Color vision test training system and method based on dynamic brightness change and multi-color

Abstract

The present invention provides a color vision test training system based on dynamic brightness changes and multiple colors, characterized by comprising: an initialization module; a block color reset module; a target recognition grid update module; and a terminal drawing module. The present invention also provides a color vision test training method based on dynamic brightness changes and multiple colors. The brightness of the present invention can dynamically change over time, and the present invention mixes multiple colors together to stimulate color-blind patients through a combination of brightness changes and multi-color visual effects. In addition, the area to be identified in the present invention can randomly appear at any position in the display area. Therefore, regardless of the number of uses, the present invention can utilize the dynamic changing visual effects over time to achieve the same stimulation effect on the same patient and realize accurate testing of the same patient.

Description

Technical Field

[0001] The invention relates to a color vision test training system and a method implemented based on the color vision test training system. Background Art

[0002] According to common sense among those skilled in the art, at least 80% of external information is acquired through vision, making vision the most important sense for humans and animals. While most cases of color deficiency are caused by genetic factors, some acquired factors can also contribute, such as optic neuropathy, eye aging, retinal degeneration, brain disease, medications, and psychological factors. Prolonged use of electronic screens can accelerate eye aging and lead to optic neuropathy and retinal degeneration. Therefore, with people's increasing dependence on electronic products, the number of people with color deficiency is increasing year by year. However, there is currently no reliable, training-based color deficiency assessment system on the market. Retrieved related published patent applications include: Patent application number CN106199954A discloses an optical device and design method for correcting blue-yellow color blindness. By selecting colorants and their concentrations and designing a transmission spectrum for correcting blue-yellow color blindness, this device can correct the color perception of individuals with blue-yellow color blindness, improving blue-yellow color resolution while preserving or slightly altering the position of the user's white point. This patent focuses on designing a device to correct blue-yellow color blindness and cannot be used to test color blindness. Some color blindness detection and assessment systems currently available on the market use a single color change or a single brightness change. After repeated use on the same patient, such a system can easily cause the patient to remember the correct location of the color block to be identified, leading to inaccurate testing. Furthermore, the more times the system is used on the same patient, the worse the stimulation effect, failing to achieve the desired training goal. Summary of the Invention

[0003] The technical problem to be solved by the present invention is that some existing color weakness detection and evaluation systems on the market are all single color changes or single brightness changes.

[0004] In order to solve the above technical problems, a technical solution of the present invention is to provide a color vision test training system based on dynamic brightness changes and multiple colors, characterized by comprising:

[0005] An initialization module is used to initialize the HSL color space color values ​​of N groups of large color groups and the HSL color space background color values ​​under N color modes, wherein the N groups of large color groups correspond to the N color modes one-to-one, and the N groups of large color groups and the N color modes correspond to N different color systems, N ≥ 1. The initialization module initializes the HSL color space color values ​​of M different colors under the same color system in each group of large color groups, M ≥ 2;

[0006] The HSL color space background color value in the nth color mode obtained by the initialization module is expressed as hatterszin-n, n=1,…,N; the H, S, and L components of the HSL color space color value of the mth color in the nth large color group obtained by the initialization module are expressed as n[H m ]、n[S m ]、n[L m ], m=1,2,…,M;

[0007] A square color reset module is used to reset the colors of all squares in the display area according to the currently used color mode and the HSL color space background color value in the current color mode, where the display area consists of R×C squares, where R and C represent the predetermined number of rows and columns respectively;

[0008] The H, S, and L components of the HSL color space color value of the i-th square in the display area are expressed as iH, iS, and iL. If the currently used color mode is the n-th color mode, then for the i-th square in the display area, iH = hatterszin-n[H], iS = hatterszin-n[S], and iL = hatterszin-n[L], where hatterszin-n[H], hatterszin-n[S], and hatterszin-n[L] respectively represent the H, S, and L components of the background color value hatterszin-n in the HSL color space;

