Visual interface icon color matching method and device based on psychophysics human body perception experiment and electronic equipment

Abstract

The invention discloses a visual interface icon color matching method and device based on a psychophysics human body perception experiment and electronic equipment. The method comprises the following steps: acquiring an initial color matching image set, classifying subjects according to a deterministic classification rule, acquiring response time of each subject in a subject group to each color matching image under a preset test condition, and preprocessing original test response time to obtain corresponding test response time; according to the method, variance analysis is carried out on the influence of the preset variable on the response time of the subject group, the significance of the preset variable in the statistical significance is deduced, and the color matching scheme is recommended based on the significance statistical deduction conclusion, so that the problems of subjectivity and one-sidedness in the prior art can be solved, the user experience is improved, and the identifiability and readability of visual interface icons are improved.

Description

Technical Field

[0001] The present application relates to computer vision design, in particular to the field of human-computer interaction interface design, and specifically to a method, device and electronic device for color matching of visual interface icons based on psychophysical human perception experiments. Background Art

[0002] The concept of visual interface can cover at least two aspects. The first aspect refers to the interactive interface presented to users through graphics, text, icons and other visual elements in electronic devices or computer systems. It is the main way for users to exchange information and operate devices. The second aspect refers to the necessary design required to highlight the visual impact of the subject or logo in public places such as clothing, home decoration, stage design, exhibition halls, airports, stations, etc., whether in life or work. In order to ensure the recognizability of icons, it is necessary to develop an icon color matching method based on human perception data to determine the color selection of icons and the matching of background colors based on objective evaluation and quantitative analysis of human perception data of different color backgrounds and icon colors. However, the current icon color matching method is mainly based on the designer's personal experience, aesthetic concepts or scattered human perception research, which leads to the subjective and one-sided problems of this method. Summary of the invention

[0003] In order to solve the above problems, the embodiment of the present application provides a visual interface icon color matching method based on psychophysical human perception experimental data, which improves the reliability of the human-computer interaction visual interface icon color matching design quality evaluation.

[0004] In a first aspect, the present invention provides a method for color matching of visual interface icons based on a psychophysical human perception experiment, the method comprising the following steps:

[0005] S1. Obtain an initial color matching image set, wherein each color matching image set is a set of different images that take values ​​from a preset background color set as the background color of the image and take values ​​from a preset foreground color set as the icon color, i.e., the foreground color; the background color set is a set of values ​​of the image background color; and the foreground color set is a set of color values ​​of the image icon content.

[0006] S2, classifying the subjects according to deterministic classification rules, wherein the deterministic classification rules may be one or a combination of several classification rules such as age, gender, normal vision, abnormal vision, etc.

[0007] S3, obtaining the reaction time of each subject in the subject group to each color matching image under preset test conditions, wherein the preset test conditions are that except for the controllable random changes in the values ​​of the background color variable and the foreground color variable, other controllable test conditions such as symbol content, symbol shape, symbol size, symbol movement, ambient light illumination, light source color temperature, display luminous intensity and other related variables affecting the reaction time are determined to remain unchanged; the subject group is a subject group with no less than 5 of the same type of subjects as the same preset test conditions; the reaction time is the time taken by the subject to complete the test task of identifying the symbol content in each color matching image.

[0008] S4, preprocessing the original test reaction time to obtain the corresponding test reaction time of the subject group, that is, first cleaning the original test data: based on the original test reaction time of the subject group, delete the abnormal data exceeding 3 times the standard deviation in the original test reaction time of each member of the same target test image, and then take the corresponding reaction time of the adjacent tester closest to the mean of the test data of the subject group to fill the missing data; then calculate the reaction time of the subject group to the corresponding color matching image under the preset test conditions: based on the test reaction time of each member of the subject group after the cleaning data, the corresponding reaction time data of all subjects in the subject group under the preset test conditions are averaged as the reaction time of the corresponding color matching image under the corresponding test conditions.

[0009] S5, perform variance analysis on the effect of preset variables on the reaction time of the subject group and infer its statistical significance, that is, classify and organize the corresponding reaction times based on the background color variables corresponding to the background color set, the foreground color variables corresponding to the foreground color value set, and the test group variables of different types of test user groups, and perform two-way variance analysis on the reaction time corresponding to the variables consisting of the set of all values ​​of any two variables or their subsets, and then, based on the variance analysis results, infer the significance of the effect of the corresponding values ​​of the variables on the reaction time.

[0010] S6, recommending a color scheme based on the significant statistical inference conclusion, specifically, for a subset of variable values ​​that have a significant effect on the reaction time, recommending a color scheme corresponding to the minimum reaction time for the variable values; and for a subset of variables that have no significant effect on the reaction time, recommending a corresponding color scheme for the variable subset.

[0011] In a second aspect, the present application provides a visual interface icon color matching device based on psychophysical human perception experimental data, the device comprising:

[0012] The original color image acquisition module is used to obtain an initial color image set, wherein each color image set is a set of different images that take values ​​from a preset background color set as the background color of the image and take values ​​from a preset foreground color set as the symbol color, i.e., the foreground color; the background color set is a set of values ​​of the image background color; and the foreground color set is a set of color values ​​of the image symbol content.

[0013] The qualified subject screening module is used to classify the subjects according to deterministic classification rules, wherein the deterministic classification rules can be one or a combination of several classification rules such as age, gender, normal vision, abnormal vision, etc.

[0014] The reaction time acquisition module is used to obtain the reaction time of each subject in the subject group to each color matching image under preset test conditions, wherein the preset test conditions are that except for the controllable random changes in the values ​​of the background color variable and the foreground color variable, other controllable test conditions such as the symbol content, symbol shape, symbol size, symbol movement, ambient light illumination, light source color temperature, display luminous intensity and other related variables affecting the reaction time are determined; the subject group is a subject group with no less than 5 of the same type of subjects as the same preset test conditions; the reaction time is the time taken by the subject to complete the test task of identifying the symbol content in each color matching image.

[0015] The data preprocessing module is used to preprocess the original test reaction time to obtain the corresponding test reaction time of the subject group, that is, first clean the original test data: based on the original test reaction time of the subject group, delete the abnormal data that exceeds 3 times the standard deviation in the original test reaction time of each member of the same target test image, and then take the corresponding reaction time of the adjacent tester closest to the mean of the test data of the subject group to fill the missing data; then calculate the reaction time of the subject group to the corresponding color matching image under the preset test conditions: based on the test reaction time of each member of the subject group after the cleaning data, the corresponding reaction time data of all subjects in the subject group under the preset test conditions are averaged as the reaction time of the corresponding color matching image under the corresponding test conditions.

