CN111429547B - Abnormal color vision test chart synthesis method based on pseudo-homochromatic search - Google Patents
Abnormal color vision test chart synthesis method based on pseudo-homochromatic search Download PDFInfo
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Abstract
The invention relates to an abnormal color vision test chart synthesis method based on pseudo-homocolor search, which mainly comprises the following steps: searching false homography pairs; selecting a pseudo-same color pair; generating a test image; aiming at the test pattern used for testing the color vision condition of the subject in the abnormal color vision test, the invention selects the pseudo-same color pair in the color space by means of an abnormal visual simulation algorithm, and performs binarization color filling on the abnormal visual test pattern, thereby generating an abnormal color vision test pattern which has various contents, can be randomly repeated and has the abnormal color vision type specificity, and compared with the existing manual drawing or computer-aided semi-manual drawing method, the abnormal color vision test pattern is flexible, random, simple and controllable and has the specificity for different abnormal color vision.
Description
Technical Field
The invention belongs to the technical field of digital image generation, and particularly relates to a method for synthesizing an abnormal color vision test chart.
Background
With the development of social economy and the continuous progress of scientific technology, the specialized technology is increasingly finer, people are more concerned about the health conditions of individual eyesight, vision and the like, the requirements of a plurality of professions on color discrimination capability are also improved, more industries and departments have more specific requirements on the eyesight and vision of the practitioners of the professions, for example, the vision and color vision are definitely regulated in the fields of air force pilot physical examination, the physical examination of the workable signs and the like, and the specialized professions of a plurality of universities also have a certain limit on the examination of color blind students in the life. There are strict requirements for visual color vision of some special service weapons abroad. Vision vision test is a widely accepted scientific quantitative inspection method, and is particularly important for talent development, health field and even social and economic development. Among them, the color blindness color vision inspection chart based on the pseudo-homocolor principle is the most commonly used color vision inspection tool worldwide.
The color blindness checking chart is a key tool for detecting color blindness. An inspection method designed according to the principle of pseudo-homochromatism is used for screening color vision abnormality for centuries. Through various types of inspection patterns, geometric patterns, digital patterns, line patterns, object patterns, and the like, the red-green and blue Huang Dengse visual abnormalities are detected. The main defects of the color blindness detection method adopting the pseudo-homochromatic principle map are single pattern, cured color scheme, no specificity and the like, and the factors seriously influence the objectivity and the authenticity of the detection result.
Most of the existing abnormal color vision test patterns are test scripts with fixed patterns drawn by using a computer drawing tool such as a manual or Photoshop machine, the patterns are single, the normal patterns are fixed, and the drawing is complicated. For example, the fifth edition of color blindness test chart widely used in physical examination, the first group of charts can be used for large-scale rapid examination; the second group of pictures is characterized by simple geometric figures, and is suitable for adult and illiterate physical examination with low cultural level; the third group of pictures is suitable for checking children, and the fourth group of pictures is a multi-digit group for professional physical examination with higher requirements on color vision; the fifth group of images are acquired color vision inspection images, and are suitable for auxiliary diagnosis of fundus diseases and central diseases by clinicians, intraneurals and surgeons.
The color vision principle of the abnormal color vision test chart is that light red and light green are crossed to interfere with the tested person, if the tested person is achromatopsia, the tested person can see only one color, so that the numbers formed by the chromatic aberration cannot be distinguished. The graphic of the correct answer in the regular picture of the reading is generally different in hue from the background color. In the inspection process, medical staff often adopts the traditional manual achromatopsia inspection drawing books to detect patients one by one, the detection patterns in the drawing books are single and limited in quantity, the scientificity of inspection is easily caused, and the conditions of missed inspection and coarser inspection occur. Especially, the pattern is single, and a tester can often memorize the answer by adopting an association or identification memorization method without carefully identifying, so that the accuracy and scientificity of the inspection result are affected to a certain extent. The original manual design and computer-aided drawing method has influence on the accuracy and practicality of the abnormal color vision test chart due to the reasons of complex process, time and labor consumption, single style fixation, low randomness and the like, so that a new method is required to be researched to manufacture the abnormal color vision test chart.
