Color vision assessment method, apparatus, and electronic device

Abstract

The application provides a color vision evaluation method and device and electronic equipment. The method is applied to a controller connected with a test palette. The test palette is used to present a stimulus color block of a specified color dimension at a random position of an image in each trial, so that a subject makes a response to the random and continuous change of the position of the stimulus color block. The stimulus color block is formed by color blocks of multiple color dimensions being crossed and spaced. The method comprises: for each color dimension, adjusting the color contrast of the next frame based on the size relationship between the RMSE value of the subject under the current color contrast of the stimulus color block and the determination standard value, so that the RMSE value fluctuates within a certain range around the standard value, thereby collecting effective response data of the subject, and then fitting the sequence data of the multiple color contrasts and the corresponding RMSE values determined based on the effective data by using a cumulative normal distribution function, to obtain a contrast threshold parameter, i.e. an accurate color vision evaluation value.

Description

TECHNICAL FIELD

[0001] The present application relates to the color test technical field, especially to a color vision evaluation method and device and electronic equipment. BACKGROUND

[0002] In the existing color vision test method, a stimulus color block needs to be set in an image, and then the stimulus color block is controlled to continuously change at different positions in the image. During the test, the subject needs to track the stimulus color block changing at different positions and make a response, so as to evaluate the color vision of the subject. However, this method has a problem. Since the color contrast of the stimulus color block is fixed, it is impossible to determine whether effective response data of the subject can be collected under the color contrast, and thus the color vision evaluation result of the subject is not accurate enough. SUMMARY

[0003] The present application aims to provide a color vision evaluation method and device and electronic equipment, which can adjust the color contrast of the stimulus color block in the next frame of image based on the size relationship between the RMSE value of the subject under the current color contrast of the current stimulus color block and the determination standard value, so that the RMSE value fluctuates within a certain range around the standard value, thereby collecting effective response data of the subject to the stimulus data, and then fitting the sequence data of the multiple color contrasts and the corresponding RMSE values determined based on the effective data by using the cumulative normal distribution function, to obtain the contrast threshold parameter, that is, the accurate color vision evaluation value.

[0004] In a first aspect, the embodiments of the present application provide a color vision evaluation method. The method is applied to a controller connected with a test panel. The test panel is used to present a stimulus color block of a specified color dimension at a random position of an image for each test, so that a subject makes a response to the random and continuous change of the position of the stimulus color block. The stimulus color block is formed by color blocks of multiple color dimensions being cross-spaced. The multiple color dimensions include a red-green color dimension, a yellow-blue color dimension, or a black-white color dimension. The method comprises: for each color dimension, taking the color contrast of the stimulus color block in a first frame of image as a current color contrast, and performing the following data acquisition steps: acquiring response data of the subject when the subject performs a color vision test through the stimulus color block under the current color contrast of the color dimension, and corresponding stimulus data; determining a current RMSE value under the current color contrast according to the response data and the stimulus data of the subject under the current color contrast; adjusting the color contrast of the stimulus color block in a next frame of image according to the size relationship between the current RMSE value and a predetermined judgment standard value, taking the adjusted color contrast as the current color contrast again, and continuing to perform the data acquisition steps until multiple color contrasts within a specified time window and the RMSE value corresponding to each color contrast are acquired; the RMSE value represents the root mean square difference between the test data and the response data in the measurement test; using a cumulative normal distribution function to fit according to the multiple color contrasts and the RMSE value corresponding to each color contrast, and estimating a contrast threshold parameter of the subject under the color dimension by using a second mathematical expectation of the distribution; and determining the contrast threshold parameter of the subject under different color dimensions as a color vision evaluation value corresponding to the subject.

[0005] Further, the step of determining the current RMSE value under the current color contrast according to the response data and the stimulus data of the subject under the current color contrast comprises: determining an action reaction delay using a cross-correlation method according to the response data and the stimulus data of the subject under the current color contrast; and calculating the root mean square difference between the stimulus data and the response data data as the current RMSE value under the current color contrast based on the response data and the stimulus data under the current color contrast and the action reaction delay.

[0006] Further, the step of calculating the root mean square difference between the stimulus data and the response data data based on the response data and the stimulus data under the current color contrast and the action reaction delay comprises: calculating the root mean square difference RMSE between the stimulus data and the response data data according to the following first specified formula:

[0007]

[0008] wherein, I t represents the reaction position of the subject at t test moment, s t-ΔtThe stimulation position at t-Δt, Δt represents the action reaction delay, and N represents the total frame number corresponding to the time window under the current color contrast.

[0009] Further, the step of adjusting the color contrast of the stimulus color block in the next frame of image according to the size relationship between the current RMSE value and the predetermined determination standard value comprises: if the current RMSE value is greater than the determination standard value, reducing the color contrast of the stimulus color block in the next frame of image by a preset step size; if the current RMSE value is less than the determination standard value, increasing the color contrast of the stimulus color block in the next frame of image by a preset step size.