[0016] The statistical discrimination module is used to perform variance analysis on the influence of preset variables on the reaction time of the subject group and infer its statistical significance, that is, based on the background color variables corresponding to the background color set, the foreground color variables corresponding to the foreground color value set, and the test group variables of different types of test user groups, the corresponding reaction times are classified and sorted, and a two-way variance analysis is performed on the reaction time corresponding to the variables consisting of all value sets or subsets of any two variables, and then, based on the variance analysis results, the significance of the influence of the corresponding value conditions of the variables on the reaction time is inferred.

[0017] The color recommendation module is used to recommend color schemes based on the significant statistical inference conclusions. Specifically, for a subset of variable values ​​that have a significant impact on reaction time, the color scheme corresponding to the minimum reaction time is recommended; for a subset of variables that have no significant impact on reaction time, the corresponding color scheme of the variable subset is recommended.

[0018] In a third aspect, an embodiment of the present application provides an electronic device, which may include: a display unit, a processor and a memory; wherein the display unit may be a touch panel, a computer display, a projection screen, VR glasses or XR glasses and other icon display panels or devices, and the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method steps of the above-mentioned first aspect.

[0019] The beneficial effects brought about by the technical solutions provided by some embodiments of the present application include at least:

[0020] In an embodiment of the present application, by obtaining an initial set of color matching images, classifying subjects according to deterministic classification rules, obtaining the reaction time of each subject in the subject group to each color matching image under preset test conditions, preprocessing the original test reaction time to obtain the corresponding test reaction time, performing variance analysis on the effect of preset variables on the reaction time of the subject group and inferring its statistical significance, and recommending a color matching scheme based on the statistical inference conclusion of the significance, it is possible to overcome the problems of subjectivity and one-sidedness in the prior art, improve user experience, and improve the recognizability and readability of visual interface icons. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 A schematic diagram of the architecture of a visual interface icon color matching system based on a psychophysical human perception experiment provided in an embodiment of the present application.

[0023] Figure 2 A flowchart of a method for color matching visual interface icons based on a psychophysical human perception experiment is provided in an embodiment of the present application.

[0024] Figure 3 The Landau ring image and screen operation diagram used in the experiment provided in the embodiment of the present application.

[0025] Figure 4A schematic diagram of the radar chart screen operation image and its color matching used in the experiment provided in the embodiment of the present application.

[0026] Figure 5 Schematic diagram of the experimental scenario provided for the embodiments of the present application.

[0027] Figure 6 Spectral distribution curves of LED lamps with different illumination provided in the embodiments of the present application.

[0028] Figure 7 A schematic diagram of the reaction time of a Landau ring color matching experiment with different illumination and color combinations provided in an embodiment of the present application.

[0029] Figure 8 This is a schematic diagram of the results of a two-factor ANOVA of the illumination variables and the color matching variables on the reaction time of the Landau ring color matching visual experiment data provided in an embodiment of the present application.

[0030] Fig. 9 This is a schematic diagram of the results of a two-factor equal-repetition analysis of variance on the reaction time of Landau ring recognition based on background color and illumination provided in an embodiment of the present application.

[0031] Fig.10 This is a schematic diagram of the results of a two-factor equal repeatability analysis of variance on the reaction time of Landau ring recognition based on foreground color and illumination provided in an embodiment of the present application.

[0032] Fig.11 A schematic diagram of the reaction time for identifying different color character strings on a black background radar screen provided in an embodiment of the present application.

[0033] Fig.12 This is a schematic diagram of the results of a two-factor repeated variance analysis of the reaction time of the radar screen character string to the illumination and foreground color provided in an embodiment of the present application.

[0034] Fig.13 This is a schematic diagram of the results of a two-factor equal-repetition analysis of variance on the effects of gender and background color on Landau ring reaction time under 500lx illumination provided in the examples of the present application.

[0035] Fig.14 This is a schematic diagram of the results of a two-factor equal-repetition analysis of variance for the Landau ring reaction time under 500 lx illumination for gender and foreground color variables including white, red and yellow provided in the embodiments of the present application.

[0036] Fig.15 A schematic diagram of the results of a two-factor repeated variance analysis of the reaction time for a radar screen character string recognition task under 500 lx illumination based on gender and foreground color variables including white, yellow and blue provided in an embodiment of the present application.

[0037] Fig.16A schematic diagram of a visual interface icon color matching device based on psychophysical human perception experimental data is provided for an embodiment of the present application.

[0038] Fig.17 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0039] Reference numerals: test user— 10 ; terminal— 20 . DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application.

[0041] In the following introduction, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance. The following introduction provides multiple embodiments of the present application, and different embodiments can be replaced or combined, so the present application can also be considered to include all possible combinations of the same and / or different embodiments recorded. Therefore, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then the present application should also be considered to include embodiments containing one or more of all other possible combinations of A, B, C, and D, although the embodiment may not be clearly recorded in the following text.

[0042] The following description provides examples and does not limit the scope, applicability or examples set forth in the claims. Changes may be made to the functions and arrangements of the elements described without departing from the scope of the present application. Various processes or components may be appropriately omitted, substituted or added to each example. For example, the described method may be performed in an order different from the order described, and various steps may be added, omitted or combined. In addition, features described in some examples may be combined in other examples.

[0043] With the development of the information age, the use of electronic devices is becoming more and more common in life and work. When people use electronic devices in life, they need to operate the corresponding devices and identify the electronic display content. The color matching of the symbol information on the device control panel and the electronic display and the background color is a problem faced by visual design; at the same time, whether in life or work, such as clothing, home decoration, stage design, exhibition halls, airports, stations and other public places, in order to highlight the visual impact of the subject or logo, that is, to enhance the recognizability of the target symbol, there is also the same color matching design problem. However, the current symbol color matching method is mainly based on the designer's personal experience, aesthetic concepts or scattered human perception research, which leads to the problem of subjectivity and one-sidedness in this method. The human eye visual recognition model involves target features such as lighting conditions, shape, size, color, and movement of symbols. In addition, it has a complex relationship with similar features of the background and observer factors, which is difficult to accurately express in an analytical form for a specific visual interface. In order to ensure the recognizability of icons in the visual interface, the embodiment of the present application develops a symbol color matching method based on human perception data, which determines the color selection of icons and the matching of background colors based on objective evaluation and quantitative analysis of human perception data of different color backgrounds and symbol colors. This can overcome the problems of subjectivity and one-sidedness in the prior art, improve user experience, and enhance the recognizability and readability of visual interface icons.