In addition, the existing achromatopsia instrument related to the computer stores the fixed pattern drawn by the existing achromatopsia inspection chart, and can not flexibly and randomly generate new patterns according to actual conditions. For example, patent "an achromatopsia instrument and achromatopsia detection method" filed by Shenzhen Rojie technologies Inc. (patent application number 20110224333, publication number 102283632A) provides an achromatopsia instrument for achromatopsia detection. The detection method comprises two stages, wherein the first stage mainly comprises the step of randomly displaying twenty-one fixed achromatopsia detection pictures to test a tested person, and the defects of the detection method are that the detection method still depends on fixed detection patterns, is randomly selected, cannot be randomly generated, cannot fundamentally solve the problem of single image and cannot guarantee the objectivity of a detection result.
Disclosure of Invention
Aiming at the technical problems, the invention provides an abnormal color vision test chart synthesis method based on pseudo-same-color search, which comprises the following steps:
step 1: searching pseudo-same color pairs, namely traversing and simulating candidate colors on an RGB grid space, and calculating perceived color difference before and after the candidate color simulation;
step 2: selecting a false same-color pair, namely judging a threshold condition, selecting the false same-color pair, and storing the false same-color pair;
step 3: generating a test image, namely selecting a color blindness test pattern, filling foreground and background with pseudo-same color pairs to form a unit test pattern, and grouping the unit test pattern.
Further, step 1 includes:
step 1.1: selecting candidate colors, namely performing grid division on an RGB space, and randomly performing tiny offset on nodes of grids or taking each grid node as a center to select the candidate colors;
step 1.2: calculating the artificial colour, i.e. candidate colour vector for selected triples
The corresponding color vector +.A corresponding color vector is obtained through a color blind simulation algorithm>
Wherein τ ε [ d, p, t ]]List items [ d, p, t ]]Respectively representing green color blindness, red color blindness and blue color blindness;
step 1.3: calculating perceived color difference, i.e. converting RGB color to XYZ color space, then to LAB color space, and then calculating { Q, Q }, using CIE Lab1976 color difference formula τ Color difference value Δe between } Lab (Q,Q τ )；
The step 2 comprises the following steps:
step 2.1: judging the threshold condition, namely setting the threshold condition to be alpha more than or equal to 0, when delta E is Lab (Q,Q τ ) When not less than alpha, the pseudo-homochromatic pair { Q, Q is reserved τ -as an element in the set of fill colors; when delta E Lab (Q,Q τ ) Discarding the pseudo-homochromatic pair { Q, Q when alpha is less than or equal to τ -wherein α is a settable parameter, the physical meaning is a color difference threshold;
step 2.2: selecting false same-color pairs, namely calculating all candidate colors, judging the threshold condition, and respectively selecting elements in a false same-color pair set according to a set color difference threshold alpha;
step 2.3: storing the pseudo-same-color pair, namely storing the selected pseudo-same-color set;
the step 3 comprises the following steps:
step 3.1: selecting a test pattern, namely selecting geometric shapes which are convenient to identify and common patterns in life as the test pattern, combining any false same-color pair generated in the process as a foreground color and a background color respectively, and filling the foreground and the background of the test pattern;
step 3.2: filling the test pattern, namely filling the test pattern by adopting the selected pseudo-same color pair;
step 3.3: generating a test unit, namely filling the test pattern to obtain a three-channel color image serving as the test unit;
step 3.4: the test images are grouped, i.e. a plurality of test units are selected randomly and combined into a group of test images.