[0010] Further, the determination method of the preset step size is as follows: the preset step size step is determined according to the following second designated formula:

[0011]

[0012] Wherein, C s The current color contrast of the stimulus color block in the current frame of image, b2 and b3 are respectively the parameters of the slope of the adjustment step size and the overall size of the step size.

[0013] Further, the determination process of the determination standard value is as follows: for the color dimension, a corresponding calibration test is set; the reaction data and the stimulation data of the subject under the calibration test are obtained; the calibration test RMSE value is determined according to the reaction data and the stimulation data under the calibration test; the calibration test RMSE value represents the root mean square difference between the test data and the reaction data in the calibration test; the determination standard value of the measurement test under the color dimension is calculated according to the calibration test RMSE value.

[0014] Further, the step of calculating the determination standard value of the measurement test under the color dimension according to the calibration test RMSE value comprises: the determination standard value d of the measurement test under the color dimension is calculated according to the following third designated formula:

[0015] d=(1+b1)RMSE';

[0016] Wherein, b1 represents a parameter for representing the strictness of the determination standard; b1 is different under different color dimensions; RMSE' represents the calibration test RMSE value.

[0017] Further, the step of fitting the RMSE values corresponding to the plurality of color contrasts using a cumulative normal distribution function and estimating the contrast threshold parameter of the subject in the color dimension by a second mathematical expectation of the distribution comprises: determining F values corresponding to the plurality of color contrasts respectively according to the RMSE values corresponding to the plurality of color contrasts; the F value represents that the RMSE under the color contrast of the next frame of image is reduced or increased relative to the RMSE under the color contrast of the current frame; substituting the plurality of color contrasts and the corresponding F values into the following fourth designated formula to determine the contrast threshold parameter of the subject in the color dimension:

[0018]

[0019] wherein x represents the color contrast of the stimulus color block under the current color dimension, F N (x|α,β) = 0 or 1; 0 represents that the RMSE under the color contrast of the next frame of image is increased relative to the RMSE under the color contrast of the current frame; 1 represents that the RMSE under the color contrast of the next frame of image is reduced relative to the RMSE under the color contrast of the current frame; a represents the contrast threshold of the subject in the color dimension; β is proportional to y = F N (α|α,β) is the derivative of the function; wherein a and β are both contrast threshold parameters.

[0020] In a second aspect, the application further provides a color vision evaluation device, which is applied to a controller connected with a test board; the test board is used to present a stimulus color block of a specified color dimension at a random position of an image for each test, so that a subject makes a response to the random and continuous change of the position of the stimulus color block; the stimulus color block is formed by color blocks of multiple color dimensions being cross-spaced, and the multiple color dimensions include a red-green color dimension, a yellow-blue color dimension or a black-white color dimension; the device includes: a data acquisition module, which is used to, for each color dimension, take the color contrast of the stimulus color block in a first frame of image as a current color contrast, and perform the following data acquisition steps: acquiring response data of the subject when the subject performs a color vision test through the stimulus color block under the current color contrast of the color dimension, and corresponding stimulus data; determining a current RMSE value under the current color contrast according to the response data and the stimulus data of the subject under the current color contrast; adjusting the color contrast of the stimulus color block in a next frame of image according to the size relationship between the current RMSE value and a predetermined judgment standard value, taking the adjusted color contrast as the current color contrast again, and continuing to perform the data acquisition step until multiple color contrasts within a specified time window and the RMSE value corresponding to each color contrast are acquired; the RMSE value represents a root mean square difference between test data and response data in a measurement test; a data fitting module, which is used to, according to the multiple color contrasts and the RMSE value corresponding to each color contrast, perform fitting using a cumulative normal distribution function, and estimate a contrast threshold parameter of the subject under the color dimension by using a second mathematical expectation of the distribution; and an evaluation value determination module, which is used to determine the contrast threshold parameter of the subject under different color dimensions as a color vision evaluation value corresponding to the subject.

[0021] In a third aspect, an embodiment of the application further provides an electronic device, including a processor and a memory, the memory stores computer executable instructions capable of being executed by the processor, and the processor executes the computer executable instructions to implement the method in the first aspect.

