CN-122025076-A - Color blindness personalized interactive assessment method and system based on augmented reality

CN122025076ACN 122025076 ACN122025076 ACN 122025076ACN-122025076-A

Abstract

The invention relates to the technical field of color blindness diagnosis, in particular to an enhanced reality-based color blindness personalized interactive assessment method and system, wherein the method comprises the steps of establishing a color mapping relation between a physical color card and an enhanced reality environment based on standard illumination conditions; the color vision testing method comprises the steps of generating a hue testing task formed by a plurality of virtual color blocks corresponding to a color mapping relation through an augmented reality environment, assisting a user to sort the virtual color blocks based on a natural interaction mode, recording sorting results to obtain color vision defect characteristics, carrying out local or cloud quantitative analysis on the color vision defect characteristics, calculating color vision quantization error parameters, constructing a user color vision sensing model, outputting the color vision defect type and severity level of the user based on the user color vision sensing model, outputting a color vision evaluation report according to the user color vision sensing model, the color vision defect type and severity level, and generating a targeted color optimization scheme. The invention provides a full-flow solution from accurate assessment to personalized color adaptation for color blind users.

Inventors

Shen Wuyao
XIAO ZHENYU
WANG TAIZHI

Assignees

图灵极视(深圳)科技有限公司

Dates

Publication Date: 20260512
Application Date: 20251224

Claims (10)