Further, in step 1.1, the RGB color space is divided into an X Y Z grid, the size is 32 multiplied by 32, and the triplet candidate color vector is selected on the nodes of the grid;
corresponding color vector Q in step 1.2 τ Is calculated as follows: firstly, converting the triplet candidate color vector Q into an LMS space to obtain a corresponding color vector in the LMS space, wherein the color vector is represented by the following formula:
wherein the method comprises the steps of
A transformation matrix for the RGB color space to the LMS color space;
and then using a color blindness simulation algorithm to obtain tau-type color blindness simulation vectors in the LMS color space:
wherein T is sim τ The transformation matrix is used in the color blindness simulation algorithm;
the tau-color blind simulation vector of the LMS color space is then converted back into an RGB space vector, i.e.,
wherein Q is τ Corresponding colors, i.e., { Q, are simulated for achromatopsia of the triplet candidate color vector Q τ -a pair of pseudo-homochromes;
in step 1.3 { Q, Q is calculated according to the following formula τ Color difference value between }:
wherein (L) Q *,a Q *,b Q * ) Representing the result after conversion of candidate color Q into LAB space,
representing the simulation color Q τ Three components after conversion to LAB space;
step 2.1 employs α=50;
step 2.2, randomly selecting in the selected pseudo-same color pair set, or directly picking up color elements in the set after visualization;
in the step 2.3, the storage mode can adopt data structures such as hash lists, dictionaries and the like, and the file format can use JSON or Pickle objects;
randomly generating numbers 0-9 as foreground contents and the rest blank area as background in the step 3.1 to form a test pattern;
in step 3.4, 5*5 unit test patterns are selected to form one test image.
Further, in step 1.1, the RGB color space is divided into grids of X Y X Z, and the grids are divided into grid nodes (X 0 ,y 0 ,z 0 ) As a center, the points reached by the random small step offsets (Δx, Δy, Δz) in each direction are used as triplet candidate color vectors.
Further, in step 3.2, the test pattern is directly filled with the pseudo-same color pair, the simulated color is used as the background filling color, and the original color is used as the foreground filling color.
Further, in step 3.2, the test pattern is filled with pseudo-same color pairs, and small circle geometric patterns which are not overlapped with each other are drawn by adopting a K-D tree data structure, so that the split test pattern units are formed.
Further, in step 3.2, the test pattern is filled with an approximate color generalization of the pseudo-homocolor pair, and similar colors are randomly picked up according to Gaussian distribution in a sphere space with the pseudo-homocolor as a sphere center and the radius ρ in the LAB color space to fill small geometric patterns generated each time, wherein ρ is more than 0 and less than 32.
Further, step 1.1 takes a small step size of the die
Wherein Δx, Δy, Δz are integers;
the test pattern is filled in a fine density checkered pattern in step 3.2.
The invention also provides an application device of the abnormal color vision test chart, which is characterized in that: the image generated by the method for manufacturing the abnormal color vision test chart can be used for a special color vision detection computer device, embedded software and hardware, a paper printing device or an Internet application software system.
Furthermore, the color vision detection computer device comprises various types of computers, mobile terminals, virtual reality equipment, google glasses, iPad tablet computers, special displays, medical eye vision testers and other equipment development corresponding offline or online application in a software system to realize the color vision test pattern synthesis method, and the color vision test pattern synthesis method is presented on a display screen by taking unit test patterns and grouping test patterns as use cases; the embedded software and hardware and paper printing device realizes a color vision test chart synthesis method by corresponding programming languages through various embedded systems such as a singlechip, an FPGA and the like and a development board, or synthesizes color vision test charts on other hardware platforms in advance, and then stores the color vision test charts in embedded equipment for display or printing; the Internet application software system develops and realizes the color vision test synthesis method in various programming languages such as Javascript, hypertext markup language and the like, or presents a color vision test chart at a browser or APP end in a micro-service and off-line application mode and combines with an interactive design to implement color vision test.
Aiming at the test pattern used for testing the color vision condition of the subject in the abnormal color vision test, the invention selects the pseudo-same color pair in the color space by means of an abnormal vision simulation algorithm, and binarizes and color fills the abnormal vision test pattern, thereby generating an abnormal color vision test pattern which has various contents, can be randomly repeated and has the abnormal vision type specificity. Compared with the existing manual drawing or computer-aided semi-manual drawing method, the method has the characteristics of flexibility, randomness, simplicity, controllability, specificity for different abnormal color vision and the like.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a graph showing the distribution of pseudo-same color pairs corresponding to three typical achromatopsia types in RGB color space at different color thresholds α;
FIG. 3 is a diagram of a unit test made using the method of the present invention;
FIG. 4 is a schematic diagram of a group test chart made using the method of the present invention.