[0044] Based on this, an embodiment of the present application provides a method for color matching of visual interface icons based on a psychophysical human perception experiment. By obtaining an initial set of color matching images, the subjects are classified according to deterministic classification rules, and the reaction time of each subject in the subject group to each color matching image under preset test conditions is obtained. The original test reaction time is preprocessed to obtain the corresponding test reaction time, and a variance analysis is performed on the effect of preset variables on the reaction time of the subject group and its statistical significance is inferred. A color matching scheme is recommended based on the statistical inference conclusion of the significance. This can overcome the problems of subjectivity and one-sidedness in the prior art, improve the user experience, and improve the recognizability and readability of visual interface icons.

[0045] See also Figure 1 , is a schematic diagram of the architecture of a visual interface icon color matching system based on a psychophysical human perception experiment provided in an embodiment of the present application.

[0046] The system includes a terminal 20, which may include but is not limited to a personal computer, a desktop computer, a tablet computer, a PDA, a smart phone, an intelligent interactive tablet, a laptop computer, an all-in-one computer, a vehicle-mounted multimedia, VR glasses, XR glasses and other electronic devices or icon display panels or display devices. By obtaining an initial color matching image set, classifying the subjects according to a deterministic classification rule, obtaining the reaction time of each subject in the subject group to each color matching image under preset test conditions, preprocessing the original test reaction time to obtain the corresponding test reaction time, performing variance analysis on the effect of the preset variable on the reaction time of the subject group and inferring its statistical significance, and recommending a color matching scheme based on the statistical inference conclusion of the significance, the problems of subjectivity and one-sidedness in the prior art can be overcome, the user experience is improved, and the recognizability and readability of the visual interface icons are improved.

[0047] See also Figure 2 , is a flow chart of a method for color matching visual interface icons based on a psychophysical human perception experiment provided in an embodiment of the present application. Figure 2 As shown, the visual interface icon color matching method based on psychophysical human perception experiment may include the following steps: S201, obtaining an initial color matching image set, wherein each color matching image set is a set of different images that take values ​​from a preset background color set as the background color of the image and take values ​​from a preset foreground color set as the symbol color, i.e., the foreground color; the background color set is a set of values ​​of the image background color; and the foreground color set is a set of color values ​​of the image symbol content.

[0048] Specifically, different preset background colors are used as the background colors of the images in the image set, and different preset foreground colors are used as the character colors of the images in the image set, i.e., the foreground colors of the images, to construct a screen operation image set. This embodiment uses two types of screen operation images, totaling 80 images. The preset conditions of these two types of images and their corresponding color schemes, i.e., 1) Landau rings and their color matching 2) radar screen character strings and their color matching are set as follows:

[0049] Please see Figure 3 The Landau ring symbol is commonly used to test vision. Figure 3As shown in (a), its shape is like the English letter C, which is a circular ring of varying sizes composed of lines of a certain width with a small gap. The openings can be evenly arranged in 8 optional directions along the four sides of the ring. Since the Landau ring was proposed and used for human vision testing in 1899, it has been used to this day; compared with the symbols used in other vision charts, only the Landau ring can realize vision testing without being interfered by shape recognition. Therefore, the Landau ring is a legal vision detection symbol in strict vision testing occasions. This experiment is different from the general vision test. It is not necessary to use the design form of the traditional logarithmic vision chart. For the sake of simplicity of the experiment, only two Landau rings with different font sizes are used, and the two non-repeating opening directions of the four directions of up, down, left and right are respectively selected; there are 6 colors for the Landau ring symbol; the background is 3 colors, and each background color corresponds to 5 of the 6 Landau ring symbol colors (here is the foreground color) (to avoid the foreground color being submerged in the background color), Figure 3 (c) is a screenshot of a white Landau ring with large font on a black background. The relevant parameters of the Landau ring are shown in Tables 1 and 2. A test task only recognizes a Landau ring symbol with a random color and background. Therefore, the number of Landau ring recognitions under each lighting condition is 60. By changing the lighting and the above color matching (i.e. background color-foreground color), the aim is to find out the law of lighting level and color matching that restricts human visual perception.

[0050] Table 1 Experimental test conditions parameter Numeric Illumination / lx Color temperature of light source / k Number of screen frames of monochrome Landau ring / f Number of background colors of Landau ring / number of colors of Landau ring / number of background colors of radar simulation screen / number of strings of radar simulation screen / number of strings of radar simulation screen / number of colors of display maximum brightness / nit Number of test groups / group Number of subjects in each group / person 100 / 300 / 500 / 700 / 100055004 (2 large and small characters each) 3 (black / blue / green) 6 (white / red / blue / green / yellow / black) 1 (black) 205 (white / red / blue / green / yellow) 35.3166~7

[0051] Table 2 Values ​​of the sRGB space of colors used in the experiment

[0052] Please refer to Figure 3 , Figure 4 , Figure 3 The Landau ring image and screen operation diagram used in the experiment provided in the embodiment of the present application are as follows: Figure 4 The radar screen operation image and its color matching diagram used in the experiment provided in the embodiment of the present application. Considering that the screen display content of the Landau ring symbol test is relatively simple, which is very different from the more complex display content in the actual screen operation, and in order to further investigate the law of illumination and character color on human visual perception when the background color is fixed, the form and content of the experimental screen display are as follows Figure 3 As shown in (d), the background is black, and there are 4 strings of each of the five colors, for a total of 20 color strings. Considering the limitations of black and white hard copy printing, Figure 4 Colors are specially marked Figure 3 (d) shows the five colors in the display screen and the display positions and contents of four different character strings corresponding to each color. Thus, 20 character strings of different colors or contents need to be identified under each lighting condition.

[0053] S202, classifying the subject according to a deterministic classification rule, wherein the deterministic classification rule may be one or a combination of several classification rules such as age, gender, normal vision, abnormal vision, etc.