[0009] The target recognition grid update module is used to calculate the position of the area to be recognized in the display area and assign colors to all squares in the area to be recognized based on the currently used color mode and the HSL color space color value in the corresponding large color group. The area to be recognized consists of r×c squares out of R×C squares, where r and c represent the predetermined number of rows and columns, respectively, and r<<R, c<<C;

[0010] The H, S, and L components of the HSL color space color value of the jth square in the area to be identified are expressed as jH, jS, and jL. If the current color mode is the nth color mode, and the area to be identified needs to display the mth color in the nth large color group, then jH=n[H m ]、jS=n[S m ]、jL=n[L m ];

[0011] Dynamic brightness calculation module, used to periodically update the L component of all squares in the display area;

[0012] The terminal drawing module is used to draw the display area and display the area to be identified on the display area.

[0013] Preferably, the M HSL color space color values ​​are arranged in order in the large color group according to the visual sensitivity of the human eye.

[0014] Preferably, the number of rows R is divisible by the number of rows r, and the number of columns C is divisible by the number of columns c.

[0015] Preferably, for the mth color in the nth large color group, the target recognition grid updating module determines the position of the upper left corner grid in the area to be recognized according to the following formula, thereby obtaining the position of the area to be recognized in the display area:

[0016] tesztkocka[m]=Math.floor(Math.random()×(C-2)+1)×C+Math.floor(Math.random()×(C-2)+1)

[0017] In the formula, Math.random() means generating a random number between 0 and 1, and Math.floor(·) means rounding.

[0018] Preferably, for the i-th square in the display area, in the current cycle, the dynamic brightness calculation module calculates the L component iL of the color displayed by the i-th square using the following formula:

[0019] iL=i-L+Math.sin(sinVal×3.14 / 2)

[0020] Where: Math.sin() is used to output a number between -1 and 1;

[0021] sinVal=Math.random()×10+0.1+Math.random() / 10, where Math.random() means generating a random number between 0 and 1.

[0022] Another technical solution of the present invention is to provide a color vision test training method based on dynamic brightness changes and multiple colors, using the above-mentioned color vision test training system, characterized by comprising the following steps:

[0023] Step 1: Initialize the HSL color space color values ​​of N groups of large color groups and the HSL color space background color values ​​under N color modes through the initialization module;

[0024] Step 2: Perform color vision test training for N color modes in sequence, wherein the color vision test training for the nth color mode includes the following steps:

[0025] Step 201: The square color resetting module resets the colors of all squares in the display area according to the HSL color space background color value in the nth color mode obtained by the initialization module;

[0026] Step 202: The target recognition grid updating module obtains the position of the area to be recognized in the display area, and assigns colors to all grids in the area to be recognized based on the mth HSL color space color value in the nth large color group.

[0027] Step 203: The dynamic brightness calculation module periodically updates the L component of the color displayed by all the squares in the display area;

[0028] Step 204: The terminal drawing module draws a display area, and displays the area to be identified on the display area;

[0029] Step 205: After the trainee completes the recognition of the area to be recognized, if all colors in the nth large color group have been traversed, the color vision test training of the nth color mode is performed; otherwise, the process returns to step 202 until all colors in the nth large color group have been traversed.

[0030] Preferably, in step 2, color vision test training of N color modes is performed in sequence from high sensitivity to low sensitivity according to the sensitivity of the human eye to different color systems.

[0031] Preferably, in step 2, when performing color vision test training of the nth color mode, different colors of areas to be identified are displayed in sequence from high sensitivity to low sensitivity in the display area according to the sensitivity of the human eye to different colors in the current color system.

[0032] The brightness of the present invention can change dynamically over time, and the present invention confuses multiple colors together to stimulate color-blind patients through a combination of brightness changes and multi-color visual effects. In addition, the area to be identified in the present invention can randomly appear at any position in the display area. Therefore, no matter how many times it is used, the present invention can utilize the dynamically changing visual effects over time to achieve the same stimulation effect on the same patient and realize accurate testing of the same patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Flowchart of the present invention. DETAILED DESCRIPTION

[0034] Below in conjunction with specific embodiment, further set forth the present invention.Should be understood that these embodiments are only used to illustrate the present invention and are not used in limiting the scope of the present invention.In addition, should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall equally within the scope limited by the appended claims of the application.