Detailed Description
The invention is further described below with reference to the drawings and examples.
Aiming at the defects of the existing color vision inspection technology, the problems of single pattern, no specificity of a color collocation scheme and the like of the existing abnormal color vision test chart, the invention provides a false same-color search-based abnormal color vision test chart manufacturing method. The technical idea is that by means of the existing abnormal color vision simulation algorithm, parameters are set in a perceived color space to search pseudo-same color pair combinations aiming at specific abnormal color vision types; then selecting a pattern, and filling the foreground and background colors of the pattern with pseudo-same color pairs to generate a binarization unit test chart; and finally, grouping a plurality of binarization unit test patterns to form a test pattern.
The specific steps of the invention are shown in figure 1, comprising:
step 1: the false homography pairs are searched. Traversing and simulating the candidate colors on the RGB grid space, and calculating the perceived color difference before and after the candidate color simulation.
Step 1.1: candidate colors are selected. Dividing the RGB space into grids, and randomly performing tiny offset on nodes of the grids or taking each grid node as a center to select candidate colors;
dividing the RGB color space into grids of X Y X Z, for example, the size can be 32X 32, and selecting the triplet candidate color vector on the nodes of the grids; or in mesh nodes (x 0 ,y 0 ,z 0 ) As a center, points reached by small step offsets (deltax, deltay, deltaz) are randomly shifted in each direction as a triplet candidate color vector, modulo a small step
Wherein Δx, Δy, and Δz are integers.
Step 1.2: the simulated colors are calculated. For the selected triplet candidate color(Vector)
The corresponding color vector +.A corresponding color vector is obtained through a color blind simulation algorithm>
Wherein τ ε [ d, p, t ]]List items [ d, p, t ]]Respectively represent green blindness, red blindness and blue blindness, and correspond to the color vector Q τ Is calculated as follows:
firstly, converting the triplet candidate color vector Q into an LMS space to obtain a corresponding color vector in the LMS space, wherein the color vector is represented by the following formula:
wherein the method comprises the steps of
A transformation matrix for the RGB color space to the LMS color space;
secondly, using a color blindness simulation algorithm proposed by Brettel et al to obtain a tau-color blindness simulation vector in an LMS color space:
wherein T is sim τ The transformation matrix is used in the color blindness simulation algorithm;
the tau-color blind simulation vector of the LMS color space is then converted back into an RGB space vector, i.e.,
the series of calculations can be summarized as a single functional relationship, namely:
Q τ ＝f sim (Q；τ),τ∈[d,p,t]
wherein Q is τ Is three in threeCorresponding colors, i.e., { Q, are simulated by achromatopsia of tuple candidate color vector Q τ -a pair of pseudo-homochromes;
step 1.3: and calculating the perceived color difference. Using the CIE L a b 1976 color difference formula, RGB colors are first converted into XYZ color space, then into LAB color space, and { Q, Q is calculated according to the following equation τ Color difference value between }:
wherein (L) Q *,a Q *,b Q * ) Representing the result after conversion of candidate color Q into LAB space,
representing the simulation color Q τ Three components after conversion to LAB space;
step 2: false homochromatic pairs are selected. And judging a threshold condition, selecting a false same color pair, and finally storing the false same color pair.