[0022] The color vision evaluation method, device and electronic equipment provided in the embodiments of the present application are as follows: the method is applied to a controller connected with a test palette; the test palette is used to present a stimulus color block of a specified color dimension at a random position of an image for each test, so that a subject makes a response to the random and continuous change of the position of the stimulus color block; the stimulus color block is formed by color blocks of multiple color dimensions being crossed and spaced, and the multiple color dimensions include a red-green color dimension, a yellow-blue color dimension or a black-white color dimension; the method comprises the following steps: for each color dimension, taking the color contrast of the stimulus color block in a first frame of image as a current color contrast, and performing the following data acquisition steps: acquiring response data of the subject when the subject performs color vision test through the stimulus color block under the current color contrast of the color dimension, and corresponding stimulus data; determining a current RMSE value under the current color contrast according to the response data and the stimulus data of the subject under the current color contrast; adjusting the color contrast of the stimulus color block in a next frame of image according to the size relationship between the current RMSE value and a predetermined judgment standard value, taking the adjusted color contrast as the current color contrast again, and continuing to perform the data acquisition steps until multiple color contrasts and the RMSE values corresponding to each color contrast in a specified time window are acquired; the RMSE value represents the root mean square difference between the test data and the response data in the measurement test; using a cumulative normal distribution function to fit the multiple color contrasts and the RMSE values corresponding to each color contrast, and estimating the contrast threshold parameter of the subject under the color dimension by using the second mathematical expectation of the distribution; and determining the contrast threshold parameters of the subject under different color dimensions as the color vision evaluation values corresponding to the subject. The color vision evaluation method provided in the embodiments of the present application can adjust the color contrast of the stimulus color block in the next frame of image according to the size relationship between the RMSE value of the subject under the current color contrast of the current stimulus color block and the judgment standard value, so that the RMSE value fluctuates within a certain range around the standard value, thereby acquiring the effective response data of the subject to the stimulus data, and then fitting the sequence data of the multiple color contrasts and the corresponding RMSE values determined based on the effective data by using the cumulative normal distribution function, to obtain the contrast threshold parameter, i.e., the color vision evaluation value. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative effort.

[0024] Figure 1 A schematic diagram of a stimulus color block provided in the embodiments of the present application;

[0025] Figure 2 A flow chart of a color vision evaluation method provided by an embodiment of the present application;

[0026] Figure 3 A flow chart of RMSE value calculation in a color vision evaluation method provided by an embodiment of the present application;

[0027] Figure 4 A flow chart of color contrast adjustment in a color vision evaluation method provided by an embodiment of the present application;

[0028] Figure 5 A flow chart of determination of a determination standard value in a color vision evaluation method provided by an embodiment of the present application;

[0029] Figure 6 A structural block diagram of a color vision evaluation device provided by an embodiment of the present application;

[0030] Figure 7 A structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0031] The technical solutions of the present application will be described in detail below with reference to the embodiments. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0032] In the existing color vision test method, since the color contrast of the stimulus color block is fixed, it is impossible to determine whether effective reaction data of the subject can be collected under the color contrast, which further leads to inaccurate color vision evaluation results of the subject.

[0033] Based on this, the embodiments of the present application provide a color vision evaluation method, device and electronic device, which can adjust the color contrast of the stimulus color block in the next frame of image based on the size relationship between the RMSE value of the subject under the current color contrast of the current stimulus color block and the determination standard value, so as to make the RMSE value fluctuate within a certain range around the standard value, thereby collecting effective reaction data of the subject to the stimulus data, and then fitting the sequence data of the multiple color contrasts and the corresponding RMSE values determined based on the effective data by using the cumulative normal distribution function, to obtain the contrast threshold parameter, i.e. the accurate color vision evaluation value.

[0034] To facilitate the understanding of the embodiments, first, a color vision evaluation method disclosed by the embodiments of the present application is described in detail.

[0035] The embodiment of the present application provides a color vision evaluation method, which is applied to a controller connected with a test palette; the test palette is used for presenting a stimulus color block of a specified color dimension at a random position of an image for each test, so that a subject makes a response to the random and continuous position change of the stimulus color block; the stimulus color block is formed by color blocks under multiple color dimensions being cross-spaced, and the multiple color dimensions include a red-green color dimension, a yellow-blue color dimension, or a black-white color dimension (i.e. a brightness dimension); the size of the stimulus color block can be ensured to be not less than a threshold value of the size of the visual angle of the subject.

[0036] Figure 1 Visual stimuli used in the embodiment of the present application are shown. On the test palette, red-green color blocks or blue-yellow color blocks are presented on a gray background with a size of 12.5°*12.5°, and the gray background is composed of 2500 color blocks, and the size of each color block is 20*20 pixels (0.25°*0.25°). The stimulus color block is composed of 5*5 color blocks, and the color of the color block in the figure is only used to distinguish two colors, and is not a real color. The color of the stimulus color block is taken from two axes of the DKL color space, that is, the red-green color is taken from the L-M axis, and the yellow-blue color is taken from the S-(L+M) axis. On the premise of ensuring that the brightness of the stimulus color block and the background is 60.7 cd / m2, the contrast of each color is converted into an axis percentage contrast, and the range is 0-100%.