1. The color blindness personalized interactive assessment method based on augmented reality is characterized by comprising the following steps of: Based on standard illumination conditions, establishing a color mapping relation between a physical color card and an augmented reality environment; Generating a hue test task through an augmented reality environment, wherein the hue test task consists of a plurality of virtual color blocks corresponding to a color mapping relation; Based on a preset natural interaction mode, assisting a user to sort the virtual color blocks and recording the sorting result to obtain color vision defect characteristics; Carrying out local or cloud quantitative analysis on the color vision defect characteristics, calculating color vision quantization error parameters, constructing a user color vision perception model, and outputting the color vision defect type and the severity level of the user based on the user color vision perception model; and outputting a color vision evaluation report according to the user color vision perception model and the color vision defect type and severity level, and generating a targeted color optimization scheme.
2. The method for personalized interactive assessment of color blindness based on augmented reality according to claim 1, wherein the step of establishing the color mapping relationship between the physical color chart and the augmented reality environment based on the standard illumination condition comprises the following steps: Placing a physical color card under standard illumination conditions, and collecting standard color data of each standard color block in the physical color card; generating a virtual color block group matched with the physical color card in an augmented reality environment, and collecting initial color data of each virtual color block in the virtual color block group; constructing a color mapping model by a color mapping algorithm based on the standard color data and the initial color data of the virtual color block group, wherein the color mapping algorithm comprises at least one of a linear mapping algorithm or a nonlinear fitting algorithm; And calibrating the initial color data of the virtual color block group by using the color mapping model, performing deviation verification on the calibrated virtual color block color data and corresponding standard color data, determining the color mapping model as a target color mapping relation if the deviation value obtained by verification is smaller than a preset threshold value, and backtracking and adjusting color mapping algorithm parameters if the deviation value is larger than or equal to the preset threshold value until the deviation value meets the preset threshold value requirement.
3. The method for personalized interactive assessment of color blindness based on augmented reality according to claim 1, wherein the step of generating the color test task through the augmented reality environment comprises the following steps: Determining a target hue interval to be covered by a hue test task based on the color mapping relation, wherein the target hue interval at least comprises two or more of red, green, blue and yellow; Generating a corresponding hue gradient virtual color block subset aiming at each target hue interval, wherein each group of hue gradient virtual color block subset comprises a preset number of virtual color blocks; And defining the color attribute of each group of virtual color block subset, wherein the hue of each virtual color block in the same subset is continuously graded, the brightness and the saturation are kept consistent, and all the virtual color block subsets are integrated into a hue test task.
4. The method for personalized interactive assessment of color blindness based on augmented reality according to claim 3, wherein the step of assisting the user to order the virtual color blocks and record the ordering result based on the preset natural interaction mode to obtain the color vision defect feature comprises the following steps: Activating a preset natural interaction mode, wherein the natural interaction mode comprises at least one of gesture interaction, head gaze control or voice control; Providing interactive auxiliary feedback for a user in an augmented reality environment, wherein the interactive auxiliary feedback comprises highlighting selected virtual color blocks, ordering position prompts or operation success vibration prompts; Recording the sorting operation of the user on each virtual color block subset in real time in the natural interaction mode, and generating an original sorting result comprising the sorting sequence and the operation duration of the virtual color blocks; And comparing the original sorting result with a standard sorting sequence of the corresponding virtual color block subset, extracting sorting deviation parameters, wherein the sorting deviation parameters comprise the number of misplaced color blocks, the inversion times of adjacent color blocks and hue intervals of the misplaced color blocks, and integrating the sorting deviation parameters to obtain color vision defect characteristics.
5. The augmented reality-based color blindness personalized interactive assessment method according to claim 4, wherein the step of performing local or cloud quantization analysis on color vision defect characteristics, calculating color vision quantization error parameters, constructing a user color vision perception model, and outputting the color vision defect type and severity level of the user based on the user color vision perception model performs local quantization analysis on the color vision defect characteristics, and calculating color vision quantization error parameters comprises the following steps: Reading the color vision defect characteristics in user terminal equipment, and carrying out data preprocessing on the color vision defect characteristics, wherein the preprocessing comprises outlier rejection, data standardization and missing value complementation; Performing local quantization analysis on the preprocessed color vision defect characteristics based on a preset quantization rule, wherein the preset quantization rule comprises the steps of assigning a preset weight coefficient to the sorting deviation parameters and calculating a deviation score according to hue interval classification; And calculating color vision quantization error parameters according to the quantization analysis result, wherein the color vision quantization error parameters comprise total error scores, deviation coefficients of all color phase intervals and maximum deviation values.
6. The augmented reality-based color blindness personalized interactive assessment method according to claim 4, wherein the step of performing local or cloud quantization analysis on color vision defect characteristics, calculating color vision quantization error parameters, constructing a user color vision perception model, and outputting the color vision defect type and severity level of the user based on the user color vision perception model, performing cloud quantization analysis on the color vision defect characteristics, and calculating color vision quantization error parameters comprises the following steps: reading the color vision defect characteristics in user terminal equipment, encrypting the color vision defect characteristics by adopting a symmetric encryption algorithm, and uploading the color vision defect characteristics to a cloud server through a secure communication link; The cloud server receives the encrypted color vision defect characteristics, and performs enhancement pretreatment after decryption, wherein the enhancement pretreatment comprises outlier rejection, data standardization, missing value complementation and color vision defect abnormal pattern recognition; If the abnormal mode is not identified, a preset complex quantization algorithm is adopted to execute cloud quantization analysis on the color vision defect characteristics after the enhancement pretreatment, wherein the preset complex quantization algorithm comprises a deviation fitting algorithm or a multidimensional weight dynamic allocation algorithm based on machine learning; And calculating to obtain color vision quantization error parameters through the anomaly processing model or a preset complex quantization algorithm, wherein the color vision quantization error parameters comprise total error scores, deviation coefficients of all color phase intervals, maximum deviation values and defect mixing coefficients, and storing the color vision quantization error parameters in a cloud server or returning the color vision quantization error parameters to user terminal equipment.
7. The augmented reality-based color blindness personalized interactive assessment method according to any one of claims 5 or 6, wherein the step of performing local or cloud quantization analysis on color vision defect characteristics, calculating color vision quantization error parameters, and constructing a user color vision perception model, and outputting the color vision defect type and severity level of the user based on the user color vision perception model comprises the following steps: obtaining color vision quantization error parameters obtained through quantization analysis as model input data; Based on model input data, constructing a user color sense perception model through a parameter fitting algorithm, wherein the user color sense perception model is used for representing a color sense deviation rule of a user in each color phase interval and outputting a color sense deviation quantization result of the user in each color phase interval; And matching the color vision deviation quantification result output by the user color vision perception model with a preset color vision defect type library and a severity level judgment standard, and outputting a color vision defect type and a severity level corresponding to the user, wherein the color vision defect type comprises at least one of red-green color blindness, red-green color weakness, blue-yellow color blindness and blue-yellow color weakness, and the severity level comprises light, moderate and severe.
8. The augmented reality-based color blindness personalized interactive assessment method according to claim 1, wherein the step of outputting a color vision assessment report and generating a targeted color optimization scheme according to a user color vision perception model and a color vision defect type and severity level comprises the following steps: Retrieving user basic information, color vision defect characteristics, color vision quantization error parameters and user color vision defect types and severity levels output by a user color vision perception model from user terminal equipment or a cloud server; Generating a color vision evaluation report based on the retrieved data, wherein the color vision evaluation report comprises user basic information, color vision defect types and severity levels, color vision deviation quantitative analysis and basic improvement suggestions; Calculating color optimization parameters based on a user color sense perception model, a color sense defect type and a severity level, and generating a targeted color optimization scheme adapting to an augmented reality interaction scene and a conventional display scene, wherein the targeted color optimization scheme comprises a hue shift coefficient, a saturation adjustment proportion, a brightness compensation value and a contrast enhancement coefficient; And integrating and outputting the color vision evaluation report and the targeted color optimization scheme, wherein the output mode comprises augmented reality interface presentation, user terminal equipment display, cloud file export or equipment adaptation instruction issuing.
9. The method for personalized color blindness interactive assessment based on augmented reality according to claim 8, wherein after the step of calculating color optimization parameters and generating a targeted color optimization scheme adapted to an augmented reality interactive scene and a regular display scene based on the user color perception model, the color perception defect type and the severity level, the method further comprises the steps of: After the targeted color optimization scheme takes effect, collecting user feedback data in real time, wherein the user feedback data comprise visual comfort degree scores, color identification degree feedback, target hue distinguishing accuracy and scene adaptation satisfaction; Carrying out validity check on the using feedback data, and extracting feedback core indexes after eliminating abnormal feedback values, wherein the feedback core indexes comprise negative feedback duty ratio, key hue adaptation deviation degree and user preference adjustment suggestions; Based on the feedback core index, combining a user color sense perception model and a color sense quantization error parameter, iteratively optimizing color optimization parameters through a dynamic weight adjustment algorithm, wherein the optimization adjustment comprises fine calibration of a hue offset coefficient, suitability correction of saturation and brightness and scenerization adjustment of a contrast enhancement coefficient; Updating the iterative optimized color optimization parameters into a targeted color optimization scheme, generating a versioned updating scheme, supporting a user to select and enable the updating scheme or keep the original scheme, and storing an updating record in user terminal equipment or a cloud server.
10. An augmented reality-based color blindness personalized interactive assessment system for implementing the steps of an augmented reality-based color blindness personalized interactive assessment method according to any one of claims 1 to 9, comprising: The color mapping module is used for establishing a color mapping relation between the physical color card and the augmented reality environment based on standard illumination conditions; The task generating module is used for generating a hue test task through an augmented reality environment, wherein the hue test task consists of a plurality of virtual color blocks corresponding to the color mapping relation; the interaction acquisition module is used for assisting a user to sort the virtual color blocks based on a preset natural interaction mode and recording the sorting result to obtain color vision defect characteristics; The computing and analyzing module is used for carrying out local or cloud quantitative analysis on the color vision defect characteristics, computing color vision quantization error parameters, constructing a user color vision perception model and outputting the color vision defect type and the severity level of the user based on the user color vision perception model; and the evaluation generation module is used for outputting a color vision evaluation report and generating a targeted color optimization scheme according to the user color vision perception model, the color vision defect type and the severity level.