[0054] Specifically, this embodiment randomly selects 41 college students from a certain university, including 35 boys and 6 girls, with an age range of 19 to 22 years old, with normal corrected vision, no color blindness or color weakness, and in good health without any recent medication use.

[0055] S203, obtaining the reaction time of each subject in the subject group to each color matching image under preset test conditions, wherein the preset test conditions are that except for the controllable random change of the values ​​of the background color variable and the foreground color variable, other controllable test conditions such as the symbol content, symbol shape, symbol size, symbol movement, ambient light illumination, light source color temperature, display luminous intensity and other related variables affecting the reaction time are determined to remain unchanged; the subject group is a subject group with no less than 5 of the same type of subjects as the same preset test conditions; the reaction time is the time taken by the subject to complete the test task of identifying the symbol content in each color matching image.

[0056] Specifically, the experimental program of this embodiment is written on the psychology software E-Prime 2 platform. E-Prime is a set of computer programs developed by a psychology software tool company for designing and implementing computer-based experiments. In this experiment, driven by the program, the screen randomly displays pictures with symbols to be identified. When the subject identifies the symbol on the picture, i.e., the opening direction of the Landau ring or the string on the radar chart, and confirms it through keyboard operation, the program can automatically record the "reaction time" of the process, which can be accurate to the "millisecond / ms" level.

[0057] The screen symbol recognition experiment under each light level is divided into two parts: Landau ring recognition and radar screen character string recognition.

[0058] During the Landau ring recognition stage, the program controls the computer screen to display the 60 pictures in random order. When the subject confirms the opening direction through any one of the WSAD of the mouse, the system records the reaction time of this test and then continues with the next test. In this way, there are 60 reaction time records for Landau ring recognition in one illumination.

[0059] Radar screen string recognition stage, in the Figure 3 (b) and started a string recognition experiment. Figure 3(d) Find the string indicated by the instructions on the color string display screen shown in the instruction, write it down on the corresponding position of the blank A4 paper, and then press the Enter key to mark the end of the recognition of a random color string. The system records the reaction time of this test and then continues the next test. In this way, there are 20 reaction time records for the recognition of color strings on the radar screen in one illumination. The purpose of asking the subjects to write down the string is to prevent the subjects from ignoring the accuracy of recognition in pursuit of speed and to enhance the reliability of the data.

[0060] Figure 5 A schematic diagram of an experimental scenario provided in an embodiment of the present application, Figure 6 Spectral distribution curves of LED lamps with different illumination provided in the embodiments of the present application. By adjusting the floor-standing LED lamp array, 5 groups of lighting levels of 100lx-1000lx are obtained (see Table 1 for details). Preliminary experiments show that the reaction time of different subjects to the same input stimulus in the groups of 6 and 7 is relatively scattered, and even exceeds the deviation range of 3σ. According to statistical sampling theory, under the premise that the probability of valid test data meeting the 3σ accuracy is 99%, the number of samples not less than 5 can meet the experimental requirements. Therefore, the number of subjects in the subject group described in the embodiments of the present application meets the statistical sample capacity requirements.

[0061] In order to facilitate the adjustment of light and the consistency of test conditions for subjects at each light level, 35 male subjects were divided into 5 groups, 7 people in each group, and each group participated in the test at a different illumination level. After the light adjustment was completed, the test group was asked to enter the laboratory and adapt for 15 minutes before starting the experiment. The experiments were conducted from 9:00 to 11:30 in the morning and from 15:00 to 17:30 in the afternoon. As a control group, a group of 6 girls participated in the experiment at a light level of 500lx. In this way, the 6 groups of reaction time data were obtained.

[0062] S204, preprocessing the original test reaction time to obtain the corresponding test reaction time of the subject group, that is, first cleaning the original test data: based on the original test reaction time of the subject group, delete the abnormal data exceeding 3 times the standard deviation in the original test reaction time of each member of the same target test image, and then take the corresponding reaction time of the adjacent tester closest to the mean of the test data of the subject group to fill the missing data; then calculate the reaction time of the subject group to the corresponding color matching image under the preset test conditions: based on the test reaction time of each member of the subject group after the cleaning data, the corresponding reaction time data of all subjects in the subject group under the preset test conditions are averaged as the reaction time of the corresponding color matching image under the corresponding test conditions.

[0063] Specifically, the data measured in S203 is exported via the Edata module of the experimental platform for subsequent statistical analysis. Then, the data is statistically analyzed in two steps:

[0064] First, the data cleaning and filling, that is, outlier detection and filling: Outliers are defined as the measured values ​​that deviate from the corresponding overall median (Median) by 3σ in the reaction time test values ​​of different subjects for the same stimulus. Matlab2022a provides a variety of filling methods, and outlier detection and filling can be completed by selecting the "nearest" method in the filloutlier function. At this time, the removed outliers are replaced by the nearest measured values.

[0065] Secondly, for the test results of the visual experiment, the mathematical statistics method of two-way variance analysis was used to determine whether there were significant statistical differences in the subjects' screen icon recognition when the illumination, background color-foreground color (color matching, background color, foreground color, gender and illumination level changed. The variance calculation can be implemented by the Data Analysis module in Microsoft Excel 2019.

[0066] S205, perform variance analysis on the effect of preset variables on the reaction time of the subject group and infer its statistical significance, that is, classify and sort the corresponding reaction time based on the background color variable corresponding to the background color set, the foreground color variable corresponding to the foreground color value set, and the test group variables of different types of test user groups, and perform two-way variance analysis on the reaction time corresponding to the variables consisting of all value sets or subsets of any two variables, and then infer the significance of the effect of the corresponding value conditions of the variables on the reaction time based on the variance analysis results. This step is hereinafter referred to as the statistical inference step.

[0067] S206, recommending a color scheme based on the statistical inference conclusion of significance, specifically, for a subset of variable values ​​that have a significant effect on reaction time, recommending a color scheme corresponding to the minimum reaction time for the variable value; and for a subset of variables that have no significant effect on reaction time, recommending a color scheme corresponding to the subset of variables. This step is hereinafter referred to as the color scheme recommendation step.

[0068] Specifically, the statistical inference step of S205 and the color scheme decision step of S206 will be described in detail below using the experimental results of this embodiment.