Step 2.1: and judging a threshold condition. Setting the threshold value condition to alpha not less than 0, when delta E is Lab (Q,Q τ ) When not less than alpha, the pseudo-homochromatic pair { Q, Q is reserved τ -as an element in the set of fill colors; when delta E Lab (Q,Q τ ) Discarding the pseudo-homochromatic pair { Q, Q when alpha is less than or equal to τ -a }; wherein alpha is a settable parameter, the physical meaning is a color difference threshold, according to the pseudo-same-color ratio versus color difference threshold distribution curve shown in fig. 2, alpha=50 is adopted, at this time, the pseudo-same-color ratio of the red and green color blindness type is about 20%, the pseudo-same-color ratio of the blue color blindness type is about 70%, and it can be ensured that the selected pseudo-same-color has larger color difference, and meanwhile, a sufficient number of pseudo-same-colors can be selected for each color blindness type;
step 2.2: a false homography pair is selected. And calculating all candidate colors, judging the threshold conditions, and respectively selecting elements in the pseudo-same color pair set according to the set color difference threshold alpha. In the actual filling process, the color elements in the selected pseudo-same color pair set can be randomly selected or directly picked up after visualization is carried out on the color elements in the set, so that the pseudo-same color pair to be used is conveniently selected;
step 2.3: the pseudo-homography pairs are stored. And storing the selected pseudo-same-color set, avoiding repeated calculation each time, and facilitating subsequent use. The storage mode can adopt a data structure such as a hash list, a dictionary and the like, and the file format can use JSON or Pickle objects.
Step 3: a test image is generated. Selecting a color blindness test pattern, and filling a foreground and a background with a pseudo-same color pair to form a unit test pattern; the cell test patterns may also be grouped to form a grouped test pattern.
Step 3.1: and selecting a test pattern. The selection of the test patterns can be adjusted according to actual conditions, and geometric shapes and common patterns in life which are convenient to identify can be adopted so as to reduce the interference of the patterns on test results. Taking Arabic numerals 0-9 as an example, the numerals 0-9 are randomly generated as foreground contents and the residual blank area as background to form a test pattern. Any pseudo-same color pair generated in the process is combined and used as a foreground color and a background color respectively, and the foreground and the background of the test pattern are filled with the pseudo-same color pair to generate a test image unit, and the generated test image unit is a binary image, namely only two colors are contained in eyes of corresponding color blindness type personnel, so that the two colors only contain one color, and the numbers in the eyes cannot be identified;
step 3.2: filling the test pattern. The test pattern is filled with the selected pseudo-same color pair.
Mode 1: the test pattern is directly filled with pseudo-homochromatic pairs to form binarized test pattern units, as shown in fig. 3 (a). And filling the foreground and the background of the test pattern respectively by using the false same color pair selected in the false same color searching process, wherein the sequence can be arbitrary, and in general, the simulated color is used as the background filling color and the original color is used as the foreground filling color. The finally generated image is a pattern with the same color in view of the abnormal color vision personnel of the corresponding type, so that the foreground content cannot be identified;
mode 2: the test pattern is filled with pseudo-same color pairs to form segmented test pattern cells, as shown in fig. 3 (b). The false same color pairs selected in the false same color searching process are respectively a foreground and a background, the sequence can be arbitrary, the test pattern is used as a base plate to draw geometric patterns such as small circles which are not mutually overlapped, and the size of an overlapping area of the geometric pattern area and the base plate is used for judging whether the pattern belongs to the foreground or the background, so that corresponding colors are filled. In the drawing process of geometric patterns such as small circles which are not overlapped with each other, the attribute and coordinate storage can be carried out on the drawn small geometric patterns by adopting the existing various K-D tree data structures so as to accelerate the drawing process. The finally generated color vision test chart is similar to the color vision test chart commonly used in clinic in texture, and the foreground is confused in the background in view of abnormal color vision personnel of the corresponding type, so that the foreground content cannot be identified;
mode 3: the approximate color generalization of the pseudo-homochromatic pairs fills the test pattern, resulting in a test cell with some robustness, as shown in fig. 3 (c). In the split filling method described in the mode 2, when geometric patterns such as small circles are specifically filled with colors, false same-color pairs are not directly used, but similar colors are randomly picked up according to gaussian distribution in a sphere space with the false same colors as sphere centers and the radius ρ in an LAB color space to fill the small geometric patterns generated each time, and generally 0 < ρ < 32 can be taken. The resulting image has some tamper resistance to poorly calibrated display devices, printers, and non-ideal brightness environments. The foreground and background patterns are consistent in texture in view of abnormal color vision personnel of the corresponding type, so that the foreground content cannot be identified;
other modes: other derivative variants similar to the three forms described above may also be included, such as a fine density checkered pattern, or multiple juxtaposed foreground patterns may be included in each test cell. The finally generated color vision testing chart unit can confuse the foreground with the background in view of abnormal color vision personnel, and the foreground content is difficult to identify;
step 3.3: a test unit is generated. And filling the test pattern to obtain a three-channel color image serving as a test unit. In addition, the candidate test units can be simulated, the effect of the image test unit can be visually evaluated, and the abnormal color vision can be mixed up according to the fact that whether the image test unit can theoretically make a mistake, so that the image test unit can be further selected and removed.