[0035] This embodiment discloses a color vision test training system based on dynamic brightness changes and multiple colors, including:

[0036] Initialization module 1:

[0037] In this embodiment, all colors are divided into three large color groups according to three color systems. In each large color group, different colors of the same color system are represented by color values ​​in the HSL color space. The three large color groups are represented by R, P, and D respectively, and then:

[0038] R=[0,100,28,6,98,28,11,95,28,15,93,28,19,90,27,27,87,26,34,84,25,40,82,26,46,80,26,59,79,26, 72,77,25,72,76,24,72,75,22,78,76,23,83,76,23,89,76,23,95,76,22,99,77,21,103,77,19,106,78,20];

[0039] P=[240,100,29,243,100,29,246,100,28,249,100,27,252,100,26,255,100,26,258,100,25,261,100,25,264,100,24,267,100,24 ,270,100,23,273,100,22,276,100,21,279,100,21,282,100,20,285,100,20,288,100,19,291,100,18,294,100,17,297,100,17];

[0040] D=[173,37,25,176,29,27,178,23,28,183,16,29,191,10,31,213,7,32,260,5,32,295,8,32,311,13,33,320,18,33, 324,22,34,324,25,34,324,28,35,327,35,35,327,42,36,327,45,36,327,48,36,327,50,36,325,62,35,324,74,35];

[0041] In the large color group R, taking 0, 100, 28 as an example, they are the H, S, and L components of the same color in the HSL color space. The others are similar and will not be repeated here.

[0042] All colors are arranged in descending order in the large color group according to the sensitivity of the human eye to different colors in the corresponding color system.

[0043] The three color systems also correspond to the three color modes. The initialization module 1 initializes the corresponding HSL color space background color value for each color mode. It should be noted that the HSL color space background color value is different from the color value in the large color group.

[0044] In this embodiment, the three HSL color space background color values ​​corresponding to the three large color groups are:

[0045] hatterszin-R=[111,78,20]

[0046] hatterszin-P=[300,100,16]

[0047] hatterszin-D=[323,87,34]

[0048] hatterszin-R, hatterszin-P, and hatterszin-D are the three HSL color space background color values ​​corresponding to the large color groups R, P, and D, respectively.

[0049] Block color reset module 2:

[0050] The square color resetting module 2 is used to reset the colors of all squares in the display area according to the current color mode and the HSL color space background color value in the current color mode. In this embodiment, the display area consists of 18×18 squares.

[0051] If it is R color mode, the block color reset module 2 resets the colors of all blocks to:

[0052] 1-H=hatterszin-R[0]

[0053] 1-S=hatterszin-R[1]

[0054] 1-L=hatterszin-R[2]

[0055] 2-H=hatterszin-R[0]

[0056] 2-S=hatterszin-R[1]

[0057] 2-L=hatterszin-R[2] ...

[0059] 324-H=hatterszin-R[0]

[0060] 324-S=hatterszin-R[1]

[0061] 324-L=hatterszin-R[2]

[0062] Among them, 1-H, 1-S, and 1-L represent the H, S, and L components of the color displayed by the first square, and so on; hatterszin-R[0], hatterszin-R[1], and hatterszin-R[2] represent the first, second, and third elements of hatterszin-R, 111, 78, and 20, respectively.

[0063] If it is the P color mode, the block color reset module 2 resets the colors of all squares to:

[0064] 1-H=hatterszin-P[0]

[0065] 1-S=hatterszin-P[1]

[0066] 1-L=hatterszin-P[2]

[0067] 2-H=hatterszin-P[0]

[0068] 2-S=hatterszin-P[1]

[0069] 2-L=hatterszin-P[2] ...

