Color vision evaluation method and device and electronic equipment

Abstract

The invention provides a color vision evaluation method and device and electronic equipment. The method is applied to a controller connected with a test drawing board. The test drawing board is used for presenting a stimulation color block with a specified color dimension at a random position of the image in each test time, so that a subject responds to tracking the randomly and continuously changing position of the stimulation color block; the stimulation color block is formed by color blocks in multiple color dimensions at intervals in a crossed mode, and the method comprises the steps that for each color dimension, the color contrast of a next frame is adjusted based on the size relation between the RMSE value of a subject under the current color contrast of the stimulation color block and a judgment standard value, so that the RMSE value fluctuates within a certain range close to the standard value, and the RMSE value fluctuates within a certain range close to the judgment standard value; according to the method, effective response data of a subject is collected, and a plurality of color contrasts determined based on the effective data and sequence data of corresponding RMSE values are fitted through a cumulative normal distribution function to obtain a contrast threshold parameter, namely an accurate color vision evaluation value.

Description

Technical Field

[0001] The present application relates to the technical field of color testing, and in particular to a color vision assessment method, device and electronic equipment. Background Art

[0002] In the existing color vision test method, it is necessary to set a stimulus color block in the image, and then control the stimulus color block to continuously change at different positions in the image; during the test, the subject is required to track and respond to the stimulus color block that is constantly changing position, so as to evaluate the subject's color vision. However, there is a problem with this method. Since the color contrast of the stimulus color block is fixed, it is impossible to determine whether effective response data for the subject can be collected under this color contrast, which leads to inaccurate color vision evaluation results for the subject. Summary of the invention

[0003] The purpose of the present application is to provide a color vision assessment method, device and electronic device, which can adjust the color contrast of the stimulus color block in the next frame image based on the size relationship between the RMSE value of the subject at 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 collecting the subject's effective response data to the stimulus data, and then fitting the sequence data of multiple color contrasts and corresponding RMSE values ​​determined based on the effective data through the cumulative normal distribution function to obtain the contrast threshold parameter, that is, the accurate color vision assessment value.

[0004] In a first aspect, an embodiment of the present application provides a color vision assessment method, which is applied to a controller connected to 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 trial, so that the subject tracks and responds to the random and continuous changing position of the stimulus color block; the stimulus color block is formed by intersecting color blocks under multiple color dimensions, and the multiple color dimensions include red-green color dimensions, yellow-blue color dimensions, or black-white color dimensions; the method includes: for each color dimension, taking the color contrast of the stimulus color block in the first frame image as the current color contrast, and performing the following data acquisition steps: acquiring the subject's reaction data when performing a color vision test using the stimulus color block under the current color contrast under the color dimension, and the corresponding stimulus data; according to the subject's reaction data and stimulus data under the current color contrast , determine the current RMSE value under the current color contrast; according to the size relationship between the current RMSE value and the predetermined judgment standard value, adjust the color contrast of the stimulus color block in the next frame image, use the adjusted color contrast as the current color contrast again, and continue to execute the data acquisition step until multiple color contrasts in the specified time window and the RMSE value corresponding to each color contrast are obtained; the RMSE value represents the root mean square difference between the test data and the response data in the measurement trial; according to the multiple color contrasts and the RMSE value corresponding to each color contrast, use the cumulative normal distribution function to fit, and use the secondary mathematical expectation of the distribution to estimate the contrast threshold parameters of the subject in the color dimension; the contrast threshold parameters of the subject in different color dimensions are determined as the corresponding color vision evaluation value of the subject.

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

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

[0007]

[0008] Among them, I t represents the subject's response position at the test time t, s t-Δtrepresents the stimulus position at time t-Δt, Δt represents the action response delay, and N represents the total number of frames corresponding to the time window under the current color contrast.

[0009] Furthermore, the above-mentioned step of adjusting the color contrast of the stimulus color block in the next frame image according to the size relationship between the current RMSE value and the predetermined judgment standard value includes: if the current RMSE value is greater than the judgment standard value, reducing the color contrast of the stimulus color block in the next frame image according to a preset step size; if the current RMSE value is less than the judgment standard value, increasing the color contrast of the stimulus color block in the next frame image according to a preset step size.

