阅读说明：本技术 视觉状态检测方法 (Visual state detection method ) 是由 魏志达 黄谦杰 陈欣怡 于 2019-04-19 设计创作，主要内容包括：本发明提供一种视觉状态检测方法,所述方法包含：步骤A：处理单元决定难度指数当前的数值；步骤B：经由显示单元显示题目,所述题目包含至少一动态波纹影像,且所述动态波纹影像的波纹的默认属性与所述难度指数当前的数值相关；步骤C：所述处理单元经由输入单元接收作答内容；步骤D：所述处理单元根据步骤C的所述作答内容产生批改结果；步骤E：所述处理单元根据步骤D的所述批改结果判断是否符合结束条件,若动态波纹影像否,则再次执行步骤A～E,若是,则执行步骤F；及步骤F：所述处理单元产生检测结果,所述检测结果与所述难度指数当前的数值相关。本发明能够适合一般大众随时自我检测,又实作简单并具有可携带性。(The invention provides a visual state detection method, which comprises the following steps: step A: the processing unit determines the current numerical value of the difficulty index; and B: displaying a title through a display unit, wherein the title comprises at least one dynamic ripple image, and the default attribute of the ripple of the dynamic ripple image is related to the current numerical value of the difficulty index; and C: the processing unit receives answering content through the input unit; step D: the processing unit generates a correction result according to the answering content in the step C; step E: the processing unit judges whether the correction result meets the end condition or not according to the correction result in the step D, if the dynamic ripple image is not, the steps A to E are executed again, and if the dynamic ripple image is not, the step F is executed; and step F: the processing unit generates a detection result, and the detection result is related to the current numerical value of the difficulty index. The invention is suitable for the general public to self-detect at any time, and has simple implementation and portability.)

1. A visual state detection method is implemented by an electronic device, wherein the electronic device is operated by a user and comprises an input unit, a display unit and a processing unit, and the visual state detection method comprises the following steps:

step A: the processing unit determines the current numerical value of the difficulty index;

and B: the processing unit displays a title through the display unit, wherein the title comprises at least one dynamic ripple image, and the default attribute of the ripple of the dynamic ripple image is related to the current numerical value of the difficulty index;

and C: the processing unit receives answering content which is input by the user and corresponds to the topic through the input unit;

step D: the processing unit generates a correction result according to the answer content of the step C, wherein the correction result indicates that the answer content of the step C is correct or incorrect;

step E: the processing unit judges whether the correction result meets the end condition or not according to the correction result in the step D, if not, the step A, the step B, the step C, the step D and the step E are executed again, and if yes, the step F is executed; and

step F: the processing unit generates a detection result, and the detection result is related to the current numerical value of the difficulty index.

2. The method according to claim 1, wherein each topic comprises one number of the dynamic moire images, and each topic further comprises an answer prompt for the user to answer the wave center position of the dynamic moire image.

3. The method according to claim 1, wherein each topic comprises one number of the dynamic moire images, and each topic further comprises an answer prompt for the user to answer a moving direction of the moire of the dynamic moire image.

4. The method according to claim 1, wherein each topic comprises two or more of the dynamic moire images, and each topic further comprises a contrast image and an answer prompt, wherein the content of the contrast image is different from the content of the dynamic moire image, and the answer prompt prompts the user to select the contrast image.

5. The method according to claim 1, wherein each topic comprises one number of the dynamic moire images, and each topic further comprises a plurality of contrast images and response prompts, wherein the content of the contrast images is different from the content of the dynamic moire images, and the response prompts prompt the user to select the dynamic moire images.

6. The method of claim 5, wherein the content of each control image is free of ripples.

7. The method of claim 5, wherein the content of each control image has ripples, and the default attribute of the ripples of each control image is related to a value of a control difficulty index that is different from a current value of the difficulty index.

8. The method according to claim 5, wherein the content of each control image has ripples, and the default property of the ripples of each control image is related to the value of a control difficulty index, the value of the control difficulty index is the same as the current value of the difficulty index, and the target property of the ripples of the control image different from the default property is different from the target property of the dynamic ripple image.