Step 3.4: the test images are grouped. A plurality of test units are randomly selected and combined into a group of test images, as shown in FIG. 4, wherein FIGS. 4 (a), (b) and (c) respectively correspond to the grouping test patterns formed by combining the test units filled in the three ways in step 3.2.
Taking possible errors of the achromatopsia simulation model and slight differences of individual color vision objectively into consideration, a plurality of images are combined into a group to form one test image, so that the color vision condition of the tested person is comprehensively evaluated according to the ratio of the number of the test units read by the tested person to the total number of the test units. Generally, 5*5 unit test patterns can be selected to form a test image, and the unit test patterns in the whole pattern are randomly generated again during each test, so that the randomness of the test patterns can be ensured.
The invention also comprises the following software and hardware devices and systems:
1. color vision detecting computer device. Aiming at various types of computers, mobile terminals, virtual Reality (VR) equipment such as apparatuses such as an eye, google glasses, an iPad tablet computer, a special display, a medical eye vision tester and the like, corresponding offline or online application is developed, the color vision test chart synthesis method is realized in a software system, and unit test charts and grouping test charts are taken as use cases and are presented on a display screen; the test chart sample can be generated in advance and stored in a hard disk or a memory, and is randomly extracted and displayed during testing; the color vision test is performed in conjunction with a specially formulated series of evaluation protocols, including but not limited to scoring the color vision test results with the correct reading rate of the grouped test charts. Control instruction input for image generation and presentation can be in various forms such as touch control, voice, mouse and the like.
2. Embedded software and hardware and paper printing device. The color vision test chart synthesizing method is realized by corresponding programming languages through various embedded systems such as a singlechip, an FPGA and the like and development boards, or the color vision test chart is synthesized in advance on other hardware platforms and then stored in embedded equipment for display or printing. The color vision test chart is printed into a paper board in a color mode, and is distributed to a tested person in a test paper mode in combination with the descriptive text of the test procedure to carry out the test. The printing equipment can be various color printing devices produced by various manufacturers at home and abroad, and also can be equipment such as a rapid imaging camera technology, a clap device and the like. Specific implementations include, but are not limited to, the following methods: for example, the color vision test chart is made by embedded hardware and computer software, and is transmitted to a color printer for printing and distributed to the tested personnel for color vision test.
3. An internet application software system. The color vision test synthesis method is developed and realized by various programming languages such as Javascript, hypertext markup language and the like, or the color vision test chart is presented at a browser or APP end in the form of micro-service and off-line application, and the color vision test can be implemented by combining a certain interactive design. Specific implementation architectures include, but are not limited to, the following two approaches: 1. directly executing in a client browser by adopting a Javascript language, generating a color vision test chart and testing; 2. a background system is adopted to generate a color vision test chart, and then the color vision test chart is visually displayed in a client browser through a hypertext markup language or a single page application component.
The invention can randomly generate pattern content according to the requirement, and overcomes the defects of fixed patterns; the invention can adjust parameters in the production process and has the advantages of controllable color matching, science and easy use; the invention can qualitatively judge the color vision condition of the subject through a single test chart, and can linearly evaluate the severity of the color blindness according to the identification proportion of the subject to the grouped unit test charts.
