of this application provides a computer-readable storage medium storing computer-executable instructions for performing the method shown in FIG1 above.

[0112] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0113] Those skilled in the art will understand that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0114] The above is a detailed description of the preferred embodiments of this application. However, this application is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A method for hierarchical management of visual color difference data, characterized in that, The method includes: Based on CIELAB colorimetric data of the standard color and CIELAB colorimetric data of the batch color, the RGB values ​​of the standard color and the batch color, as well as the first color difference between the RGB values ​​of the standard color and the batch color are determined. Based on the RGB value of the standard color, determine the RGB values ​​of each of the multiple surrounding neighboring colors of the standard color; Based on the RGB value of the standard color and the RGB values ​​of each of the multiple surrounding neighboring colors, a second color difference between each of the multiple surrounding neighboring colors and the standard color is determined; According to the preset color difference reference value system classification table, the second color difference between multiple surrounding adjacent colors and the standard color is classified to obtain the reference color set corresponding to each color difference level. The color difference reference value system classification table may include different color difference levels and their corresponding color difference ranges. The first color difference is filtered in the color difference reference value system classification table to obtain the target color difference level corresponding to the first color difference. Based on the RGB value of the batch color and the RGB value of each reference color in the reference color set corresponding to the target color difference level, the third color difference between the multiple reference colors and the batch color is determined, and the one with the smallest difference is selected as the target reference color. The target reference color, the standard color, and the batch color are controlled to perform output display processing so that the user can make a visual evaluation based on the output display results.

2. The method according to claim 1, characterized in that, The determination of the RGB values ​​of the standard color and the batch color based on CIELAB colorimetric data of the standard color and CIELAB colorimetric data of the batch color includes: Obtain CIELAB colorimetric data for standard colors and batch colors; The CIELAB color measurement data of the standard color and the CIELAB color measurement data of the batch color are converted into formats according to the preset CIELAB color measurement data and RGB value conversion algorithm, respectively, to obtain the screen display RGB standard color and the screen display RGB batch color. If the standard color is visually consistent with the RGB standard color displayed on the screen, and the batch color is visually consistent with the RGB batch color displayed on the screen, then the RGB values ​​of the standard color and the batch color are determined based on the RGB standard color displayed on the screen and the RGB batch color displayed on the screen.

3. The method according to claim 2, characterized in that, The determination of the RGB values ​​of the standard color and the batch color based on CIELAB colorimetric data of the standard color and CIELAB colorimetric data of the batch color also includes: If the standard color is visually inconsistent with the RGB standard color displayed on the screen, or if the batch color is visually inconsistent with the RGB batch color displayed on the screen, then adjust the measurement conditions or the conversion algorithm, and re-execute the steps of obtaining CIELAB colorimetric data of the standard color and CIELAB colorimetric data of the batch color. The CIELAB colorimetric data of the standard color and the CIELAB colorimetric data of the batch color are then converted according to a preset conversion algorithm between CIELAB colorimetric data and RGB values ​​to obtain the RGB standard color and the RGB batch color displayed on the screen, until the standard color is consistent with the RGB standard color displayed on the screen and the batch color is consistent with the RGB batch color displayed on the screen.

4. The method according to claim 2, characterized in that, The determination of the RGB values ​​of the standard color and the batch color based on CIELAB colorimetric data of the standard color and CIELAB colorimetric data of the batch color includes: If the standard color is visually inconsistent with the RGB standard color displayed on the screen, then the RGB value of the reference color that is closest to the standard color is visually selected from all surrounding RGB reference colors as the RGB value of the standard color. If the batch color is visually inconsistent with the RGB batch color displayed on the screen, then the RGB value of the reference color that is closest to the batch color is selected visually from all surrounding RGB reference colors as the RGB value of the batch color.

5. The method according to claim 1, characterized in that, The step of determining the RGB values ​​of multiple neighboring colors of the standard color based on the RGB values ​​of the standard color includes: Based on the preset range of variation values ​​for the three components R, G, and B, the combinations of R, G, and B components are arranged, and the RGB values ​​of the standard color are adjusted according to the combinations of R, G, and B components to obtain the respective RGB values ​​of multiple neighboring colors of the standard color.

6. The method according to claim 1, characterized in that, Before the step of classifying the second color difference between multiple neighboring colors and the standard color according to the preset color difference reference value system classification table to obtain the reference color set corresponding to each color difference level, the method further includes: The standard color and the reference color set corresponding to each color difference level are displayed and output as images, so that users can analyze or adjust the rationality of the color difference reference value system classification table by visually evaluating the reference color set corresponding to each color difference level displayed and output. If an adjustment instruction for the color difference reference value system classification table is detected, then the color difference reference value system classification table is updated according to the adjustment instruction, and then the step of classifying the second color difference between multiple surrounding neighboring colors and the standard color according to the preset color difference reference value system classification table is executed to obtain the reference color set corresponding to each color difference level.

7. The method according to claim 1, characterized in that, The step of filtering the first color difference in the color difference reference value system classification table to obtain the target color difference level corresponding to the first color difference includes: Calculate the difference between the first color difference and the upper and lower limits of the color difference range of each color difference level, and determine the first predetermined number of color difference levels with the smallest difference as the target color difference level.

8. A visual color difference data hierarchical management device, characterized in that, include: The color data determination module is used to determine the RGB values ​​of the standard color and the batch color, as well as the first color difference between the RGB values ​​of the standard color and the batch color, based on the CIELAB color measurement data of the standard color and the CIELAB color measurement data of the batch color. The adjacent color data determination module is used to determine the RGB values ​​of multiple adjacent colors of the standard color based on the RGB values ​​of the standard color. The adjacent color difference value determination module is used to determine the second color difference between the multiple adjacent colors and the standard color based on the RGB value of the standard color and the RGB values ​​of the multiple adjacent colors. The reference color set determination module is used to classify the second color difference between multiple surrounding neighboring colors and the standard color according to a preset color difference reference value system classification table, so as to obtain the reference color set corresponding to each color difference level. The color difference reference value system classification table may include different color difference levels and their corresponding color difference ranges. The target reference color determination module is used to filter the first color difference in the color difference reference value system classification table to obtain the target color difference level corresponding to the first color difference, and to determine the third color difference between the multiple reference colors and the batch color according to the RGB value of the batch color and the RGB value of each reference color in the reference color set corresponding to the target color difference level, and to select the one with the smallest difference as the target reference color. The color sample display output module is used to control the output display processing of the target reference color, the standard color, and the batch color, so that the user can make a visual evaluation based on the output display results.

9. An electronic device, characterized in that, The device includes a processor and a memory, the memory storing computer-readable instructions, and the processor being configured to execute the computer-readable instructions, wherein the computer-readable instructions, when executed, perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions for performing the method according to any one of claims 1 to 7.

Images