9. The visual state detection method of claim 1, wherein the wavelength of the waviness of the dynamic moire image of each topic is inversely related to the difficulty index.

10. The visual state detection method of claim 1, wherein the amplitude of the waviness of the dynamic waviness image of each topic is inversely related to the difficulty index.

11. The visual state detection method of claim 1, wherein the frequency of waviness of the dynamic moire image of each subject is positively correlated with the difficulty index.

12. The method of claim 1, further comprising, before step A:

step G: the processing unit determines an execution state of the processing unit, wherein the execution state is a first state of a difficulty increasing stage, a second state of the difficulty increasing stage, a first state of a difficulty decreasing stage or a second state of the difficulty decreasing stage;

if the judgment result of the step E is negative, executing the step G, the step A, the step B, the step C, the step D and the step E again;

when the execution state of the processing unit before the step G is the first state of the difficulty raising stage and the batch result generated by the last execution of the step D indicates that the response content is correct, the execution state of the processing unit in the step G is maintained;

when the execution state of the processing unit before step G is the first state of the difficulty raising stage and the batching result generated by the last execution of step D indicates that the response content is incorrect, changing the execution state of the processing unit to the second state of the difficulty raising stage in step G;

when the execution state of the processing unit before the step G is the second state of the difficulty raising stage and the batch result generated by the last execution of the step D indicates that the response content is correct, changing the execution state of the processing unit to the first state of the difficulty raising stage in the step G;

when the execution state of the processing unit before step G is the second state of the difficulty-raising stage and the batching result generated by the last execution of step D indicates that the response content is incorrect, changing the execution state of the processing unit to the first state of the difficulty-lowering stage in step G;

when the execution state of the processing unit before step G is the first state of the difficulty decreasing stage and the batching result generated by the last execution of step D indicates that the response content is incorrect, the execution state of the processing unit in step G remains unchanged;

when the execution state of the processing unit before the step G is changed to the first state of the difficulty decreasing stage and the modification result generated by the last execution of the step D indicates that the response is correct, the execution state of the processing unit is changed to the second state of the difficulty decreasing stage in the step G;

when the execution state of the processing unit before step G is the second state of the difficulty decreasing stage and the result of the batch modification generated by the last execution of step D indicates that the answer content is incorrect, changing the execution state of the processing unit to the first state of the difficulty decreasing stage in step G;

when the processing unit executes the step A in the first state of the difficulty increasing stage, the processing unit increases the value of the difficulty index by a first default value;

when the processing unit executes the step A in the second state of the difficulty increasing stage, the processing unit keeps the value of the difficulty index unchanged;

when the processing unit executes the step A in the first state of the difficulty level decreasing stage, the processing unit decreases the value of the difficulty index by a second default value;

when the processing unit executes the step a in the second state of the difficulty level decreasing stage, the processing unit keeps the value of the difficulty index unchanged.

13. The method according to claim 12, wherein in step E, the end condition is that the current execution status of the processing unit is the second status of the difficulty decreasing stage, and the result of the batch change generated by the last execution of step D indicates that the response content is correct.

14. The visual state detection method of claim 12, wherein the execution state can also be a first state of a difficulty rapid-rise phase or a second state of the difficulty rapid-rise phase;

when the execution state of the processing unit before the step G is the first state of the difficulty rapid-rise stage and the batch result generated by the last execution of the step D indicates that the response content is correct, the execution state of the processing unit in the step G is maintained;

when the execution state of the processing unit before step G is the first state of the difficulty fast-raising stage and the batching result generated by the last execution of step D indicates that the response content is incorrect, changing the execution state of the processing unit to the second state of the difficulty fast-raising stage in step G;

when the execution state of the processing unit before step G is the second state of the difficulty increasing stage and the modification result generated by the last execution of step D indicates that the response is correct, then the execution state of the processing unit is changed to the first state of the difficulty increasing stage in step G;

when the execution state of the processing unit before step G is the second state of the difficulty rapidly increasing stage and the batching result generated by the last execution of step D indicates that the response content is incorrect, the execution state of the processing unit in step G remains unchanged;

when the processing unit executes the step a in the first state of the difficulty rapid rise stage, the processing unit increases the value of the difficulty index by a first adjustment value, and the first adjustment value is greater than the first default value;

when the processing unit executes the step a in the second state of the difficulty rapid-rise stage, the processing unit decreases the value of the difficulty index by a second adjustment value, where the second adjustment value is greater than the second default value.