[0069] Please see Figure 7 , Figure 7A schematic diagram of reaction time for a Landau ring color matching experiment with different illuminations and color combinations provided in an embodiment of the present application. The experimental data of the boys' group was taken as the research object. For the Landau ring recognition experiment, there are 15 combinations of background color and foreground Landau ring color combinations. The reaction time data for a color combination under each illumination level includes 4 opening directions and 7 subject observations. Therefore, 420 raw reaction time data are collected for each illumination level; for 5 illumination levels, a total of 2100 data are collected. First, the 7 reaction times of each group of subjects with the same observation conditions are subjected to outlier detection and filling operations, and then the average is calculated. Then, the corresponding reaction times of the 4 Landau rings with exactly the same color combination (background color-foreground color) are averaged, and the average is used as the reaction time of the corresponding color combination. In this way, the following is obtained: Figure 7 Reaction times for 15 color-matching experiments at five illumination levels as shown.

[0070] Please see Figure 8 , is the result of the two-factor variance analysis of the illumination variable and the color matching variable on the reaction time of the Landau ring color matching visual experiment data provided in the embodiment of the present application. Figure 7 The reaction time data shown were subjected to two-way analysis of variance (ANOVA 2), and the results are shown in Figure 8 The error bars represent plus or minus one standard deviation. Figure 8 It can be seen that no matter the analysis result of the light level variable on reaction time (F=53.05, df=4, p<0.0001) or the result of the foreground-background color matching variable (F=14.04, df=14, p<0.0001), the p value is less than 0.05, that is, both variables have a significant effect on reaction time.

[0071] because Figure 8 The statistical inference conclusions of the illumination variable and the color matching variable on the reaction time are both significant, that is, the difference in the corresponding reaction time when the variable is taken at different values ​​cannot be ignored in a statistical sense. Therefore, the corresponding value with the minimum reaction time is recommended for the color matching variable. Figure 8 The color matching data can recommend that the background color-foreground color variable be black-white, and its mean value is 475.5s. However, at this time, the foreground color and background color can only have one color value.

[0072] Taking into account Figure 8 It can be seen from the data that there are four color matching values ​​that are similar, as shown in Table 3. Figure 8 Taking the reaction time data under five illumination levels corresponding to the four values ​​of the color matching variable (background color - foreground color) shown in the figure as an example, the corresponding statistical analysis results are shown in Table 4. Figure 3It shows that the black-white color scheme has the smallest mean value. However, from the variance statistical analysis results in Table 4, since the p value is 0.697, which is greater than 0.05, there is no statistically significant difference in the reaction time of these four color variables. Therefore, the color schemes of black-white / blue-white / green-black / green-blue are recommended.

[0073] It should be noted that, except for the p-value which is the corresponding probability value in the variance analysis results table shown in Table 4, the specific calculation of variance analysis and the statistical significance of other related symbols can be found in general statistics textbooks (such as: Sheng Zhou, Xie Shiqian, Pan Chengyi. Probability Theory and Mathematical Statistics [M]. Fourth Edition. Beijing: Higher Education Press, 2017, pp. 287-291.), which is suitable for engineering and technical professionals in related fields to understand, and will not be repeated here.

[0074] Table 3 Mean and variance of reaction time for four values ​​of color matching variables Background color - foreground color Mean / s <![CDATA[Variance / s 2 > Black-White 475.5 843.2 Blue-white 483.0 1637.0 Green-Black 487.0 640.4 Green-Blue 485.5 1791.6

[0075] Table 4 ANOVA results of reaction time data with color matching variables as rows Error Sources SS df MS F P F crit Row / Color 392.6 3 130.9 0.49 0.697 3.49 Column / Light 16430.2 4 4107.6 15.31 0.0001 3.27 error 3218.6 12 268.2 total 20041.4 19

[0076] Please see Fig. 9 , which is a schematic diagram of the results of the two-factor equal-repeated ANOVA on the reaction time of Landau ring recognition provided by the embodiment of the present application. For the light level and background color variables, since there are 3 background colors and the number of repeated observations corresponding to each background color is 5, a two-factor equal-repeated ANOVA with 5 repeated observations is used, and the results are as follows: Fig. 9 As shown. Fig. 9 It can be seen that the analysis results of the background color variable and the light level variable on the reaction time are (F=7.44, df=2, p<0.05) and (F=16.43, df=4, p<0.001), respectively, and their p values ​​are both less than 0.05, that is, both variables have a significant effect on the reaction time; and because p=0.91, that is, greater than 0.05, the interaction effect between the two is not significant (F=0.42, df=3, p=0.91). At this time, the reaction time when the background color is green is the shortest, so it is recommended to take the green color value of the background color without considering the change of the foreground color.

[0077] Please see Fig.10 , which is a schematic diagram of the results of the two-factor equal repeatability analysis of variance of the foreground color and illumination on the reaction time of Landau ring recognition provided by the embodiment of the present application. For the foreground color variable and the illumination level variable, there are 6 foreground colors of the Landau ring symbol in the experiment, and each foreground color is Figure 5There are at least 2 of the 15 data points shown, so the two-factor equal-repetition ANOVA method with 2 repeated observations is used, and the results are as follows Fig.10 As shown. Fig.10 It can be seen that the analysis results of the foreground color variable and the light level variable on the reaction time are (F=3.79, df=5, p<0.01) and (F=11.07, df=4, p<0.0001), respectively, and their p values ​​are both less than 0.05, that is, both variables have a significant effect on the reaction time; and because p=0.95 is greater than 0.05, the interaction effect between the two is not significant (F=0.30, df=20, p=0.95). At this time, the reaction time when the foreground color is white is the shortest, so it is recommended to use the white color value for the foreground color without considering the background color change.

[0078] Please see Fig.11 , which is a schematic diagram of the reaction time of different color character strings on a black background radar screen provided by an embodiment of the present application. The preprocessing method of the observation data in the radar screen character string screen recognition operation test phase is similar to the Landau ring screen operation recognition test, which will not be repeated here. Fig.11 A total of 25 data preprocessed by the method described in S204 are displayed on a black background radar simulation screen under 5 colors and 5 illumination levels, wherein each data is the average of 4 different string observations under the same color and illumination conditions.