[0071] 324-H=hatterszin-P[0]

[0072] 324-S=hatterszin-P[1]

[0073] 324-L=hatterszin-P[2]

[0074] For the explanation of all parameters, please refer to the above and will not be repeated here.

[0075] If it is D color mode, the block color reset module 2 resets the colors of all squares to:

[0076] 1-H=hatterszin-D[0]

[0077] 1-S=hatterszin-D[1]

[0078] 1-L=hatterszin-D[2]

[0079] 2-H=hatterszin-D[0]

[0080] 2-S=hatterszin-D[1]

[0081] 2-L=hatterszin-D[2] ...

[0083] 324-H=hatterszin-D[0]

[0084] 324-S=hatterszin-D[1]

[0085] 324-L=hatterszin-D[2]

[0086] For the explanation of all parameters, please refer to the above and will not be repeated here.

[0087] Target recognition grid update module 4:

[0088] The target recognition grid updating module 4 can calculate the position of the area to be recognized in the display area. In this embodiment, the area to be recognized consists of 3×3 grids. The target recognition grid updating module 4 can determine the position of the upper left corner grid of the area to be recognized in the display area as shown below:

[0089] tesztkocka[1]=Math.floor(Math.random()*16+1)*18+Math.floor(Math.random()*16+1);

[0090] tesztkocka[2]=Math.floor(Math.random()*16+1)*18+Math.floor(Math.random()*16+1); ...

[0092] tesztkocka

[20] =Math.floor(Math.random()*16+1)*18+Math.floor(Math.random()*16+1);

[0093] Where tesztkocka[1] represents the position of the upper left corner square of the area to be identified in the display area when the area to be identified displays the first color in the large color group R, P, or D, and so on; Math.floor() represents rounding; Math.random() represents generating a random number between 0 and 1.

[0094] The target recognition grid updating module 4 is further configured to assign colors to all grids in the area to be recognized according to the currently used color mode and the HSL color space color values ​​in the corresponding large color group.

[0095] In this embodiment, if the color mode is R, then:

[0096] tesztkocka[1]-H=R[3*0]

[0097] tesztkocka[1]-S=R[3*0+1]

[0098] tesztkocka[1]-L=R[3*0+2]

[0099] tesztkocka[2]-H=R[3*1]

[0100] tesztkocka[2]-S=R[3*1+1]

[0101] tesztkocka[2]-L=R[3*1+2] ...

[0103] tesztkocka

[20] -H=R[3*19]

[0104] tesztkocka

[20] -S=R[3*19+1]

[0105] tesztkocka

[20] -L=R[3*19+2]

[0106] If it is P color mode, then:

[0107] tesztkocka[1]-H=P[3*0]

[0108] tesztkocka[1]-S=P[3*0+1]

[0109] tesztkocka[1]-L=P[3*0+2]

[0110] tesztkocka[2]-H=P[3*1]

[0111] tesztkocka[2]-S=P[3*1+1]

[0112] tesztkocka[2]-L=P[3*1+2] ...

[0114] tesztkocka

[20] -H=P[3*19]

[0115] tesztkocka

[20] -S=P[3*19+1]

[0116] tesztkocka

[20] -L=P[3*19+2]

[0117] If it is D color mode, then:

[0118] tesztkocka[1]-H=D[3*0]

[0119] tesztkocka[1]-S=D[3*0+1]

[0120] tesztkocka[1]-L=D[3*0+2]

[0121] tesztkocka[2]-H=D[3*1]

[0122] tesztkocka[2]-S=D[3*1+1]

[0123] tesztkocka[2]-L=D[3*1+2] ...

[0125] tesztkocka

[20] -H=D[3*19]

[0126] tesztkocka

[20] -S=D[3*19+1]

[0127] tesztkocka

[20] -L=D[3*19+2]

[0128] tesztkocka[1]-H, tesztkocka[1]-S, tesztkocka[1]-L respectively represent the H, S, and L components of the color filled in the first square in the area to be identified, and so on; R[3*0] represents the value of the 3*0th element in the large color group R, and so on.