Technical Field

The invention relates to a detection method, in particular to a detection method of eyesight.

Background

Currently, visual state detection methods are commonly used, such as visual acuity examination with a blue dalton or schnerren chart, dry eye examination with a contrast acuity chart, or visual fatigue examination with a flash fusion instrument and a hoelel ten scale. Although these detection methods are continuously used in practice, there are some improvements, such as heavy equipment is inconvenient for the general public to carry and expensive equipment is not available for the general users. Therefore, how to develop a new visual state detection method, which is simple to implement, has portability, and is suitable for the general public to perform self-detection at any time becomes a subject to be further discussed by the invention.

Disclosure of Invention

The invention aims to provide a visual state detection method. A visual state detection method is implemented by an electronic device, the electronic device is operated by a user and comprises an input unit, a display unit and a processing unit, and the method comprises the following steps: (A) the processing unit determines the current numerical value of the difficulty index; (B) the processing unit displays a title through the display unit, wherein the title comprises at least one dynamic ripple image, and the default attribute of the ripple of the dynamic ripple image is related to the current numerical value of the difficulty index; (C) the processing unit receives answering content which is input by the user and corresponds to the topic through the input unit; (D) the processing unit generates a correction result according to the answering content of the step (C), wherein the correction result indicates that the answering content of the step (C) is correct or incorrect; (E) the processing unit judges whether the batching result in the step (D) meets an end condition, if not, the step (A), the step (B), the step (C), the step (D) and the step (E) are executed again, and if so, the step (F) is executed; and (F) the processing unit generates a detection result, wherein the detection result is related to the current numerical value of the difficulty index.

In some embodiments, each topic comprises one number of the dynamic moire images, and each topic further comprises an answer prompt for the user to answer the wave center position of the dynamic moire image.

In some embodiments, each topic comprises one number of the dynamic moire images, and each topic further comprises an answer prompt prompting the user to answer a moving direction of the moire of the dynamic moire images.

In some embodiments, each topic includes a number of the motion blur images greater than or equal to two, and each topic further includes a contrast image and an answer prompt, the content of the contrast image is different from the content of the motion blur image, and the answer prompt prompts the user to select the contrast image.

In some embodiments, each topic includes one number of the motion blur images, and each topic further includes a plurality of contrast images and response prompts, wherein the content of the contrast images is different from the content of the motion blur images, and the response prompts prompt the user to select the motion blur images.

In some embodiments, the content of each control image is free of ripples.

In some embodiments, the content of each control image is rippled, and the default attribute of the rippling of each control image is associated with a value of a control difficulty index that is different from a current value of the difficulty index.

In some embodiments, the content of each control image is rippled, and the default attribute of rippling of each control image is related to a value of a control difficulty index, the value of the control difficulty index is the same as the current value of the difficulty index, and a target attribute of rippling of the control image, which is different from the default attribute, is different from the target attribute of the dynamic rippling image.

In some embodiments, the wavelength of the moire of the dynamic moire image for each topic is inversely related to the difficulty index.

In some embodiments, the amplitude of the waviness of the dynamic waviness image of each topic is inversely related to the difficulty index.

In some embodiments, the frequency of waviness of the dynamic waviness image of each topic is positively correlated with the difficulty index.

In some embodiments, before step (a), further comprising: (G) the processing unit determines an execution state of the processing unit, wherein the execution state is a first state of a difficulty increasing stage, a second state of the difficulty increasing stage, a first state of a difficulty decreasing stage, or a second state of the difficulty decreasing stage.

And (E) if the judgment result in the step (E) is negative, executing the step (G), the step (a), the step (B), the step (C), the step (D) and the step (E) again.

When the execution state of the processing unit before the step (G) is the first state of the difficulty raising stage and the modification result generated by the last execution of the step (D) indicates that the response is correct, the execution state of the processing unit in the step (G) is maintained.