[0010] Furthermore, the above-mentioned preset step length is determined as follows: the preset step length step is determined according to the following second specified formula:

[0011]

[0012] Among them, C s It represents the current color contrast of the stimulus color block in the current frame image. b2 and b3 are the parameters for adjusting the slope of the step length and the overall size of the step length, respectively.

[0013] Furthermore, the process of determining the above-mentioned judgment standard value is as follows: for the color dimension, set the corresponding calibration trial; obtain the reaction data and stimulus data of the subject in the calibration trial; determine the RMSE value of the calibration trial based on the reaction data and stimulus data in the calibration trial; the RMSE value of the calibration trial represents the root mean square difference between the test data and the reaction data in the calibration trial; and calculate the judgment standard value of the measurement trial under the color dimension based on the RMSE value of the calibration trial.

[0014] Furthermore, the step of calculating the judgment standard value of the measurement trial in the color dimension according to the RMSE value of the calibration trial includes: calculating the judgment standard value d of the measurement trial in the color dimension according to the following third specified formula:

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

[0016] Among them, b1 represents the parameter used to characterize the strictness of the judgment standard; b1 is different in different color dimensions; RMSE′ represents the RMSE value of the calibration test.

[0017] Furthermore, the above-mentioned step of fitting using a cumulative normal distribution function according to multiple color contrasts and the RMSE value corresponding to each color contrast, and estimating the contrast threshold parameter of the subject in the color dimension by the secondary mathematical expectation of the distribution includes: determining the F values ​​corresponding to the multiple color contrasts respectively according to the RMSE value corresponding to each color contrast; the F value represents the RMSE under the color contrast of the next frame image, which decreases or increases relative to the RMSE under the color contrast of the current frame; substituting the multiple color contrasts and the corresponding F values ​​into the following fourth specified formula to determine the contrast threshold parameter of the subject in the color dimension:

[0018]

[0019] Among them, x represents the color contrast of the stimulus color block in the current color dimension, F N (x|α,β)=0 or 1; 0 means the RMSE under the color contrast of the next frame image increases relative to the color contrast of the current frame; 1 means the RMSE under the color contrast of the next frame image decreases relative to the color contrast of the current frame; α means the contrast threshold of the subject in the 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.

[0020] In a second aspect, the present application further provides a color vision assessment device, which is applied to a controller connected to 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 trial, so that the subject can track and respond to the random and continuous changes in the position of the stimulus color block; the stimulus color block is formed by the cross-interval of color blocks under multiple color dimensions, and the multiple color dimensions include red and green color dimensions, yellow and blue color dimensions, or black and white color dimensions; the device includes: a data acquisition module, which is used to use the color contrast of the stimulus color block in the first frame image as the current color contrast for each color dimension, and perform the following data acquisition steps: obtain the subject's reaction data when performing a color vision test using the stimulus color block under the current color contrast under the color dimension, and the corresponding stimulus data; determine the current color contrast according to the subject's reaction data and stimulus data under the current color contrast. The current RMSE value under color contrast; according to the size relationship between the current RMSE value and the predetermined judgment standard value, the color contrast of the stimulus color block in the next frame of the image is adjusted, the adjusted color contrast is used again as the current color contrast, and the data acquisition step is continued until multiple color contrasts in the specified time window and the RMSE value corresponding to each color contrast are obtained; the RMSE value represents the root mean square difference between the test data and the response data in the measurement trial; a data fitting module is used to fit according to multiple color contrasts and the RMSE value corresponding to each color contrast using the cumulative normal distribution function, and estimate the contrast threshold parameters of the subject in the color dimension with the secondary mathematical expectation of the distribution; an evaluation value determination module is used to determine the contrast threshold parameters of the subject in different color dimensions as the corresponding color vision evaluation value of the subject.

[0021] In a third aspect, an embodiment of the present application further provides an electronic device, including a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the method described in the first aspect above.