[0037] Figure 2 A flowchart of a color vision evaluation method provided by the embodiment of the present application is shown, and the method specifically includes the following steps:

[0038] In step S202, for each color dimension, the color contrast of the stimulus color block in the first frame of image is taken as a current color contrast, and the following data acquisition steps are performed: acquiring response data of the subject when the subject performs color vision test through the stimulus color block under the current color contrast of the color dimension, and corresponding stimulus data; determining a current RMSE value under the current color contrast according to the response data and the stimulus data of the subject under the current color contrast; adjusting the color contrast of the stimulus color block in the next frame of image according to the size relationship between the current RMSE value and a predetermined judgment standard value, taking the adjusted color contrast as the current color contrast again, and continuing to perform the data acquisition step, until a plurality of color contrasts in a specified time window and the RMSE value corresponding to each color contrast are acquired; the RMSE value represents the root mean square difference between the test data and the response data in the measurement test;

[0039] The above steps are a process of testing the subject by the stimulus color block under each color dimension to obtain test data under each color dimension. The test data includes stimulus data of the stimulus color block and reaction data of the subject; the stimulus data includes continuously changing test positions of the stimulus color block in the image; and the reaction data includes reaction positions corresponding to each of the continuously changing test positions.

[0040] In a specific test, the current RMSE value under the current color contrast is calculated according to the reaction data and the stimulus data of the subject under the current color contrast in a detection window; then, the color contrast of the stimulus color block in the next frame of image is adjusted according to the size relationship between the current RMSE value under the current color contrast and the pre-calibrated judgment standard value, and then the test is continued by the adjusted stimulus color block to enable the subject to make a corresponding tracking reaction, and the stimulus data and the reaction data under the next color contrast are obtained again, and so on. Finally, a data sequence, a color contrast sequence and a corresponding RMSE value sequence can be obtained.

[0041] The above RMSE value is calculated based on the test data (including stimulus data and reaction data) obtained after the subject is tested in a detection time window under the same color contrast. The above RMSE value can be regarded as a judgment parameter for whether the color vision test data is effective. If the RMSE value is too low, the stimulus is too simple, and if the RMSE value is too high, the subject can hardly see the stimulus and cannot obtain effective test data. Therefore, in the embodiment, the adjustment of the subsequent stimulus color block needs to be continuously performed according to the size relationship between the RMSE value and the judgment standard value, so that the calculated RMSE value is always maintained within a certain range of the judgment standard value. In this way, the stimulus test effect can be best, the reaction data of the subject obtained is most effective, and thus the effective color contrast sequence and the corresponding RMSE value sequence can be obtained, so as to accurately evaluate the color vision subsequently.

[0042] In step S204, the cumulative normal distribution function is used to fit according to the plurality of color contrasts and the RMSE value corresponding to each color contrast, and the second mathematical expectation of the distribution is used to estimate the contrast threshold parameter of the subject under the color dimension.

[0043] In step S206, the contrast threshold parameters of the subject under different color dimensions are determined as the color vision evaluation values corresponding to the subject.

[0044] The color vision evaluation method provided by the embodiments of the present application can adjust the color contrast of the stimulus color block in the next frame of image based on the size relationship between the RMSE value of the subject under the current color contrast of the stimulus color block and the determination standard value, so as to make the RMSE value fluctuate within a certain range around the standard value, thereby collecting effective reaction data of the subject to the stimulus data, and then fitting the sequence data of the plurality of color contrasts and the corresponding RMSE values determined based on the effective data by using the cumulative normal distribution function, to obtain the contrast threshold parameter, that is, the accurate color vision evaluation value.

[0045] Referring to Figure 3 The step of determining the current RMSE value under the current color contrast according to the reaction data and the stimulus data of the subject under the current color contrast specifically includes:

[0046] In step S302, the motion reaction delay is determined by using the cross-correlation method according to the reaction data and the stimulus data of the subject under the current color contrast.

[0047] In step S304, the root mean square difference between the stimulus data and the reaction data is calculated as the current RMSE value under the current color contrast based on the reaction data and the stimulus data under the current color contrast and the motion reaction delay.

[0048] Specifically, the root mean square difference RMSE between the stimulus data and the reaction data is calculated according to the following first designated formula:

[0049]

[0050] Wherein, I t represents the reaction position of the subject at t test moment, s t-Δt represents the stimulus position at t-Δt moment, Δt represents the motion reaction delay, and N represents the total frame number corresponding to the time window under the current color contrast.

[0051] The RMSE value calculation process under the measurement trial is shown above. In the embodiments, the time window used for the measurement trial is 600 ms, and N is 51 frames, that is, the total frame number of the set time window. 600 ms is the time when the performance of the subject is indeed lower than the determination standard d. This setting ensures that the stimulus contrast is reduced below the threshold value.

[0052] Referring to Figure 4 The step of adjusting the color contrast of the stimulus color block in the next frame of image according to the size relationship between the current RMSE value and the pre-determined determination standard value specifically includes:

[0053] Step S402, if the current RMSE value is greater than the determination standard value, the color contrast of the stimulus color block in the next frame of image is reduced by a preset step size;

[0054] Step S404, if the current RMSE value is less than the determination standard value, the color contrast of the stimulus color block in the next frame of image is increased by a preset step size.