[0079] Please see Fig.12 , is a schematic diagram of the results of a two-factor repeated variance analysis of the reaction time of the radar screen character string to the illumination and foreground color provided in the embodiment of the present application. With the illumination level and foreground color, i.e., the color of the character string, as the control variables, it can be concluded that the character string of the same color was observed four times in the experiment, so the two-factor equal repeated variance analysis method can be used to make further statistical inferences on the data. Fig.12 The results of two-way repeated analysis of variance for the effects of light level and foreground color on the reaction time of character string recognition. Fig.12 It can be seen that different illumination levels have no significant difference in reaction time (F=2.15, df=4, p=0.083), the string color variable has a significant effect on the string recognition time (F =4.78, df=4, p<0.01), and the interaction effect between the two is not significant (F=0.30, df=16, p=0.65). At this time, the reaction time of the white string is the shortest, so the foreground color is recommended to be white when the background is black, and no matter how the illumination level changes, the reaction time of the string on the black background screen has no significant difference.

[0080] Please see Fig.13, which is a schematic diagram of the results of the two-factor equal-repeated variance analysis of the Landau ring reaction time under 500lx illumination provided in the embodiment of the present application. Considering the influence of gender and background color on the reaction time, the data of the Landau ring recognition task experimental stage, with gender and background color as dependent variables, can be considered as repeated observations of each background color at 500lx illumination level 20 times, so the two-factor equal-repeated variance analysis method can be used, and the results are as follows Fig.13 As shown. Fig.13 It can be seen that gender has a significant difference in reaction time (F=67.9, df=1, p<0.001), and background color has a significant difference in reaction time (F=3.58, df=2, p<0.05). The p values ​​corresponding to both are less than the significance level of 0.05, and the interaction effect between the two is not significant (F=0.49, df=2, p=0.62). At this time, the green background reaction time is the shortest, so it is recommended to take the green color value of the background color without considering the change of the foreground color.

[0081] Please see Fig.14 , which is a schematic diagram of the results of the two-factor equal-repeated variance analysis of the Landau ring reaction time under 500lx illumination for the foreground color variables of gender and white, red and yellow provided in the embodiment of the present application. A gender control analysis was performed on the foreground color variable. Since the number of repeated observations of the data corresponding to the three colors of foreground color white, red and yellow in the two control groups was 3 each, a two-factor equal-repeated variance analysis method was used, and the results obtained were as follows: Fig.14 As shown. Fig.14 It can be seen that there is a significant difference in reaction time between genders (p<0.05), and there is no significant difference in reaction time corresponding to the three foreground color variables of white, red, and blue (p=0.5). At this time, regardless of gender, the recommended color value is to use all color values ​​that include white, red, and yellow as foreground colors.

[0082] Please see Fig.15 , is a schematic diagram of the results of a two-factor repeated variance analysis of the reaction time of the radar screen character string recognition task under 500lx illumination for gender and foreground color variables including white, yellow and blue provided in the embodiment of the present application. Gender control analysis was performed for the foreground color variables including white, yellow and blue. Fig.15It shows that there is no significant difference in the effect of gender on reaction time (F=0.11, df=1, p=0.74), and there is no significant difference in the foreground colors of white, yellow and blue on reaction time (F=0.092, df=2, p=0.91). There is no significant interaction effect between the two variables (F=0.28, df=2, p=0.76). It can be seen that in the color matching of the radar chart under the black background, the foreground color variable value of white, yellow and blue and the user's gender have no statistically significant effect on the reaction time (i.e. recognition) of the screen recognition task. Therefore, it is recommended to use the three color values ​​of white, yellow and blue foreground colors at this time, and this color matching has no significant effect on the reaction time of gender.

[0083] In an embodiment of the present application, by obtaining an initial set of color matching images, the subjects are classified according to deterministic classification rules, the reaction time of each subject in the subject group to each color matching image under preset test conditions is obtained, the original test reaction time is preprocessed to obtain the corresponding test reaction time, a variance analysis is performed on the effect of the preset variables on the reaction time of the subject group and its statistical significance is inferred, and a color matching scheme is recommended based on the statistical inference conclusion of the significance, thereby overcoming the problems of subjectivity and one-sidedness in the prior art, improving the user experience, and improving the recognizability and readability of the visual interface icons.

[0084] Please see Fig.16 , a visual interface icon color matching device based on psychophysical human perception experimental data is provided for the embodiment of the present application, the device comprising:

[0085] The first original color image acquisition module 1611 is used to acquire an initial color image set, wherein each color image set is a set of different images that take values ​​from a preset background color set as the background color of the image and take values ​​from a preset foreground color set as the symbol color, i.e., the foreground color; the background color set is a set of values ​​of the image background color; and the foreground color set is a set of color values ​​of the image symbol content.

[0086] The second qualified subject screening module 1612 is used to classify the subjects according to deterministic classification rules, wherein the deterministic classification rules can be one or a combination of several classification rules such as age, gender, normal vision, abnormal vision, etc.

[0087] The third reaction time acquisition module 1613 is used to obtain the reaction time of each subject in the subject group to each color matching image under preset test conditions, wherein the preset test conditions are that except for the controllable random changes in the values ​​of the background color variable and the foreground color variable, other controllable test conditions such as symbol content, symbol shape, symbol size, symbol movement, ambient light illumination, light source color temperature, display luminous intensity and other related variables affecting the reaction time are determined; the subject group is a subject group with no less than 5 of the same type of subjects as the same preset test conditions; the reaction time is the time taken by the subject to complete the test task of identifying the symbol content in each color matching image.

[0088] The fourth data preprocessing module 1614 is used to preprocess the original test reaction time to obtain the corresponding test reaction time of the subject group, that is, first clean the original test data: based on the original test reaction time of the subject group, delete the abnormal data that exceeds 3 times the standard deviation in the original test reaction time of each member of the same target test image, and then take the corresponding reaction time of the adjacent tester closest to the mean of the subject group test data to fill the missing data; then calculate the reaction time of the subject group to the corresponding color matching image under the preset test conditions: based on the test reaction time of each member of the subject group after the cleaning data, the corresponding reaction time data of all subjects in the subject group under the preset test conditions are averaged as the reaction time of the corresponding color matching image under the corresponding test conditions.