[0022] In the color vision assessment method, device and electronic device provided in the embodiments of the present application, the method is applied to a controller connected to 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 trial, so that the subject can track and respond to the random and continuous change of the position of the stimulus color block; the stimulus color block is formed by the cross-interval of color blocks under multiple color dimensions, and the multiple color dimensions include red and green color dimensions, yellow and blue color dimensions or black and white color dimensions; the method includes: for each color dimension, taking the color contrast of the stimulus color block in the first frame image as the current color contrast, performing the following data acquisition steps: acquiring the reaction data of the subject when the color vision test is performed by the stimulus color block under the current color contrast under the color dimension, and the corresponding stimulus data; according to the reaction data of the subject under the current color contrast and the stimulus data, determine the current RMSE value under the current color contrast; according to the size relationship between the current RMSE value and the predetermined judgment standard value, adjust the color contrast of the stimulus color block in the next frame image, use the adjusted color contrast as the current color contrast again, and continue to execute the data acquisition step until multiple color contrasts in the specified time window and the RMSE value corresponding to each color contrast are obtained; the RMSE value represents the root mean square difference between the test data and the response data in the measurement trial; according to the multiple color contrasts and the RMSE value corresponding to each color contrast, use the cumulative normal distribution function to fit, and use the secondary mathematical expectation of the distribution to estimate the contrast threshold parameters of the subject in the color dimension; the contrast threshold parameters of the subject in different color dimensions are determined as the corresponding color vision evaluation value of the subject. The color vision assessment method provided in the embodiment of the present application can adjust the color contrast of the stimulus color block in the next frame image based on the size relationship between the RMSE value of the subject at 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 collecting effective subject response data to the stimulus data, and then fitting the sequence data of multiple color contrasts and corresponding RMSE values ​​determined based on the effective data through the cumulative normal distribution function to obtain the contrast threshold parameter, that is, the color vision assessment value. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

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

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

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

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

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

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

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

[0031] The technical solution of the present application will be described clearly and completely below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0032] In existing color vision testing methods, since the color contrast of the stimulus color blocks is fixed, it is impossible to determine whether effective response data of the subject can be collected under this color contrast, which leads to inaccurate color vision evaluation results for the subject.

[0033] Based on this, the embodiments of the present application provide a color vision assessment method, device and electronic device, which can adjust the color contrast of the stimulus color block in the next frame 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 judgment standard value, so that the RMSE value fluctuates within a certain range around the standard value, thereby collecting the subject's effective response data to the stimulus data, and then fitting the sequence data of multiple color contrasts and corresponding RMSE values ​​determined based on the effective data through the cumulative normal distribution function to obtain the contrast threshold parameter, that is, the accurate color vision assessment value.

[0034] To facilitate understanding of this embodiment, a color vision assessment method disclosed in an embodiment of the present application is first introduced in detail.

[0035] An embodiment of the present application provides a color vision assessment method, which is applied to a controller connected to 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 trial, so that the subject tracks and responds to the random and continuous changing position of the stimulus color block; the stimulus color block is formed by cross-intervals of color blocks in multiple color dimensions, and the multiple color dimensions include a red-green color dimension, a yellow-blue color dimension, or a black-and-white color dimension (i.e., a brightness dimension); the size of the stimulus color block only needs to ensure that the size of the subject's viewing angle is not less than a threshold.

[0036] Figure 1 The visual stimulus used in the embodiment of the present application is shown. On the test drawing board, a red-green block or a blue-yellow block is presented on a gray background of 12.5°×12.5°. A total of 2500 color blocks make up the gray background, 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. The color of the color block in the figure is only used to distinguish between the two colors, and is not the real color. The color of the stimulus color block is taken from the two axes of the DKL color space, that is, the red and green colors are taken from the LM axis, and the yellow and blue colors are taken from the S-(L+M) axis. On the premise of ensuring that the brightness of the stimulus color block and the background is 60.7cd / m2, the contrast of each color is converted into an axis percentage contrast, which ranges from 0 to 100%.

[0037] Figure 2 A flow chart of a color vision evaluation method provided in an embodiment of the present application is shown, and the method specifically comprises the following steps:

[0038] Step S202, for each color dimension, the color contrast of the stimulus color block in the first frame image is used as the current color contrast, and the following data acquisition steps are performed: the reaction data of the subject when the color vision test is performed through the stimulus color block under the current color contrast under the color dimension, and the corresponding stimulus data are obtained; according to the reaction data and stimulus data of the subject under the current color contrast, the current RMSE value under the current color contrast is determined; according to the size relationship between the current RMSE value and the predetermined judgment standard value, the color contrast of the stimulus color block in the next frame image is adjusted, and the adjusted color contrast is used again as the current color contrast, and the data acquisition steps are continued until multiple color contrasts within the specified time window and the RMSE value corresponding to each color contrast are obtained; the RMSE value represents the root mean square difference between the test data and the reaction data in the measurement trial;