When the execution state of the processing unit before the step (G) is executed is the first state of the difficulty raising stage and the modification result generated by the last execution of the step (D) indicates that the response content is incorrect, the execution state of the processing unit is changed to the second state of the difficulty raising stage in the step (G).

When the execution state of the processing unit before the step (G) is the second state of the difficulty raising stage and the modification result generated by the last execution of the step (D) indicates that the response is correct, the execution state of the processing unit is changed to the first state of the difficulty raising stage in the step (G).

When the execution state of the processing unit before the step (G) is changed to the second state of the difficulty increasing stage and the modification result generated by the last execution of the step (D) indicates that the response content is incorrect, the execution state of the processing unit is changed to the first state of the difficulty decreasing stage in the step (G).

When the execution state of the processing unit before the step (G) is executed is the first state of the difficulty decreasing stage and the modification result generated by the last execution of the step (D) indicates that the response content is incorrect, the execution state of the processing unit in the step (G) is maintained.

When the execution state of the processing unit before the step (G) is the first state of the difficulty decreasing stage and the modification result generated by the last execution of the step (D) indicates that the response is correct, the execution state of the processing unit is changed to the second state of the difficulty decreasing stage in the step (G).

When the execution state of the processing unit before the step (G) is changed to the second state of the difficulty decreasing stage and the modification result generated by the last execution of the step (D) indicates that the response content is incorrect, the execution state of the processing unit is changed to the first state of the difficulty decreasing stage in the step (G).

When the processing unit executes the step (a) in the first state of the difficulty raising stage, the processing unit increases the value of the difficulty index by a first default value.

When the processing unit executes the step (a) in the second state of the difficulty increasing stage, the processing unit maintains the value of the difficulty index unchanged.

When the processing unit executes the step (a) in the first state of the difficulty decreasing stage, the processing unit decreases the value of the difficulty index by a second default value.

When the processing unit executes the step (a) in the second state of the difficulty level decreasing stage, the processing unit maintains the value of the difficulty level index unchanged.

In some embodiments, in step (E), the end condition is that the current execution state of the processing unit is the second state of the difficulty decreasing stage, and the batched result generated by the last execution of step (D) indicates that the response is correct.

In some embodiments, the execution state may also be the first state of the difficulty ramp-up phase、Or a second state of the difficulty ramp-up phase.

When the execution state of the processing unit before the step (G) is the first state of the difficulty rapid-rise stage and the batching result generated by the last execution of the step (D) indicates that the response content is correct, the execution state of the processing unit in the step (G) is maintained.

When the execution state of the processing unit before the step (G) is executed is the first state of the difficulty rapid-rise stage and the batching result generated by the last execution of the step (D) indicates that the response content is incorrect, the execution state of the processing unit is changed to the second state of the difficulty rapid-rise stage in the step (G).

When the execution state of the processing unit before the step (G) is the second state of the difficulty increasing stage and the modification result generated by the last execution of the step (D) indicates that the response is correct, the execution state of the processing unit is changed to the first state of the difficulty increasing stage in the step (G).

When the execution state of the processing unit before the step (G) is the second state of the difficulty rapid-rise stage and the batching result generated by the last execution of the step (D) indicates that the response content is incorrect, the execution state of the processing unit in the step (G) is maintained.

When the processing unit executes the step (a) in the first state of the difficulty rapid-rise stage, the processing unit increases the value of the difficulty index by a first adjustment value, where the first adjustment value is greater than the first default value.

When the processing unit executes the step (a) in the second state of the difficulty rapid-rise stage, the processing unit decreases the value of the difficulty index by a second adjustment value, and the second adjustment value is greater than the second default value.

The invention has the beneficial effects that: the processing unit displays the subjects through the display unit, each subject comprises the at least one dynamic ripple image, and the default attribute of the ripple of the dynamic ripple image is related to the current numerical value of the difficulty index, so that the method is suitable for the general public to detect at any time, is simple to implement and has portability.