Claims (9)
1. An abnormal color vision test chart synthesis method based on pseudo-same color search comprises the following steps:
step 1: searching pseudo-same color pairs, namely traversing and simulating candidate colors on an RGB grid space, and calculating perceived color difference before and after the candidate color simulation;
the step 1 comprises the following steps:
step 1.1: selecting candidate colors, namely performing grid division on an RGB space, and randomly performing tiny offset on nodes of grids or taking each grid node as a center to select the candidate colors;
step 1.2: calculating the artificial colour, i.e. candidate colour vector for selected triples
The corresponding color vector +.A corresponding color vector is obtained through a color blind simulation algorithm>
Wherein τ ε [ d, p, t ]]List items [ d, p, t ]]Respectively representing green color blindness, red color blindness and blue color blindness;
step 1.3: calculating perceived color difference, i.e. converting RGB color to XYZ color space, then to LAB color space, and then calculating { Q, Q }, using CIE Lab1976 color difference formula τ Color difference value Δe between } Lab (Q,Q τ )；
Step 2: selecting a false same-color pair, namely judging a threshold condition, selecting the false same-color pair, and storing the false same-color pair;
the step 2 comprises the following steps:
step 2.1: judging the threshold condition, namely setting the threshold condition to be alpha more than or equal to 0, when delta E is Lab (Q,Q τ ) When not less than alpha, the pseudo-homochromatic pair { Q, Q is reserved τ -as an element in the set of fill colors; when delta E Lab (Q,Q τ ) Discarding pseudo-homochromatic pairs when alpha is less than or equal to alpha
{Q,Q τ -wherein α is a settable parameter, the physical meaning is a color difference threshold;
step 2.2: selecting false same-color pairs, namely calculating all candidate colors, judging the threshold condition, and respectively selecting elements in a false same-color pair set according to a set color difference threshold alpha;
step 2.3: storing the pseudo-same-color pair, namely storing the selected pseudo-same-color set;
step 3: generating a test image, namely selecting a color blindness test pattern, filling a foreground and a background with a pseudo-same color pair to form a unit test pattern, and grouping the unit test pattern;
the step 3 comprises the following steps:
step 3.1: selecting a test pattern, namely selecting geometric shapes which are convenient to identify and common patterns in life as the test pattern, combining any false same-color pair generated in the process as a foreground color and a background color respectively, and filling the foreground and the background of the test pattern;
step 3.2: filling the test pattern, namely filling the test pattern by adopting the selected pseudo-same color pair;
step 3.3: generating a test unit, namely filling the test pattern to obtain a three-channel color image serving as the test unit;
step 3.4: the test images are grouped, i.e. a plurality of test units are selected randomly and combined into a group of test images.
2. The abnormal color vision test chart synthesizing method based on pseudo-same color search as defined in claim 1, wherein the abnormal color vision test chart synthesizing method is characterized by comprising the following steps:
in the step 1.1, dividing the RGB color space into grids of X multiplied by Y multiplied by Z, wherein the size is 32 multiplied by 32, and selecting a triplet candidate color vector on a node of the grid;
corresponding color vector Q in step 1.2 τ Is calculated as follows: firstly, converting the triplet candidate color vector Q into an LMS space to obtain a corresponding color vector in the LMS space, wherein the color vector is represented by the following formula:
wherein the method comprises the steps of
A transformation matrix for the RGB color space to the LMS color space;
and then using a color blindness simulation algorithm to obtain tau-type color blindness simulation vectors in the LMS color space:
wherein T is sim τ The transformation matrix is used in the color blindness simulation algorithm;
the tau-color blind simulation vector of the LMS color space is then converted back into an RGB space vector, i.e.,
wherein Q is τ Corresponding colors, i.e., { Q, are simulated for achromatopsia of the triplet candidate color vector Q τ -a pair of pseudo-homochromes;
in step 1.3 { Q, Q is calculated according to the following formula τ Color difference value between }:
ΔE* Lab (Q,Q τ )＝[(L Q *-L Qτ *) 2 +(a Q *-a Qτ *) 2 +(b Q *-b Qτ *) 2 ]
wherein (L) Q *,a Q *,b Q * ) Representing the result of conversion of candidate color Q into LAB space, (L) Qτ *,a Qτ *,b Qτ * ) Representing the simulation color Q τ Three components after conversion to LAB space;
step 2.1 employs α=50;
step 2.2, randomly selecting in the selected pseudo-same color pair set, or directly picking up color elements in the set after visualization;
the storage mode in the step 2.3 can adopt a hash list or dictionary data structure, and a file format can use JSON or Pickle objects;
randomly generating numbers 0-9 as foreground contents and the rest blank area as background in the step 3.1 to form a test pattern;
in step 3.4, 5*5 unit test patterns are selected to form one test image.