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

[0040] In the specific test, the current RMSE value under the current color contrast is calculated based on the subject's reaction data and stimulus data in a detection window under the current color contrast; then, based on the relationship between the current RMSE value under the current color contrast and the pre-calibrated judgment standard value, the color contrast of the stimulus color block in the next frame of the image is adjusted, and then the test is continued with the adjusted stimulus color block to enable the subject to make a corresponding tracking response, and the stimulus data and reaction data under the next frame of 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 response data) obtained after the test of the subject within 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 valid. If the RMSE value is too low, it indicates that the stimulus is too simple. If the RMSE value is too high, it indicates that the subject can hardly see the stimulus and cannot obtain valid test data. Therefore, in this embodiment, it is necessary to continuously adjust the subsequent stimulus color blocks according to the size relationship between the RMSE value and the judgment standard value, so that the calculated RMSE value is always kept within a certain range of the judgment standard value. In this way, the best stimulus test effect can be guaranteed, and the most effective reaction data of the subject can be obtained, so that an effective color contrast sequence and a corresponding RMSE value sequence can be obtained, so as to perform accurate color vision evaluation later.

[0042] Step S204, using a cumulative normal distribution function to perform fitting based on multiple color contrasts and the RMSE value corresponding to each color contrast, and using the secondary mathematical expectation of the distribution to estimate the contrast threshold parameter of the subject in the color dimension;

[0043] Step S206: Determine the contrast threshold parameters of the subject in different color dimensions as the color vision evaluation values ​​corresponding to the subject.

[0044] In a color vision assessment method provided in an embodiment of the present application, for different color dimensions, the color contrast of the stimulus color block in the next frame image can be adjusted based on the size relationship between the subject's RMSE value 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 collecting the subject's effective response data to the stimulus data, and then fitting the sequence data of multiple color contrasts and corresponding RMSE values ​​determined based on the effective data through the cumulative normal distribution function to obtain the contrast threshold parameter, that is, the accurate color vision assessment value.

[0045] See also Figure 3 As shown, the above step of determining the current RMSE value under the current color contrast according to the subject's reaction data and stimulus data under the current color contrast specifically includes:

[0046] Step S302, determining the action response delay using a cross-correlation method based on the subject's response data and stimulus data under the current color contrast;

[0047] Step S304, based on the reaction data, the stimulus data and the action reaction delay under the current color contrast, 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.

[0048] Specifically, the root mean square error (RMSE) between the stimulus data and the response data is calculated according to the following first specified formula:

[0049]

[0050] Among them, I t represents the subject's response position at the test time t, s t-Δt represents the stimulus position at time t-Δt, Δt represents the action response delay, and N represents the total number of frames corresponding to the time window under the current color contrast.

[0051] The above shows the RMSE value calculation process under the measurement trial. In this embodiment, the time window used for the measurement trial is 600ms, and N is 51 frames, that is, the total number of frames in the set time window. 600ms is the time for evaluating that the subject's performance is indeed lower than the judgment standard d. This setting ensures that the stimulus contrast drops below the threshold.

[0052] See also Figure 4 As shown, the step of adjusting the color contrast of the stimulus color block in the next frame image according to the size relationship between the current RMSE value and the predetermined judgment standard value specifically includes:

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

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

[0055] Furthermore, the above-mentioned preset step length is determined as follows: the preset step length step is determined according to the following second specified formula:

[0056]

[0057] Among them, C s It represents the current color contrast of the stimulus color block in the current frame image. b2 and b3 are the parameters for adjusting the slope of the step length and the overall size of the step length, respectively.

[0058] The step size increases exponentially with the stimulus contrast. It changes slowly when the stimulus contrast is close to the threshold range to increase the accuracy of threshold estimation, and changes rapidly when the stimulus contrast is far above the threshold range 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] See also Figure 5 As shown, the determination process of the above judgment standard value is as follows:

[0063] Step S502, for the color dimension, corresponding calibration trials are set; calibration trials are trials in which the contrast does not change with performance, and measurement trials are trials in which the contrast changes with the subject's performance.