Drawings

FIG. 1 is a diagram illustrating a hardware connection relationship of a first embodiment of a visual state detection method according to the present invention;

FIG. 2 is a schematic interface diagram illustrating the contents of a measured distance alert message according to the first embodiment;

FIG. 3 is a flow chart of the first embodiment;

FIG. 4 is a state diagram of the first embodiment;

FIG. 5 is a schematic interface diagram illustrating the contents of a topic in the first embodiment;

FIG. 6 is an image diagram illustrating the relationship between the circular moire and a difficulty index of a dynamic moire image according to the first embodiment;

FIG. 7 is a schematic diagram of an interface of a visual state detection method according to a second embodiment of the present invention, illustrating the contents of the title;

FIG. 8 is a diagram of an image illustrating the relationship between the grid-shaped moire of the dynamic moire image and the difficulty index according to the second embodiment;

FIG. 9 is a schematic view of an interface of a third embodiment of the visual state detection method according to the present invention, illustrating the contents of the title;

FIG. 10 is a schematic diagram of an image of the third embodiment, illustrating the relationship between diamond-shaped moire of the dynamic moire image and the difficulty index;

FIG. 11 is a schematic diagram of an interface of a visual state detection method according to a fourth embodiment of the present invention, illustrating the contents of the title; and

FIG. 12 is a schematic interface diagram of a visual state detection method according to a sixth embodiment of the present invention, illustrating the contents of the title.

Detailed Description

The invention is described in detail below with reference to the following figures and examples:

before the present invention is described in detail, it should be noted that in the following description, like elements are represented by like reference numerals.

Referring to fig. 1, a first embodiment of the visual status detection method of the present invention is implemented by an electronic device 100. The electronic device 100 is operated by a user and includes an input unit 1, a display unit 2, and a processing unit 3 electrically connected to the input unit 1 and the display unit 2. In this embodiment, the electronic device 100 is a smart phone, and the input unit 1 and the display unit 2 of the electronic device 100 are implemented by a touch screen module of the smart phone, but the electronic device 100 is not limited to the smart phone, and the electronic device 100 may be a tablet computer, a laptop computer, a desktop computer, or other specialized detection devices.

The steps of the visual state detection method of the present invention are described below. Referring to fig. 1 and 2, first, as shown in step S00, the processing unit 3 displays a distance measurement prompt message (shown in fig. 3) via the display unit 2. The measurement distance prompt message is used for the user to determine the distance between the user and the display unit 2 of the electronic device 100. The test distance hint message includes a first test word (e.g., ABCDEFG), a second test word (e.g., ABCDEFG) having a font size smaller than the first test word, and a hint word. In this embodiment, the prompt text is "please keep distance during the detection process, the left letter above the screen must be clearly seen, but the right letter cannot be clearly seen".

Next, in step S01, the processing unit 3 determines its own execution status. As shown in FIG. 4, the execution states are a first state 201 of the difficulty raising phase 200, a second state 202 of the difficulty raising phase 200, a first state 301 of the difficulty lowering phase 300, a second state 302 of the difficulty lowering phase 300, a first state 401 of the difficulty rapidly raising phase 400, or a second state 402 of the difficulty rapidly raising phase 400. When the step S01 is executed for the first time, the processing unit 3 determines that the execution status is the first status 401 of the difficulty increasing stage 400, and then when the step S01 is executed again, the manner in which the processing unit 3 determines the execution status is related to the response of the user, which will be described in detail later.

Next, in step S02, the processing unit 3 determines a current value of the difficulty index (k). When the processing unit 3 determines that the current value of the difficulty index is a preset initial value (for example, k is 3) when the step S02 is executed for the first time, and then when the step S02 is executed again, the manner in which the processing unit 3 determines the current value of the difficulty index is related to the current execution state of the processing unit 3. As shown in fig. 4, when the processing unit 3 executes step S02 in the first state 401 of the difficulty rapid-rise phase 400, the processing unit 3 increases the value of the difficulty index by a first adjustment value (k-k + 4); when the processing unit 3 executes step S02 in the second state 402 of the difficulty rapid-rise phase 400, the processing unit 3 decreases the value of the difficulty index by a second adjustment value (k-3); when the processing unit 3 executes step S02 in the first state 201 of the difficulty increasing stage 200, the processing unit 3 increases the value of the difficulty index by a first default value (k ═ k +1), where the first default value is smaller than the first adjustment value; when the processing unit 3 executes step S02 in the second state 202 of the difficulty increasing stage 200, the processing unit 3 keeps the value of the difficulty index unchanged (k-k + 0); when the processing unit 3 executes step S02 in the first state 301 of the difficulty level decreasing stage 300, the processing unit 3 decreases the value of the difficulty index by a second default value (k-1), which is smaller than the second adjustment value; when the processing unit 3 executes step S02 in the second state 302 of the difficulty level decreasing phase 300, the processing unit 3 keeps the value of the difficulty index unchanged (k-0).