[0055] Further, the determination method of the preset step size is as follows: the preset step size step is determined according to the following second designated formula:

[0056]

[0057] Wherein, C s represents the current color contrast of the stimulus color block in the current frame of image, b2 and b3 are parameters of the overall size of the slope and step size of the adjustment step size.

[0058] The change step size step increases exponentially with the stimulus contrast, and changes slowly when the stimulus contrast is close to the threshold range, so as to increase the accuracy of threshold estimation, and changes rapidly when the stimulus contrast is far higher than the threshold range, so as to facilitate the subject to quickly find the stimulus.

[0059] Specifically, the parameter values used in different color dimensions are shown in Table 1:

[0060] Table 1

[0061]

[0062] Referring to Figure 5 The determination process of the determination standard value is as follows:

[0063] Step S502, for the color dimension, a corresponding calibration trial is set; the calibration trial is a trial in which the contrast does not change with the performance, and the measurement trial is a trial in which the contrast changes with the performance of the subject.

[0064] Step S504, the reaction data and the stimulus data of the subject in the calibration trial are obtained;

[0065] Step S506, the calibration trial RMSE value is determined according to the reaction data and the stimulus data in the calibration trial; the calibration trial RMSE value represents the root mean square difference between the test data and the reaction data in the calibration trial;

[0066] The calculation process of the calibration trial RMSE value is the same as the calculation process of the aforementioned measurement trial, and the calibration trial contrast does not change with the RMSE of the reaction position and the stimulus position of the subject. The time window for calculating the calibration trial RMSE value is 60s, i.e. all 5100 frames, which is used to determine the determination standard value of the subsequent measurement trial.

[0067] Step S508, according to the calibration trial RMSE value, the color dimension under the measured trial of the determination criterion value. Specifically, according to the following third designated formula, the determination criterion value d of the measured trial under the color dimension is calculated:

[0068] d = (1 + b1) RMSE';

[0069] Wherein, b1 represents a parameter for representing the strictness of the determination criterion; b1 is different under different color dimensions; RMSE' represents the calibration trial RMSE value.

[0070] The strictness b1 of the determination criterion is adjusted in the debugging process, so that the stimulus contrast can be reduced below the threshold of the subject. If the measured trial RMSE value is higher than the determination criterion value, it is considered that the subject can see and track the spot, and the subject threshold is below the contrast at this moment, so the next frame stimulus contrast is reduced, otherwise the next frame stimulus contrast is increased.

[0071] Specifically, the parameter values used under different color dimensions are shown in Table 2:

[0072] Table 2

[0073]

[0074] Further, the above step of fitting using the cumulative normal distribution function according to the plurality of color contrasts and the RMSE value corresponding to each color contrast, and estimating the contrast threshold parameter of the subject under the color dimension by the second mathematical expectation of the distribution, includes:

[0075] (1) According to the RMSE value corresponding to each color contrast, determine the F value corresponding to each color contrast; F value represents the RMSE under the color contrast of the next frame image, which is reduced or increased relative to the RMSE under the color contrast of the current frame;

[0076] (2) Substitute the plurality of color contrasts and the corresponding F values into the following fourth designated formula to determine the contrast threshold parameter of the subject under the color dimension:

[0077]

[0078] Wherein, x represents the color contrast of the stimulus color block under the current color dimension, F N (x|α,β) = 0 or 1; 0 represents that the RMSE under the color contrast of the next frame image is increased relative to the RMSE under the color contrast of the current frame; 1 represents that the RMSE under the color contrast of the next frame image is reduced relative to the RMSE under the color contrast of the current frame; α represents the contrast threshold of the subject under the color dimension; β is proportional to y = F Nderivative of the function at (a,a, b); wherein a and b are both contrast threshold parameters.

[0079] Taking the red-green color dimension as an example, first, a calibration trial is performed, in which the stimulus contrast does not change with the performance of the subject, and the RMSE value of the calibration trial calculated from the trial is used to determine the parameters used in the subsequent measurement trials. Each measurement trial is 60 seconds, and there are 5100 frames, and the contrast of each frame is changed according to the performance of the subject in the previous frame to obtain as much information as possible. After the test, a 5100x1 logical matrix is obtained according to whether the RMSE of each frame in the measurement trial increases, which is used as the reaction input of the subject, and the contrast of each frame is used as the stimulus intensity input. The stimulus contrast at which the RMSE of the subject has a 50% chance of increasing and a 50% chance of decreasing is extracted as the contrast threshold of the subject in the color dimension.

[0080] Finally, the calculated a and b in each color dimension are determined as the color vision evaluation value of the subject.