[0064] Step S504, obtaining the subject's response data and stimulus data in the calibration trial;

[0065] Step S506, determining the calibration trial RMSE value according to the response 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 response data in the calibration trial;

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

[0067] Step S508: Calculate the standard value of the measurement test in the color dimension according to the RMSE value of the calibration test. Specifically, calculate the standard value d of the measurement test in the color dimension according to the following third specified formula:

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

[0069] Among them, b1 represents the parameter used to characterize the strictness of the judgment standard; b1 is different in different color dimensions; RMSE′ represents the RMSE value of the calibration test.

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

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

[0072] Table 2

[0073]

[0074] Furthermore, the step of fitting using a cumulative normal distribution function based on multiple color contrasts and the RMSE value corresponding to each color contrast, and estimating the contrast threshold parameter of the subject in the color dimension using the secondary mathematical expectation of the distribution includes:

[0075] (1) According to the RMSE value corresponding to each color contrast, the F value corresponding to each of the plurality of color contrasts is determined; the 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) Substituting multiple color contrasts and corresponding F values ​​into the following fourth specified formula to determine the contrast threshold parameter of the subject in the color dimension:

[0077]

[0078] Among them, x represents the color contrast of the stimulus color block in the current color dimension, F N (x|α,β)=0 or 1; 0 means the RMSE under the color contrast of the next frame image increases relative to the color contrast of the current frame; 1 means the RMSE under the color contrast of the next frame image decreases relative to the color contrast of the current frame; α means the contrast threshold of the subject in the color dimension; β is proportional to y=F NThe derivative of the function at (α|α,β); where α and β are contrast threshold parameters.

[0079] Taking the red and green color dimension as an example, a calibration trial is first performed. In the calibration trial, the stimulus contrast does not change with the subject's performance. The RMSE value of the calibration trial calculated by this trial is used to determine the parameters used in the subsequent measurement trial. Each measurement trial is 60s, with a total of 5100 frames. The contrast of each frame will change according to the subject's performance in the previous frame to obtain the maximum amount of information as much as possible. After the test, a 5100×1 logical matrix can be obtained based on whether the RMSE of each frame in the measurement trial increases, as the subject's response input, and the contrast of each frame is used as the stimulus intensity input. The stimulus contrast with a 50% increase and a 50% decrease in the subject's RMSE is extracted as the subject's contrast threshold in this color dimension.

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

[0081] In the color vision assessment method provided in the embodiment of the present application, for different color dimensions, the color contrast of the stimulus color block in the next frame image can be adjusted based on the size relationship between the RMSE value of the subject at 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 collecting the subject's effective response data to the stimulus data, and then obtaining a color contrast sequence and a corresponding RMSE value sequence based on the effective data, and finally fitting the color contrast sequence and the corresponding RMSE value sequence through the cumulative normal distribution function to obtain the contrast threshold parameters (such as the aforementioned α and β) as the accurate color vision assessment value of the subject.

[0082] Based on the above method embodiment, the embodiment of the present application further provides a color vision assessment device, which is applied to a controller connected to 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 trial, so that the subject can track and respond to the random and continuous change of the position of the stimulus color block; the stimulus color block is formed by the color blocks of multiple color dimensions intersecting and spaced, and the multiple color dimensions include red-green color dimension, yellow-blue color dimension or black-white color dimension; see Figure 6 As shown, the device comprises:

[0083] The data acquisition module 62 is used for, for each color dimension, using the color contrast of the stimulus color block in the first frame image as the current color contrast, and executing the following data acquisition steps: obtaining the reaction data and corresponding stimulus data of the subject when the color vision test is performed through the stimulus color block at the current color contrast in the color dimension; determining the current RMSE value at the current color contrast according to the reaction data and stimulus data of the subject at the current color contrast; adjusting the color contrast of the stimulus color block in the next frame image according to the size relationship between the current RMSE value and the predetermined judgment standard value, re-using the adjusted color contrast as the current color contrast, and continuing to execute the data acquisition steps until multiple color contrasts within the specified time window and the RMSE value corresponding to each color contrast are obtained; 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 used for fitting using the cumulative normal distribution function according to the multiple color contrasts and the RMSE value corresponding to each color contrast, and estimating the contrast threshold parameter of the subject in the color dimension with the secondary mathematical expectation of the distribution; the evaluation value determination module 66 is used for determining the contrast threshold parameters of the subject in different color dimensions as the corresponding color vision evaluation value of the subject.