Next, in step S03, the processing unit 3 displays a question including an answer prompt and at least one dynamic moire image through the display unit 2, and a default attribute of the moire of the dynamic moire image is related to the current value of the difficulty index. As shown in fig. 5, in the present embodiment, each topic includes one number of the dynamic moire images, and the answering prompt prompts the user to answer the wave center position of the dynamic moire image.

Furthermore, in this embodiment, the default attribute is a wavelength, and the wavelength of the moire of the dynamic moire image of each topic is inversely related to the difficulty index. As shown in fig. 6, when the numerical value of the difficulty index is larger, the wavelength of the moire of the dynamic moire image is smaller. Specifically, the processing unit 3 may be the dynamic moire image for generating circular moire using the following formula (1), wherein the size of the dynamic moire image is N × N pixels, T sampling points are equally scaled over a complete period of one wave, B is an average luminance (0 ≦ B ≦ 255), A is a maximum amplitude (0 ≦ A ≦ min (B,255-B)), and k is the difficulty index, (i, j) e {0,1, …, N-1}²For each pixel of the dynamic moire image, (p, q) belongs to {0,1, …, N-1}²For the wave center position, T ∈ {0,1, …, T-1} is each sampling time point in a single cycle.

In other embodiments, the dynamic moire image may also be a pre-stored GIF image file or movie file. In addition, in other embodiments, the default attribute is, for example, amplitude or frequency, for example, the amplitude of the ripple of the dynamic ripple image of each topic is negatively correlated with the difficulty index (the larger the value of the difficulty index is, the smaller the amplitude of the ripple of the dynamic ripple image is), or the frequency of the ripple of the dynamic ripple image of each topic is positively correlated with the difficulty index (the larger the value of the difficulty index is, the larger the frequency of the ripple of the dynamic ripple image is).

Next, as shown in step S04, the processing unit 3 receives a content corresponding to the topic input by the user via the input unit 1. In this embodiment, the answering content is that the wave center is located at the upper left, the wave center is located at the lower left, the wave center is located at the upper right, the wave center is located at the lower right, or uncertain.

Next, as shown in step S05, the processing unit 3 generates a batch modification result according to the answering content of step S04. The correction result indicates that the response content of step S04 is correct or incorrect, wherein incorrect represents a wave center position error or selection "uncertain" selected by the user.

Next, as shown in step S06, the processing unit 3 determines whether an end condition is met according to the falsification result of step S05, and if not, performs step S01 to step S06 again, and if so, performs step S07.

The manner in which the processing unit 3 determines the execution state when the processing unit 3 executes step S01 again will be described below with reference to fig. 4, where "P" in fig. 4 represents that the wholesale result indicates that the answering content is correct, and "F" in fig. 4 represents that the wholesale result indicates that the answering content is incorrect (wrong or "uncertain" selection). When the execution state of the processing unit 3 before the step S01 is the first state 401 of the difficulty rapidly increasing stage 400 and the batch change result generated by the last execution of the step S05 indicates that the response is correct, the execution state of the processing unit 3 is maintained at the step S01.

When the execution state of the processing unit 3 before the step S01 is the first state 401 of the difficulty rapid-rise phase 400 and the batch change result generated by the last execution of the step S05 indicates that the response content is incorrect, the execution state of the processing unit 3 is changed to the second state 402 of the difficulty rapid-rise phase 400 in step S01.

When the execution state of the processing unit 3 before the step S01 is the second state 402 of the difficulty increasing stage 400 and the batch change result generated by the last execution of the step S05 indicates that the response is correct, the execution state of the processing unit 3 is changed to the first state 201 of the difficulty increasing stage 200 in step S01.