[0081] In the color vision evaluation method provided by the embodiments of the present application, for different color dimensions, the color contrast of the stimulus color block in the next frame of image can be adjusted based on the size relationship between the RMSE value of the subject under the current color contrast of the current stimulus color block and the determination standard value, so that the RMSE value fluctuates within a certain range around the standard value, thereby collecting effective reaction data of the subject to the stimulus data, and then obtaining the color contrast sequence and the corresponding RMSE value sequence based on the effective data, and finally fitting the color contrast sequence and the corresponding RMSE value sequence by the cumulative normal distribution function to obtain the contrast threshold parameters (such as the aforementioned a and b) as the accurate color vision evaluation value of the subject.

[0082] Based on the above method embodiments, the embodiments of the present application also provide a color vision evaluation device, which is applied to a controller connected with a test panel; the test panel is used to present a stimulus color block of a specified color dimension at a random position of an image for each trial, so that the subject makes a reaction to the random and continuous change of the position of the stimulus color block; the stimulus color block is formed by color blocks of multiple color dimensions being crossed and spaced, and the multiple color dimensions include a red-green color dimension, a yellow-blue color dimension, or a black-white color dimension; as shown in the figure, the device comprises: Figure 6

[0083] ​The data acquisition module 62 is configured to, for each color dimension, take the color contrast of the stimulus color block in the first frame of image as a current color contrast, and perform the following data acquisition steps: acquire reaction data of the subject when the subject performs the color vision test on the stimulus color block under the current color contrast in the color dimension, and corresponding stimulus data; determine a current RMSE value under the current color contrast according to the reaction data and the stimulus data of the subject under the current color contrast; adjust the color contrast of the stimulus color block in the next frame of image according to the size relationship between the current RMSE value and a predetermined judgment standard value, take the adjusted color contrast as the current color contrast again, and continue to perform the data acquisition steps until a plurality of color contrasts within a specified time window and the RMSE value corresponding to each color contrast are acquired; the RMSE value represents the root mean square difference between the test data and the reaction data in the measurement trial; the data fitting module 64 is configured to use a cumulative normal distribution function to fit according to the plurality of color contrasts and the RMSE value corresponding to each color contrast, and estimate the contrast threshold parameter of the subject under the color dimension by using the second mathematical expectation of the distribution; the evaluation value determination module 66 is configured to determine the contrast threshold parameter of the subject under different color dimensions as the color vision evaluation value corresponding to the subject.

[0084] Further, the data acquisition module 62 is configured to determine the action reaction delay by using a cross-correlation method according to the reaction data and the stimulus data of the subject under the current color contrast; and calculate the root mean square difference between the stimulus data and the reaction data as the current RMSE value under the current color contrast based on the reaction data and the stimulus data under the current color contrast and the action reaction delay.

[0085] Further, the data acquisition module 62 is configured to calculate the root mean square difference RMSE between the stimulus data and the reaction data according to the following first specified formula:

[0086]

[0087] wherein, I t represents the reaction position of the subject at t test moment, s t-Δt represents the stimulus position at t-Δt moment, Δt represents the action reaction delay, and N represents the total frame number corresponding to the time window under the current color contrast.

[0088] Further, the data acquisition module 62 is configured to, if the current RMSE value is greater than the judgment standard value, reduce the color contrast of the stimulus color block in the next frame of image by a preset step size; and if the current RMSE value is less than the judgment standard value, increase the color contrast of the stimulus color block in the next frame of image by a preset step size.

[0089] Further, the preset step length is determined as follows: the preset step length step is determined according to the following second designated formula:

[0090]

[0091] wherein, C s represents the current color contrast of the stimulus color block in the current frame image, b2 and b3 are parameters of the slope and the overall size of the step length, respectively.

[0092] Further, the determination process of the determination standard value is as follows: for the color dimension, a corresponding calibration trial is set; the reaction data and the stimulus data of the subject in the calibration trial are obtained; the calibration trial RMSE value is determined according to the reaction data and the stimulus data in the calibration trial; the calibration trial RMSE value represents the root mean square error between the test data and the reaction data in the calibration trial; and the determination standard value of the measurement trial in the color dimension is calculated according to the calibration trial RMSE value.

[0093] Further, the data acquisition module 62 is configured to calculate the determination standard value d of the measurement trial in the color dimension according to the following third designated formula:

[0094] d = (1 + b1) RMSE';

[0095] wherein, b1 represents a parameter for representing the strictness of the determination standard; b1 is different in different color dimensions; and RMSE' represents the calibration trial RMSE value.