[0084] Furthermore, the data acquisition module 62 is used to determine the action reaction delay using the cross-correlation method according to the reaction data and stimulus data of the subject under the current color contrast; based on the reaction data, stimulus data and action reaction delay under the current color contrast, 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.

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

[0086]

[0087] Among them, I t represents the subject's response position at the test time t, s t-Δt represents the stimulus position at time t-Δt, Δt represents the action response delay, and N represents the total number of frames corresponding to the time window under the current color contrast.

[0088] Furthermore, the data acquisition module 62 is used to reduce the color contrast of the stimulus color block in the next frame image according to a preset step size if the current RMSE value is greater than the judgment standard value; 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 image according to a preset step size.

[0089] Furthermore, the above-mentioned preset step length is determined as follows: the preset step length step is determined according to the following second specified formula:

[0090]

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

[0092] Furthermore, the process of determining the above-mentioned judgment standard value is as follows: for the color dimension, set the corresponding calibration trial; obtain the reaction data and stimulus data of the subject in the calibration trial; determine the RMSE value of the calibration trial based on the reaction data and stimulus data in the calibration trial; the RMSE value of the calibration trial represents the root mean square difference between the test data and the reaction data in the calibration trial; and calculate the judgment standard value of the measurement trial under the color dimension based on the RMSE value of the calibration trial.

[0093] Furthermore, the data acquisition module 62 is used to calculate the judgment standard value d of the measurement test in the color dimension according to the following third specified formula:

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

[0095] Among them, b1 represents the parameter used to characterize the strictness of the judgment standard; b1 is different in different color dimensions; RMSE′ represents the RMSE value of the calibration test.

[0096] Further, the data fitting module 64 is used to: determine the F values ​​corresponding to the multiple color contrasts according to the RMSE value corresponding to each color contrast; the 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; substitute the multiple color contrasts and the corresponding F values ​​into the following fourth specified formula to determine the contrast threshold parameter of the subject in the color dimension:

[0097]

[0098] Among them, x represents the color contrast of the stimulus color block in the current color dimension, F N (x|α,β)=0 or 1; 0 means the RMSE under the color contrast of the next frame image increases relative to the color contrast of the current frame; 1 means the RMSE under the color contrast of the next frame image decreases relative to the color contrast of the current frame; α means the contrast threshold of the subject in the 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.

[0099] The device provided in the embodiment of the present application has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the embodiment of the device, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0100] The present application also provides an electronic device, such as Figure 7 As shown, it is a schematic diagram of the structure of the electronic device, wherein the electronic device 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 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] Among them, the memory 70 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 73 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 72 can 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 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0103] The processor 71 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 71. The above processor 71 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to execute, or the hardware and software modules in the decoding processor can be executed. The software module can be located in a mature storage medium in the field such as 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 is located in the memory, and the processor 71 reads the information in the memory and completes the steps of the method of the above embodiment in combination with its hardware.

[0104] An embodiment of the present application also 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 prompt the processor to implement the above method. The specific implementation can be found in the aforementioned method embodiment, which will not be repeated here.

[0105] The computer program products of the methods, devices, and electronic devices provided in the embodiments of the present application include a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the previous method embodiments. The specific implementation can be found in the method embodiments, which will not be repeated here.

[0106] Unless otherwise specifically stated, the relative steps, numerical expressions and 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 functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0108] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0109] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A color vision assessment method, characterized in that: The method is applied to a controller connected to a test drawing board; the test drawing board 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 tracks and responds to the position of the stimulus color block that changes randomly and continuously; the stimulus color block is formed by color blocks in multiple color dimensions that are interlaced 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 includes: For each color dimension, the color contrast of the stimulus color block in the first frame image is used as the current color contrast, and the following data acquisition steps are performed: the reaction data of the subject when the color vision test is performed through the stimulus color block under the current color contrast under the color dimension, and the corresponding stimulus data are obtained; according to the reaction data and stimulus data of the subject under the current color contrast, the current RMSE value under the current color contrast is determined; according to the size relationship between the current RMSE value and the predetermined judgment standard value, the color contrast of the stimulus color block in the next frame image is adjusted, and the adjusted color contrast is used again as the current color contrast, and the data acquisition steps are continued until multiple color contrasts within the specified time window and the RMSE value corresponding to each color contrast are obtained; the RMSE value represents the root mean square difference between the test data and the reaction data in the measurement trial; According to multiple color contrasts and the RMSE value corresponding to each color contrast, a cumulative normal distribution function is used for fitting, and the secondary 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 subject in different color dimensions are determined as the color vision evaluation values ​​corresponding to the subject.