[0129] Dynamic brightness calculation module 3:

[0130] The dynamic brightness calculation module 3 is used to periodically update the L component of the color displayed by all squares in the display area every 16 milliseconds. By changing the brightness unit of the color every 16 milliseconds, it affects the effect of stimulating color-blind patients, so that there is no regularity in each test, thereby achieving a more professional color-blind test effect.

[0131] For the i-th square in the display area, in the current cycle, the dynamic brightness calculation module calculates the L component iL of the color displayed by the i-th square using the following formula:

[0132] iL=i-L+Math.sin(sinVal×3.14 / 2)

[0133] Where: Math.sin() is used to output a number between -1 and 1;

[0134] sinVal=Math.random()×10+0.1+Math.random() / 10, where Math.random() means generating a random number between 0 and 1.

[0135] In this embodiment, there are:

[0136] 1-L=1-L+Math.sin(sin=Val*3.14 / 2)

[0137] 2-L=2-L+Math.sin(sinVal*3.14 / 2) ...

[0139] 324-L=324-L+Math.sin(sinVal*3.14 / 2).

[0140] The terminal drawing module 5 is used to draw the display area and display the area to be identified on the display area.

[0141] This embodiment also discloses a color vision test training method based on dynamic brightness changes and multiple colors, which uses the above-mentioned color vision test training system and includes the following steps:

[0142] Step 1: Initialize the HSL color space color values ​​of three large color groups and the HSL color space background color values ​​under three color modes through the initialization module 1;

[0143] Step 2: Perform color vision test training for three color modes in sequence. The color vision test training for any nth color mode includes the following steps, where n = 1, 2, 3:

[0144] Step 201: The square color resetting module 2 resets the colors of all squares in the display area according to the HSL color space background color value in the nth color mode obtained by the initialization module 1;

[0145] Step 202: The target recognition grid updating module 4 obtains the position of the area to be recognized in the display area, and assigns colors to all grids in the area to be recognized based on the mth HSL color space color value in the nth large color group, where m = 1, 2, ..., 20.

[0146] Step 203: The dynamic brightness calculation module 3 periodically updates the L component of the color displayed by all the squares in the display area;

[0147] Step 204: The terminal drawing module 5 draws a display area, and displays the area to be identified on the display area;

[0148] Step 205: After the trainee completes the recognition of the area to be recognized, if all 20 colors in the nth group of large color groups have been traversed, the color vision test training of the nth color mode will be performed; otherwise, the process returns to step 202 until all 20 colors in the nth group of large color groups have been traversed.

Claims

1. A color vision test and training system based on dynamic brightness changes and multiple colors, characterized in that: include: An initialization module is used to initialize the HSL color space color values ​​of N groups of large color groups and the HSL color space background color values ​​under N color modes, wherein the N groups of large color groups correspond to the N color modes one-to-one, and the N groups of large color groups and the N color modes correspond to N different color systems, N ≥ 1. The initialization module initializes the HSL color space color values ​​of M different colors under the same color system in each group of large color groups, M ≥ 2; The HSL color space background color value in the nth color mode obtained by the initialization module is expressed as hatterszin-n, n=1,…,N; the H, S, and L components of the HSL color space color value of the mth color in the nth large color group obtained by the initialization module are expressed as n[H m ]、n[S m ]、n[L m ], m=1,2,…,M; A square color reset module is used to reset the colors of all squares in the display area according to the currently used color mode and the HSL color space background color value in the current color mode, where the display area consists of R×C squares, where R and C represent the predetermined number of rows and columns respectively; The H, S, and L components of the HSL color space color value of the i-th square in the display area are expressed as iH, iS, and iL. If the currently used color mode is the n-th color mode, then for the i-th square in the display area, iH = hatterszin-n[H], iS = hatterszin-n[S], and iL = hatterszin-n[L], where hatterszin-n[H], hatterszin-n[S], and hatterszin-n[L] respectively represent the H, S, and L components of the background color value hatterszin-n in the HSL color space; The target recognition grid update module is used to calculate the position of the area to be recognized in the display area and assign colors to all squares in the area to be recognized based on the currently used color mode and the HSL color space color value in the corresponding large color group. The area to be recognized consists of r×c squares out of R×C squares, where r and c represent the predetermined number of rows and columns, respectively, and r<<R, c<<C; The H, S, and L components of the HSL color space color value of the jth square in the area to be identified are expressed as jH, jS, and jL. If the current color mode is the nth color mode, and the area to be identified needs to display the mth color in the nth large color group, then jH=n[H m ]、jS=n[S m ]、jL=n[L m ]; Dynamic brightness calculation module, used to periodically update the L component of all squares in the display area; The terminal drawing module is used to draw the display area and display the area to be identified on the display area.