[0089] The fifth statistical discrimination module 1615 is used to perform variance analysis on the influence of preset variables on the reaction time of the subject group and infer its statistical significance, that is, based on the background color variables corresponding to the background color set, the foreground color variables corresponding to the foreground color value set, and the test group variables of different types of test user groups, the corresponding reaction times are classified and sorted, and a two-way variance analysis is performed on the reaction time corresponding to the variables consisting of the set of all values ​​of any two variables or their subsets, and then, based on the variance analysis results, the significance of the influence of the corresponding values ​​of the variables on the reaction time is inferred.

[0090] The sixth color recommendation module 1616 is used to recommend color schemes based on the significant statistical inference conclusion. Specifically, for a subset of variable values ​​that have a significant impact on the reaction time, the color scheme corresponding to the minimum reaction time is recommended; for a subset of variables that have no significant impact on the reaction time, the corresponding color scheme of the variable subset is recommended.

[0091] In an embodiment of the present application, by obtaining an initial set of color matching images, the subjects are classified according to deterministic classification rules, the reaction time of each subject in the subject group to each color matching image under preset test conditions is obtained, the original test reaction time is preprocessed to obtain the corresponding test reaction time, a variance analysis is performed on the effect of the preset variables on the reaction time of the subject group and its statistical significance is inferred, and a color matching scheme is recommended based on the statistical inference conclusion of the significance, thereby overcoming the problems of subjectivity and one-sidedness in the prior art, improving the user experience, and improving the recognizability and readability of the visual interface icons.

[0092] See also Fig.17 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig.17 As shown, the terminal device may include: at least one processor, at least one network interface, at least one input / output interface, at least one display unit, at least one memory, and at least one communication bus. Among them, the processor may include one or more processing cores. The processor uses various interfaces and lines to connect the various parts of the entire electronic device, and executes various functions of the terminal and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory. The memory can be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory may optionally be at least one storage device located away from the aforementioned processor. Among them, the network interface may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface or a Bluetooth interface). The communication bus is used to realize the connection and communication between these components. The display unit may be a touch panel, a computer display, a projection screen, a VR glasses or an XR glasses or other graphic display panel or display device. As Fig.17 As shown, the memory as a storage medium may include an operating system, a network communication module, an input / output interface module, and a visual interface icon color matching program based on a psychophysical human perception experiment.

[0093] exist Fig.17 In the electronic device shown, the input and output interface is mainly used to provide an interface for users and access devices and obtain data input by users and access devices.

[0094] In one embodiment, Fig.17 The processor in the electronic device shown can be used to call the visual interface icon color matching program based on the psychophysical human perception experiment stored in the memory, and specifically perform the following operations:

[0095] S1. Obtain an initial color matching image set, wherein each color matching image set is a set of different images that take values ​​from a preset background color set as the background color of the image and take values ​​from a preset foreground color set as the icon color, i.e., the foreground color; the background color set is a set of values ​​of the image background color; and the foreground color set is a set of color values ​​of the image icon content.

[0096] S2, classifying the subjects according to deterministic classification rules, wherein the deterministic classification rules may be one or a combination of several classification rules such as age, gender, normal vision, abnormal vision, etc.

[0097] S3, obtaining the reaction time of each subject in the subject group to each color matching image under preset test conditions, wherein the preset test conditions are that except for the controllable random changes in the values ​​of the background color variable and the foreground color variable, other controllable test conditions such as symbol content, symbol shape, symbol size, symbol movement, ambient light illumination, light source color temperature, display luminous intensity and other related variables affecting the reaction time are determined to remain unchanged; the subject group is a subject group with no less than 5 of the same type of subjects as the same preset test conditions; the reaction time is the time taken by the subject to complete the test task of identifying the symbol content in each color matching image.

[0098] S4, preprocessing the original test reaction time to obtain the corresponding test reaction time of the subject group, that is, first cleaning the original test data: based on the original test reaction time of the subject group, delete the abnormal data exceeding 3 times the standard deviation in the original test reaction time of each member of the same target test image, and then take the corresponding reaction time of the adjacent tester closest to the mean of the test data of the subject group to fill the missing data; then calculate the reaction time of the subject group to the corresponding color matching image under the preset test conditions: based on the test reaction time of each member of the subject group after the cleaning data, the corresponding reaction time data of all subjects in the subject group under the preset test conditions are averaged as the reaction time of the corresponding color matching image under the corresponding test conditions.

[0099] S5, perform variance analysis on the effect of preset variables on the reaction time of the subject group and infer its statistical significance, that is, classify and organize the corresponding reaction times based on the background color variables corresponding to the background color set, the foreground color variables corresponding to the foreground color value set, and the test group variables of different types of test user groups, and perform two-way variance analysis on the reaction time corresponding to the variables consisting of the set of all values ​​of any two variables or their subsets, and then, based on the variance analysis results, infer the significance of the effect of the corresponding values ​​of the variables on the reaction time.

[0100] S6, recommending a color scheme based on the significant statistical inference conclusion, specifically, for a subset of variable values ​​that have a significant effect on the reaction time, recommending a color scheme corresponding to the minimum reaction time for the variable values; and for a subset of variables that have no significant effect on the reaction time, recommending a corresponding color scheme for the variable subset.

[0101] It is worth noting that a more detailed technical implementation description of each step S1 to S6 in the embodiment of the present application is provided in the following Figure 2 The steps S201 to S206 are shown in the figure and are accordingly reflected and will not be described in detail here.

[0102] In an embodiment of the present application, by obtaining an initial set of color matching images, the subjects are classified according to deterministic classification rules, the reaction time of each subject in the subject group to each color matching image under preset test conditions is obtained, the original test reaction time is preprocessed to obtain the corresponding test reaction time, a variance analysis is performed on the effect of the preset variables on the reaction time of the subject group and its statistical significance is inferred, and a color matching scheme is recommended based on the statistical inference conclusion of the significance, thereby overcoming the problems of subjectivity and one-sidedness in the prior art, improving the user experience, and improving the recognizability and readability of the visual interface icons.

[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that the technical solution of the present application can be implemented by means of at least one of software and hardware. "Unit" and "module" in this specification refer to at least one of software and hardware that can independently complete or cooperate with other components to complete specific functions, where the hardware can be, for example, a field programmable gate array (FPGA), an integrated circuit (IC), etc.

[0104] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0105] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0106] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0107] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0108] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0109] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable an electronic device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, disk or optical disk and other media that can store program codes.