2. The method according to claim 1, characterized in that The step of determining a current RMSE value at the current color contrast according to the reaction data and stimulus data of the subject at the current color contrast comprises: determining the action response delay using a cross-correlation method based on the subject's response data and stimulus data at the current color contrast; Based on the reaction data and the stimulus data under the current color contrast and the action reaction delay, 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.

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 the stimulus data under the current color contrast and the action response delay comprises: Calculate the root mean square error (RMSE) between the stimulus data and the response data according to the following first specified formula: Among them, I t represents the subject's response position at the test time t, s t-Δt represents the stimulus position at time t-Δt, 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 the stimulus color block in the next frame image according to the size relationship between the current RMSE value and the predetermined judgment standard value includes: If the current RMSE value is greater than the judgment standard value, the color contrast of the stimulus color block in the next frame image is reduced according to a preset step size; If the current RMSE value is less than the judgment standard value, the color contrast of the stimulus color block in the next frame image is increased according to a preset step size.

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

6. The method according to claim 1, characterized in that The determination process of the judgment standard value is as follows: For the color dimension, setting corresponding calibration trials; Acquiring the subject's response data and stimulus data in the calibration trial; Determine a calibration trial RMSE value according to the reaction data and stimulus data under 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; According to the RMSE value of the calibration trial, the judgment standard value of the measurement trial under the color dimension is calculated.

7. The method according to claim 6, characterized in that The step of calculating the judgment standard value of the measurement trial under the color dimension according to the calibration trial RM SE value includes: According to the following third specified formula, the judgment standard value d of the measurement test under the color dimension is calculated: d = (1 + b1) RMSE'; Wherein, b1 represents a parameter used to characterize the strictness of the judgment standard; b1 is different in 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 using a cumulative normal distribution function according to multiple color contrasts and the RMSE value corresponding to each color contrast, and estimating the contrast threshold parameter of the subject in the color dimension using the secondary mathematical expectation of the distribution include: Determine the F values ​​corresponding to the plurality of color contrasts respectively according to the RMSE value corresponding to each color contrast; the 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; Substitute multiple color contrasts and corresponding F values ​​into the following fourth specified formula to determine the contrast threshold parameter of the subject in the color dimension: Among them, x represents the color contrast of the stimulus color block in the current color dimension, F N (x|α,β)=0 or 1; 0 means the RMSE under the color contrast of the next frame image increases relative to the color contrast of the current frame; 1 means the RMSE under the color contrast of the next frame image decreases relative to the color contrast of the current frame; α means the contrast threshold of the subject under the 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 applied to a controller connected to a test drawing board; the test drawing board 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 tracks and responds to the position of the stimulus color block that changes randomly and continuously; the stimulus color block is formed by color blocks in multiple color dimensions that are interlaced 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 device includes: A data acquisition module is used for, for each color dimension, using the color contrast of the stimulus color block in the first frame image as the current color contrast, and executing the following data acquisition steps: acquiring the reaction data of the subject when the color vision test is performed through the stimulus color block at the current color contrast under the color dimension, and the corresponding stimulus data; determining the current RMSE value at the current color contrast according to the reaction data and stimulus data of the subject at the current color contrast; adjusting the color contrast of the stimulus color block in the next frame image according to the size relationship between the current RMSE value and a predetermined judgment standard value, re-using the adjusted color contrast as the current color contrast, and continuing to execute 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 reaction data in the measurement trial; A data fitting module, for fitting using a cumulative normal distribution function according to 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 using a secondary mathematical expectation of the distribution; The evaluation value determination module is used to determine the contrast threshold parameters of the subject in different color dimensions as the color vision evaluation values ​​corresponding to the subject.

10. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 8.

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