When the execution state of the processing unit 3 before the step S01 is the second state 402 of the difficulty rapidly increasing stage 400 and the batch change result generated by the last execution of the step S05 indicates that the response content is incorrect, the execution state of the processing unit 3 is maintained at the step S01.

When the execution state of the processing unit 3 before the step S01 is the first state 201 of the difficulty increasing stage 200 and the batch result generated by the last execution of the step S05 indicates that the response is correct, the execution state of the processing unit 3 is maintained at the step S01.

When the execution state of the processing unit 3 before the execution of step S01 is the first state 201 of the difficulty increasing phase 200 and the batch result generated by the last execution of step S05 indicates that the answer content is incorrect, then the execution state of the processing unit 3 is changed to the second state 202 of the difficulty increasing phase 200 in step S01.

When the execution state of the processing unit 3 before the execution of step S01 is the second state 202 of the difficulty increasing phase 200 and the batch result generated by the last execution of step S05 indicates that the response is correct, the execution state of the processing unit 3 is changed to the first state 201 of the difficulty increasing phase 200 in step S01.

When the execution state of the processing unit 3 before the execution of step S01 is the second state 202 of the difficulty increasing phase 200 and the batch result from the last execution of step S05 indicates that the answer content is incorrect, then the execution state of the processing unit 3 is changed to the first state 301 of the difficulty decreasing phase 300 in step S01.

When the execution state of the processing unit 3 before the step S01 is the first state 301 of the difficulty decreasing stage 300 and the batch result generated by the last execution of the step S05 indicates that the response content is incorrect, the execution state of the processing unit 3 is maintained at the step S01.

When the execution state of the processing unit 3 before the execution of step S01 is the first state 301 of the difficulty level decreasing phase 300 and the batch change result generated by the last execution of step S05 indicates that the response is correct, the execution state of the processing unit 3 is changed to the second state 302 of the difficulty level decreasing phase 300 in step S01.

When the execution state of the processing unit 3 before the execution of step S01 is the second state 302 of the difficulty level decreasing phase 300 and the batch result generated by the last execution of step S05 indicates that the answer content is incorrect, then the execution state of the processing unit 3 is changed to the first state 301 of the difficulty level decreasing phase 300 in step S01.

Furthermore, in step S06, the end condition is that the current execution state of the processing unit 3 is the second state 302 of the difficulty decreasing stage 300, and the batched result generated by the last execution of step S05 indicates that the response is correct.

Finally, as shown in step S07, the processing unit 3 generates a detection result and displays the detection result via the display unit 2, wherein the detection result is related to the current value of the difficulty index.

Referring to fig. 7 and 8, a second embodiment of the visual status detecting method of the present invention is similar to the first embodiment, and the differences are described as follows. In this embodiment, the answer prompt prompts the user to answer a moving direction (e.g., upper left, lower left, upper right, or lower right) of the moire of the dynamic moire image, and the moire of the dynamic moire image is in a grid shape.

As shown in fig. 8, when the numerical value of the difficulty index is larger, the wavelength of the moire of the dynamic moire image is smaller. Specifically, the processing unit 3 may be the dynamic moire image for generating a grid-like moire by using the following formula (2), wherein the size of the dynamic moire image is N × N pixels, and is equal to each other in a complete period of one waveCutting T sampling points in proportion, wherein B is average brightness (0 & ltB & gt & lt 255 & gt), A is maximum amplitude (0 & ltA & lt min (B,255-B)), k is the difficulty index, (i, j) belongs to {0,1, …, N-1}²For each pixel point of the dynamic moire image, (p, q) ∈ { -1,0,1}²For the direction of motion, T ∈ {0,1, …, T-1} is each sampling time point in a single cycle.

Referring to fig. 9 and 10, a third embodiment of the visual status detecting method of the present invention is similar to the first embodiment, and the differences are described as follows. In this embodiment, each topic includes two or more of the motion blur images (e.g., three motion blur images), and each topic further includes a contrast image, and the content of the contrast image is different from the content of the motion blur image. In this embodiment, the content of the contrast image has no ripples, and the shape of the ripples of the dynamic ripple image is a diamond shape. The answering prompt prompts the user to select the contrast image.