[0096] Further, the data fitting module 64 is configured to determine the F value corresponding to each color contrast according to the RMSE value corresponding to each color contrast; the F value represents the RMSE at the color contrast of the next frame image, which is reduced or increased relative to the RMSE at the color contrast of the current frame; and the plurality of color contrasts and the corresponding F values are substituted into the following fourth designated formula to determine the contrast threshold parameter of the subject in the color dimension:

[0097]

[0098] wherein, x represents the color contrast of the stimulus color block in the current color dimension, F N (x|α,β) = 0 or 1; 0 represents that the RMSE at the color contrast of the next frame image is increased relative to the RMSE at the color contrast of the current frame; 1 represents that the RMSE at the color contrast of the next frame image is reduced relative to the RMSE at the color contrast of the current frame; α represents the contrast threshold of the subject in the color dimension; and β is proportional to y = F N the derivative of the function at (α|α,β); wherein, both α and β are contrast threshold parameters.

[0099] The device provided in this application embodiment has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts of the device embodiment not mentioned can be referred to the corresponding content in the aforementioned method embodiment.

[0100] This application also provides an electronic device, such as... Figure 7 The diagram shows the structure of the electronic device, which includes a processor 71 and a memory 70. The memory 70 stores computer-executable instructions that can be executed by the processor 71, and the processor 71 executes the computer-executable instructions to implement the above-described method.

[0101] exist Figure 7 In the illustrated embodiment, the electronic device further includes a bus 72 and a communication interface 73, wherein the processor 71, the communication interface 73, and the memory 70 are connected via the bus 72.

[0102] The memory 70 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 73 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 72 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 72 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0103] The processor 71 can be an integrated circuit chip with signal processing capability. In the implementation process, the steps of the above method can be completed by the integrated logic circuit of hardware in the processor 71 or the instruction in the form of software. The processor 71 described above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory or an electrically erasable programmable memory, a register, etc. The storage medium in the memory is read by the processor 71, and the hardware thereof is combined to complete the steps of the method of the foregoing embodiments.

[0104] The embodiment of the present application further provides a computer readable storage medium, which stores computer executable instructions. When the computer executable instructions are called and executed by a processor, the computer executable instructions cause the processor to implement the above method. For details, refer to the foregoing method embodiments, which will not be described here.

[0105] The computer program product of the method, device and electronic equipment provided by the embodiment of the present application includes a computer readable storage medium storing program codes. The instructions included in the program codes can be used to execute the method described in the foregoing method embodiments. For details, refer to the method embodiments, which will not be described here.

[0106] Unless otherwise specifically stated, the relative steps, numerical expressions and numerical values of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0107] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a nonvolatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present application or the part of the prior art that essentially contributes to the prior art or the part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various storage medium that can store program codes.

[0108] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the purpose of facilitating the description of the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", "third" are only for the purpose of description, and cannot be understood as indicating or implying relative importance.

[0109] Finally, it should be noted that: the above-described embodiments are only specific embodiments of the present application, used to illustrate the technical solutions of the present application, and are not limited thereto, the protection scope of the present application is not limited thereto, although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art within the technical scope disclosed by the present application can modify or easily think of changes to the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to part of the technical features; and these modifications, changes or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for assessing color vision, characterized in that, The method is applied to a controller connected to a test chart; the test chart is used to present stimulus color patches of a specified color dimension at random locations on an image for each trial, so that the subject can track and respond to the randomly and continuously changing positions of the stimulus color patches; the stimulus color patches are formed by the interleaving of color patches under multiple color dimensions, including red-green color dimension, yellow-blue color dimension, or black-and-white color dimension; the method includes: For each color dimension, the color contrast of the stimulus patch in the first frame image is used as the current color contrast. The following data acquisition steps are performed: acquire the subject's response data when performing a color vision test using the stimulus patch at the current color contrast in the color dimension, as well as the corresponding stimulus data; determine the current RMSE value at the current color contrast based on the subject's response data and stimulus data; adjust the color contrast of the stimulus patch in the next frame image according to the relationship between the current RMSE value and a predetermined judgment standard value, and use the adjusted color contrast as the current color contrast again. Continue performing the data acquisition steps until multiple color contrasts and the RMSE value corresponding to each color contrast are acquired within a specified time window; the RMSE value represents the root mean square difference between the test data and the response data in the measurement trials. Based on multiple color contrasts and the RMSE value corresponding to each color contrast, a cumulative normal distribution function is used for fitting, and the second-order mathematical expectation of the distribution is used to estimate the contrast threshold parameter of the subject in the color dimension. The contrast threshold parameters of the subjects under different color dimensions are determined as the color vision assessment values ​​corresponding to the subjects.

2. The method according to claim 1, characterized in that, The step of determining the current RMSE value at the current color contrast based on the subject's response data and stimulus data at the current color contrast includes: Based on the subject's response data and stimulus data at the current color contrast, the cross-correlation method was used to determine the action response delay; Based on the response data and stimulus data under the current color contrast and the action response delay, the root mean square difference between the stimulus data and the response data is calculated as the current RMSE value under the current color contrast.