2. A color vision test and training system based on dynamic brightness changes and multiple colors as claimed in claim 1, characterized in that: The M HSL color space color values ​​are arranged in order in the large color group according to the visual sensitivity of the human eye.

3. A color vision test and training system based on dynamic brightness changes and multiple colors as claimed in claim 1, characterized in that: The number of rows R is divisible by the number of rows r, and the number of columns C is divisible by the number of columns c.

4. A color vision test and training system based on dynamic brightness changes and multiple colors as claimed in claim 1, characterized in that: For the mth color in the nth large color group, the target recognition grid updating module determines the position of the upper left corner grid in the area to be recognized according to the following formula, thereby obtaining the position of the area to be recognized in the display area: tesztkocka[m]=Math.floor(Math.random()×(C-2)+1)×C+Math.floor(Math.random()×(C-2)+1) In the formula, Math.random() means generating a random number between 0 and 1, and Math.floor(·) means rounding.

5. A color vision test and training system based on dynamic brightness changes and multiple colors as claimed in claim 1, characterized in that: For the i-th square in the display area, in the current cycle, the dynamic brightness calculation module calculates the L component iL of the color displayed by the i-th square using the following formula: iL=i-L+Math.sin(sinVal×3.14 / 2) Where: Math.sin() is used to output a number between -1 and 1; sinVal=Math.random()×10+0.1+Math.random() / 10, where Math.random() means generating a random number between 0 and 1.

6. A color vision test training method based on dynamic brightness changes and multiple colors, using the color vision test training system according to claim 1, characterized in that: The following steps are involved: Step 1: Initialize the HSL color space color values ​​of N groups of large color groups and the HSL color space background color values ​​under N color modes through the initialization module; Step 2: Perform color vision test training for N color modes in sequence, wherein the color vision test training for the nth color mode includes the following steps: Step 201: The square color resetting module resets the colors of all squares in the display area according to the HSL color space background color value in the nth color mode obtained by the initialization module; Step 202: The target recognition grid updating module obtains the position of the area to be recognized in the display area, and assigns colors to all grids in the area to be recognized based on the mth HSL color space color value in the nth large color group. Step 203: The dynamic brightness calculation module periodically updates the L component of the color displayed by all the squares in the display area; Step 204: The terminal drawing module draws a display area, and displays the area to be identified on the display area; Step 205: After the trainee completes the recognition of the area to be recognized, if all colors in the nth large color group have been traversed, the color vision test training of the nth color mode is performed; otherwise, the process returns to step 202 until all colors in the nth large color group have been traversed.

7. A color vision test training method based on dynamic brightness changes and multiple colors as claimed in claim 6, characterized in that: In step 2, color vision test training of N color modes is performed in sequence from high sensitivity to low sensitivity according to the sensitivity of the human eye to different color systems.

8. A color vision test training method based on dynamic brightness change and multiple colors as claimed in claim 6, characterized in that: In step 2, when the color vision test training of the nth color mode is performed, according to the sensitivity of the human eye to different colors in the current color system, the areas to be identified of different colors are displayed in sequence from high sensitivity to low sensitivity in the display area.

Images