3. The abnormal color vision test chart synthesizing method based on pseudo-same color search as defined in claim 2, wherein the abnormal color vision test chart synthesizing method is characterized in that:
in step 1.1, the RGB color space is divided into grids of X Y X Z, and the grids are divided into grid nodes (X 0 ,y 0 ,z 0 ) As a center, the points reached by the random small step offsets (Δx, Δy, Δz) in each direction are used as triplet candidate color vectors.
4. The abnormal color vision test chart synthesizing method based on pseudo-same color search as defined in claim 2, wherein the abnormal color vision test chart synthesizing method is characterized in that:
in the step 3.2, the test pattern is directly filled with the pseudo-same color pair, the simulated color is used as the background filling color, and the original color is used as the foreground filling color.
5. The abnormal color vision test chart synthesizing method based on pseudo-same color search as defined in claim 2, wherein the abnormal color vision test chart synthesizing method is characterized in that:
and 3.2, filling the test pattern with the pseudo-same color pair split type, and drawing small circle geometric patterns which are not overlapped with each other by adopting a K-D tree data structure to form a split type test pattern unit.
6. The abnormal color vision test chart synthesizing method based on pseudo-same color search as defined in claim 2, wherein the abnormal color vision test chart synthesizing method is characterized in that:
in step 3.2, the test pattern is filled with the approximate color generalization of the pseudo-same color pair, and similar colors are randomly picked up according to Gaussian distribution in a sphere space with the pseudo-same color as a sphere center and the radius rho in an LAB color space to fill small geometric patterns generated each time, wherein rho is more than 0 and less than 32.
7. The abnormal color vision test chart synthesizing method based on pseudo-same color search as defined in claim 3, wherein the abnormal color vision test chart synthesizing method is characterized in that: step 1.1 taking a die of small step size
Wherein Δx, Δy, Δz are integers;
the test pattern is filled in a fine density checkered pattern in step 3.2.
8. An abnormal color vision test chart application device is characterized in that: the image generated by the false same color search based abnormal color vision test chart synthesis method according to any one of claims 1 to 7 can be used for a special color vision detection computer device, embedded software and hardware, paper printing device or internet application software system.
9. The abnormal color vision test chart application apparatus according to claim 8, wherein: the color vision detection computer device comprises various types of computers, mobile terminals, virtual Reality (VR) equipment such as Oculus, google glasses, iPad tablet computers, special displays and medical eye vision tester equipment, wherein the method for synthesizing the color vision test patterns is realized by using the off-line or on-line application of the development of the corresponding medical eye vision tester equipment in a software system, and the color vision test patterns are presented on a display screen by taking unit test patterns and grouping test patterns as use cases; the embedded software and hardware and paper printing device realizes a color vision test chart synthesis method by a corresponding programming language through a singlechip, various embedded systems of an FPGA and a development board, or synthesizes color vision test charts on other hardware platforms in advance, and then stores the color vision test charts in embedded equipment for display or printing; the Internet application software system develops and realizes the color vision test synthesis method in various programming languages such as Javascript and hypertext markup language, or presents a color vision test chart at a browser or APP end in a micro-service and off-line application mode and combines with an interactive design to implement color vision test.
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