Description

Color blindness personalized interactive assessment method and system based on augmented reality Technical Field The invention relates to the technical field of achromatopsia diagnosis, in particular to an achromatopsia personalized interactive assessment method and system based on augmented reality. Background Color vision deficiency (Color Vision Deficiency, CVD for short, also known as achromatopsia or color weakness) is a common visual disorder, and is statistically affected by about 5% of the population worldwide. CVD can be classified into red-green vision defects, blue-yellow vision defects, and total color blindness by the damaged band. Such defects cause confusion for users when identifying a particular color, affecting their visual experience in the fields of traffic, education, engineering, and information visualization, etc. Currently, there is no fully effective treatment for CVD, but reprocessing of images by computer vision has been demonstrated to improve the visual experience of the population of color vision defects. However, the existing image enhancement processing often needs personalized color vision defect characteristics, and the visual defect detection research aiming at the CVD user is mainly focused on two schemes: One is in clinical testing. Clinical FM100-Hue et al tests are widely used to obtain personalized color vision deficiency characteristics to provide corrective parameters for vision correction systems. However, the application of these methods is limited by factors such as equipment (e.g., optical limitations, field of view, etc.), personnel (e.g., human supervision, professional assessment, etc.), and environment (e.g., lighting environment, etc.), which limit the convenience and repeatability in practical applications. And secondly, a digital color sense test is performed. With the development of existing computing vision, limited FM100-Hue is converted into digital portability. However, the existing digital color blindness detection technology also faces limitations, and lacks customization of individual differences of users and real-time adaptive capacity to environment. With the rise of Augmented Reality (AR) devices, color blind image enhancement systems combined with AR technology have higher portability, however, image enhancement is often limited by CVD level of users, and personalized enhancement cannot be performed. Therefore, developing a personalized, real-time and convenient achromatopsia diagnosis system can effectively improve the visual experience of achromatopsia individuals, and the method has become a problem to be solved urgently. Disclosure of Invention In order to overcome the defects of the prior art, the invention provides an enhanced reality-based color blindness personalized interactive assessment method and system, which are used for solving the problems in the prior art. One embodiment of the invention provides an enhanced reality-based color blindness personalized interactive assessment method, which comprises the following steps: The application also relates to an enhanced reality-based color blindness personalized interactive assessment system, which comprises: The color mapping module is used for establishing a color mapping relation between the physical color card and the augmented reality environment based on standard illumination conditions; The task generating module is used for generating a hue test task through an augmented reality environment, wherein the hue test task consists of a plurality of virtual color blocks corresponding to the color mapping relation; the interaction acquisition module is used for assisting a user to sort the virtual color blocks based on a preset natural interaction mode and recording the sorting result to obtain color vision defect characteristics; The computing and analyzing module is used for carrying out local or cloud quantitative analysis on the color vision defect characteristics, computing color vision quantization error parameters, constructing a user color vision perception model and outputting the color vision defect type and the severity level of the user based on the user color vision perception model; and the evaluation generation module is used for outputting a color vision evaluation report and generating a targeted color optimization scheme according to the user color vision perception model, the color vision defect type and the severity level. The color blindness personalized interactive assessment method and system based on the augmented reality provided by the embodiment have the following beneficial effects: The color vision evaluation method based on the cloud computing system comprises the steps of establishing a color mapping relation between a physical color card and an augmented reality environment based on standard illumination conditions, guaranteeing reference accuracy of color vision test, solving the problem of test deviation caused by environment illumination interference