As shown in fig. 10, the larger the difficulty index value is, the smaller the wavelength of the moire of the dynamic moire image is. Specifically, the processing unit 3 may be the dynamic moire image generating diamond-shaped moire using the following formula (3), wherein the size of the dynamic moire image is N × N pixels, T sampling points are equally scaled over a complete period of one wave, B is an average luminance (0 ≦ B ≦ 255), A is a maximum amplitude (0 ≦ A ≦ min (B,255-B)), and k is the difficulty index, (i, j) e {0,1, …, N-1}²For each pixel point of the dynamic moire image, (p, q) ∈ { -1,0,1}²For the direction of motion, T ∈ {0,1, …, T-1} is each sampling time point in a single cycle.

In the title shown in fig. 9, the images at the left one, the right one and the right two are the dynamic moire images, and the image at the left two is the contrast image. The difficulty index associated with the dynamic moire image is adjusted from the preset initial value.

In another embodiment, the content of the contrast image has ripples, and the default property of the ripples of the contrast image is related to a value of a contrast difficulty index, and the value of the contrast difficulty index is different from the current value of the difficulty index (the value of the contrast difficulty index may be set to a relatively large value, such as 80, for example), so that the default property of the ripples of the contrast image is different from the default property of the ripples of the dynamic ripples image, such as the moving direction of the ripples, the wave center position, the amplitude of the ripples, the wavelength of the ripples, the frequency of the ripples, the moving speed of the ripples, and the like. Taking the wavelength of the ripple as an example, the processing unit 3 also generates the comparison image of the diamond-shaped ripple by using formula (3), except that the difficulty index in formula (3) is replaced by the comparison difficulty index.

Referring to fig. 11, a fourth embodiment of the visual status detecting method of the present invention is similar to the third embodiment, and the differences are described as follows. In this embodiment, each question includes one number of the motion blur images, and each question further includes a plurality of contrast images, and the answer prompt prompts the user to select the motion blur image.

In the title shown in fig. 11, the images at the left one, the right one and the right two are the contrast images, and the image at the left two is the dynamic moire image. The difficulty index associated with the dynamic moire image is adjusted from the preset initial value.

In the fourth embodiment, the content of the contrast image has no ripples, and the shape of the ripples of the dynamic ripple image is a diamond shape.

A fifth embodiment of the method for detecting a visual state of the present invention is similar to the fourth embodiment, and the difference is that the contents of the comparison images have ripples, the default attribute of the ripples of each comparison image is related to the value of the comparison difficulty index, and the value of the comparison difficulty index is different from the current value of the difficulty index (the value of the comparison difficulty index may be, for example, a value larger than the difficulty index, or may be set to a relatively large value, for example, 80), so that the default attribute of the ripples of the comparison images is different from the default attribute of the ripples of the dynamic ripple images.

Referring to fig. 12, a sixth embodiment of the visual state detection method according to the present invention is similar to the fourth embodiment, and the difference is that the contents of the comparison images have ripples, the default attribute of the ripple of each comparison image is related to the value of the comparison difficulty index, and the value of the comparison difficulty index is the same as the current value of the difficulty index, such that the default attribute of the ripple of the comparison image is the same as the default attribute of the ripple of the dynamic ripple image. Furthermore, a target attribute of the moire of the contrast image, which is different from the default attribute, is different from the target attribute of the dynamic moire image, so that the content of the contrast image is different from the content of the dynamic moire image. Taking fig. 12 as an example, the target attribute is a wave center position.

In summary, the visual status detection method of the present invention displays the questions through the display unit 2 by the processing unit 3, and each question includes the at least one dynamic moire image, and the attribute of the moire of the dynamic moire image is related to the current value of the difficulty index, so as to be suitable for the general public to self-detect at any time, and the method is simple to implement and portable, thereby achieving the purpose of the present invention.

The above description is only for the preferred embodiment of the present invention, and it is not intended to limit the scope of the present invention, and any person skilled in the art can make further modifications and variations without departing from the spirit and scope of the present invention, therefore, the scope of the present invention should be determined by the claims of the present application.