[0110] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by entering a program to instruct related hardware. The program may be stored in a computer-readable memory, and the memory may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0111] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering and practicing the disclosure here, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for color matching of visual interface icons based on psychophysical human perception experiments, the method comprising the following steps: S1, obtaining an initial color matching image set; S2, classifying the subjects according to deterministic classification rules; S3, obtaining the reaction time of each subject in the subject group to each color matching image under preset test conditions; S4, preprocessing the original test reaction time to obtain the corresponding test reaction time of the subject group; S5, performing variance analysis on the effect of preset variables on the reaction time of the subject group and inferring its statistical significance; S6, recommending a color matching scheme based on the statistically significant inference conclusion.

2. Based on claim 1, each color matching image set is a set composed of different images that take values ​​from a preset background color set as the background color of the image and take values ​​from a preset foreground color set as the icon color, i.e., the foreground color; the background color set is a set of values ​​of the image background color; and the foreground color set is a set of color values ​​of the image icon content.

3. Classifying the subjects according to deterministic classification rules based on claim 1, wherein the deterministic classification rules can be one or a combination of several classification rules such as age, gender, normal vision, abnormal vision, etc.

4. Based on the method of claim 1, the reaction time of each subject in the subject group to each color matching image under preset test conditions is obtained, wherein the preset test conditions are that except for the controllable random changes in the values ​​of the background color variable and the foreground color variable, other controllable test conditions such as symbol content, symbol shape, symbol size, symbol movement, ambient light illumination, light source color temperature, display luminous intensity and other related variables affecting the reaction time are determined to remain unchanged; the subject group is a subject group with no less than 5 of the same type of subjects as the same preset test conditions; the reaction time is the time taken by the subject to complete the test task of identifying the symbol content in each color matching image.

5. Based on the original test reaction time as described in claim 1, the corresponding test reaction time of the subject group is obtained by preprocessing the original test reaction time, that is, firstly, the original test data is cleaned: based on the original test reaction time of the subject group, the abnormal data exceeding 3 times the standard deviation in the original test reaction time of each member of the same target test image is deleted, and then the corresponding reaction time of the adjacent tester closest to the mean of the test data of the subject group is taken to fill the missing data; then the reaction time of the subject group to the corresponding color matching image under the preset test conditions is calculated: based on the test reaction time of each member of the subject group after the cleaning data, the corresponding reaction time data of all subjects in the subject group under the preset test conditions are averaged as the reaction time of the corresponding color matching image under the corresponding test conditions.

6. Based on the effect of preset variables on the reaction time of the subject group as described in claim 1, a variance analysis is performed and its statistical significance is inferred, that is, based on the background color variables corresponding to the background color set, the foreground color variables corresponding to the foreground color value set, and the test group variables of different types of test user groups, their corresponding reaction times are classified and sorted, and a two-way variance analysis is performed on the reaction time corresponding to the variables consisting of the set of all values ​​of any two variables or their subsets, and then, based on the variance analysis results, the significance of the effect of the corresponding values ​​of the variables on the reaction time is inferred.

7. Based on the color scheme recommended based on the significant statistical inference conclusion described in claim 1, specifically, for a subset of variable values ​​that have a significant impact on reaction time, recommend a color scheme corresponding to the minimum reaction time for the variable values; for a subset of variables that have no significant impact on reaction time, recommend a corresponding color scheme for the variable subset.

8. A visual interface icon color matching device based on psychophysical human perception experimental data, the device comprising: The original color matching image acquisition module is used to acquire an initial color matching image set, wherein each color matching image set is a set of different images that take values ​​from a preset background color set as the background color of the image and take values ​​from a preset foreground color set as the icon color, i.e., the foreground color; the background color set is a set of values ​​of the image background color; and the foreground color set is a set of values ​​of the color of the image icon content; A qualified subject screening module is used to classify the subjects according to deterministic classification rules, wherein the deterministic classification rules can be one or a combination of several classification rules such as age, gender, normal vision, abnormal vision, etc.; A reaction time acquisition module is used to acquire the reaction time of each subject in the subject group to each color matching image under preset test conditions, wherein the preset test conditions are that, except for the controllable random change of the values ​​of the background color variable and the foreground color variable, other controllable test conditions such as the symbol content, symbol shape, symbol size, symbol movement, ambient light illumination, light source color temperature, display luminous intensity and other related variables affecting the reaction time are determined unchanged; the subject group is a subject group with no less than 5 subjects of the same type as the same preset test conditions; the reaction time is the time taken by the subject to complete the test task of identifying the symbol content in each color matching image; The data preprocessing module is used to preprocess the original test reaction time to obtain the corresponding test reaction time of the subject group, that is, firstly clean the original test data: based on the original test reaction time of the subject group, delete the abnormal data exceeding 3 times the standard deviation in the original test reaction time of each member of the same target test image, and then take the corresponding reaction time of the adjacent tester closest to the mean of the test data of the subject group to fill the missing data; then calculate the reaction time of the subject group to the corresponding color matching image under the preset test conditions: based on the test reaction time of each member of the subject group after the cleaning data, the corresponding reaction time data of all subjects in the subject group under the preset test conditions are averaged as the reaction time of the corresponding color matching image under the corresponding test conditions; A statistical discrimination module is used to perform variance analysis on the effect of preset variables on the reaction time of the subject group and infer its statistical significance, that is, based on the background color variables corresponding to the background color set, the foreground color variables corresponding to the foreground color value set, and the test group variables of different types of test user groups, the corresponding reaction times are classified and sorted, and a two-way variance analysis is performed on the reaction time corresponding to the variables consisting of the set of all values ​​of any two variables or their subsets, and then, based on the variance analysis results, the significance of the effect of the corresponding values ​​of the variables on the reaction time is inferred; The color matching recommendation module is used to recommend color matching schemes based on the statistical inference conclusions. For a subset of variable values ​​that have a significant effect on reaction time, a color matching scheme corresponding to the minimum reaction time is recommended for the subset of variable values ​​that have no significant effect on reaction time; and for a subset of variables that have no significant effect on reaction time, a color matching scheme corresponding to the subset of variables is recommended.

9. An electronic device may include: A display unit, a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method steps described in claims 1 to 7.

10. The display unit according to claim 9 can be a touch panel, a computer display, a projection screen, VR glasses, XR glasses or other icon display panels or display devices.

Images