3. The method according to claim 2, characterized in that, The step of calculating the root mean square difference between the stimulus data and the response data based on the response data and stimulus data under the current color contrast and the action response delay includes: Calculate the root mean square error (RMSE) between the stimulus and response data using the first specified formula below: Among them, I t Indicates the subject's position at time t during the test, s t-Δt The value represents the stimulus location at time t-Δt, where Δt represents the action response delay, and N represents the total number of frames corresponding to the time window under the current color contrast.

4. The method according to claim 1, characterized in that, The step of adjusting the color contrast of stimulus color patches in the next frame image based on the relationship between the current RMSE value and a predetermined judgment standard value includes: If the current RMSE value is greater than the judgment standard value, the color contrast of the stimulating color block in the next frame image is reduced by a preset step size; If the current RMSE value is less than the judgment criterion value, the color contrast of the stimulating color blocks in the next frame image is increased by a preset step size.

5. The method according to claim 4, characterized in that, The preset step size is determined as follows: Determine the preset step size step according to the following second specified formula: Among them, C s b1 represents the current color contrast of the stimulus color block in the current frame image, and b2 and b3 are parameters for adjusting the slope and the overall size of the step size, respectively.

6. The method according to claim 1, characterized in that, The process for determining the judgment criterion value is as follows: For the aforementioned color dimension, set the corresponding number of calibration trials; Acquire the subject's response data and stimulus data under the calibrated trials; The RMSE value of the calibration trial is determined based on the response data and stimulus data under the calibration trial; the RMSE value of the calibration trial represents the root mean square difference between the test data and the response data in the calibration trial. Based on the RMSE value of the calibration test, calculate the judgment standard value of the measurement test under the color dimension.

7. The method according to claim 6, characterized in that, The step of calculating the judgment standard value of the measurement test under the color dimension based on the RM SE value of the calibration test includes: Calculate the criterion value d for the measurement trials in the color dimension according to the following third specified formula: d = (1 + b1)RMSE'; Wherein, b1 represents the parameter used to characterize the strictness of the judgment standard; b1 is different for different color dimensions; RMSE′ represents the RMSE value of the calibration test.

8. The method according to claim 1, characterized in that, The steps of fitting a cumulative normal distribution function to multiple color contrasts and the corresponding RMSE values ​​for each color contrast, and estimating the contrast threshold parameter of the subject in the color dimension using the second-order mathematical expectation of the distribution, include: Based on the RMSE value corresponding to each color contrast, determine the F value corresponding to each of the multiple color contrasts; the F value represents the RMSE under the color contrast of the next frame image, which may decrease or increase compared to the RMSE under the color contrast of the current frame. Substitute multiple color contrast ratios and their corresponding F-values ​​into the following fourth specified formula to determine the contrast threshold parameter for the subject in the color dimension: Where x represents the color contrast of the stimulus color patch in the current color dimension, and F N (x|α,β) = 0 or 1; 0 indicates that the RMSE in the next frame is greater than the RMSE in the current frame; 1 indicates that the RMSE in the next frame is less than the RMSE in the current frame; α represents the contrast threshold of the subject in the stated color dimension; β is proportional to y = F N The derivative of the function at (α|α,β); where α and β are contrast threshold parameters.

9. A color vision assessment device, characterized in that, The device is used in a controller connected to a test chart; the test chart is used to present stimulus color patches of a specified color dimension at random locations on an image for each trial, so that the subject can track and respond to the randomly and continuously changing positions of the stimulus color patches; the stimulus color patches are formed by the interleaving of color patches under multiple color dimensions, including red-green color dimension, yellow-blue color dimension, or black-and-white color dimension; the device includes: The data acquisition module is used to, for each color dimension, take the color contrast of the stimulus color patch in the first frame image as the current color contrast, and perform the following data acquisition steps: acquire the subject's reaction data when performing a color vision test through the stimulus color patch at the current color contrast in the color dimension, and the corresponding stimulus data; determine the current RMSE value at the current color contrast based on the subject's reaction data and stimulus data; adjust the color contrast of the stimulus color patch in the next frame image according to the relationship between the current RMSE value and a predetermined judgment standard value, and use the adjusted color contrast as the current color contrast again, continuing to perform the data acquisition steps until multiple color contrasts and the RMSE value corresponding to each color contrast are acquired within a specified time window; the RMSE value represents the root mean square difference between the test data and the reaction data in the measurement trials; The data fitting module is used to fit the data using a cumulative normal distribution function based on multiple color contrasts and the RMSE value corresponding to each color contrast, and to estimate the contrast threshold parameter of the subject in the color dimension using the second-order mathematical expectation of the distribution. The evaluation value determination module is used to determine the contrast threshold parameters of the subject under different color dimensions as the color vision evaluation value corresponding to the subject.

10. An electronic device, characterized in that, The method includes a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the method of any one of claims 1 to 8.

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