Visual acuity test data processing method and system, and visual acuity test system

Abstract

The present application discloses a visual acuity test data processing method. The method comprises: displaying, on a display interface, an optotype back and forth at a set rate in a horizontal direction, said optotype corresponding to a visual acuity level, so as to induce eye following of a subject by moving the optotype; in said process, collecting an eye movement image sequence of the subject; a detection controller parsing the eye movement image sequence to obtain eye movement position data, constructing an eye movement curve by using time as a horizontal axis and single-dimensional data of the eye movement position data as a vertical axis, and determining whether the eye movement curve continuously increases or continuously decreases, and whether the rate of continuous increase or decrease falls within a human eye movement speed range; if the conditions are met, it indicates that the eyes of the subject can follow the optotype, and the visual acuity of the subject reaches a visual acuity level corresponding to the optotype; and if the visual acuity of the subject does not reach the visual acuity level corresponding to the optotype, the eyes do not have an ability of effectively following the optotype, and the conditions are not met at the same time. Further disclosed are a visual acuity test data processing system and a visual acuity test system.

Description

A vision detection data processing method and system and a vision detection system TECHNICAL FIELD

[0001] The present application belongs to the technical field of vision detection, and particularly relates to a vision detection data processing method and system and a vision detection system. BACKGROUND

[0002] Currently, there are four methods for testing the vision of infants under 36 months of age: the first method is to test by using a standard logarithmic visual acuity chart; the second method is to test by using optical instruments; the third method is to test by using induced optokinetic nystagmus; and the fourth method is to test by using a traditional preferential looking (PL) card. TECHNICAL PROBLEM

[0003] For the first method, the tester is required to honestly and accurately inform whether the pattern in the chart can be seen, and if the tester cheats or is too young to answer, the test cannot be performed, and therefore the method is not suitable for infants under 24 months of age. At the same time, the method has strict requirements for the light in the test room, and the test precision is poor, and the size of the adjacent two levels of visual targets differs by 0.1 in logarithmic scale, such as the Snellen visual acuity chart and the ETDRS visual acuity chart.

[0004] For the second method, the human eye is simply used as an optical element for testing, and the vision of a person is the result of inputting an image into the brain through the optical element of the human eye and processing it through the nervous system and then feeding it back. Therefore, this method only tests the optical element of the human eye and does not consider the influence of the visual neural pathway. Therefore, it cannot be used as an evaluation of the visual acuity (VA).

[0005] For the third method, induced optokinetic nystagmus is used to objectively measure the vision level through the instinctive response of the tester. This method is suitable for children over 6 months of age, and multiple sets of visual targets are required to confirm the vision level of the tester. This method requires analysis of the eye movement trajectory of the tester to obtain optokinetic nystagmus data, and therefore requires a high analysis algorithm to obtain accurate optokinetic nystagmus data.

[0006] For the fourth method, the doctor is required to hold a card with different visual targets and observe whether the infant looks at the card with the corresponding visual target for more than 75% of the time within 30 seconds. Although this method is suitable for children under 18 months of age, the actual operation has high requirements for the environment and light, and the single test takes a long time, and therefore has not been widely used. TECHNICAL SCHEME

[0007] The application aims to provide a vision detection data processing method, system and vision detection system, which is based on the existing PL vision detection theory, uses a display device to display an optotype corresponding to a vision level, and moves the optotype back and forth in a set range to induce the testee to follow the movement of the optotype with the eyes, and then collects a series of eye movement images of the testee watching the optotype, analyzes the series of eye movement images, and judges whether the testee's eyes successfully follow the optotype, compared with the existing PL vision detection method, the application can truly reflect the vision level of the testee by testing the visual feedback signal of the testee after the brain and nervous system processing, and has low testing difficulty.

[0008] To solve the above technical problems, the application adopts the following technical solutions to achieve the application:

[0009] The application provides a vision detection data processing method, which comprises the following steps:

[0010] S1. Displaying an optotype back and forth horizontally on a display device at a set speed, and collecting a series of eye movement images of the testee; the optotype corresponds to a vision level; the series of eye movement images are obtained by collecting the testee's eyes watching the optotype;

[0011] S2. Analyzing the series of eye movement images to obtain eye movement position data;

[0012] S3. Constructing an eye movement curve with the time or frame sequence of the eye movement images as the horizontal axis and the horizontal data of the eye movement position data as the vertical axis;

[0013] S4. Judging whether the eye movement curve continuously increases or decreases and the continuously increasing or decreasing speed is within a preset interval; the preset interval is the human eye movement speed interval; if yes, turn to step S5; if not, turn to step S6;

[0014] S5. Determining that the testee's eyes successfully follow the displayed optotype;

[0015] S6. Determining that the testee's eyes fail to successfully follow the displayed optotype.

[0016] In some embodiments of the application, in step S4, when the eye movement curve continuously increases or decreases and the continuously increasing or decreasing speed is within the preset interval, the method further comprises:

[0017] Calculating the minimum displacement distance of the eye movement;

[0018] When the eye movement position data all reach the minimum displacement distance, turn to step S5; otherwise, turn to step S6.

[0019] In some embodiments of the application, step S2 specifically comprises:

[0020] S21, identifying a blink frame from the eye movement image sequence;

[0021] S22, replacing the eye movement position of the blink frame with the eye movement position of the frame before the blink frame.

[0022] In some embodiments of the present application, step S2 specifically comprises:

[0023] S23, identifying an eye movement loss frame from the eye movement image sequence;

[0024] S24, identifying the position of the eye movement loss frame;

[0025] S25, compensating the eye movement position data of the eye movement loss frame according to the effective eye movement position data of the frames before and after the identified position.

[0026] In some embodiments of the present application, step S2 specifically comprises:

[0027] S26: bilateral filtering the eye movement position data.

[0028] In some embodiments of the present application, in step S23, if the identified eye movement loss frame is located at the beginning or the end of the eye movement image sequence, the eye movement loss frame is discarded.

[0029] A processing system for vision detection data is provided, comprising a display device and an eye movement image acquisition device; wherein,

[0030] The display device is configured to display an optotype on its display interface.

[0031] The eye movement image acquisition device is configured to acquire an eye movement image sequence of the eye of the testee following the optotype; and further comprises:

[0032] A detection controller is configured to control the display device to display the optotype on its display interface in a set speed and to return horizontally; the optotype corresponds to a vision level; when displaying the optotype corresponding to a vision level each time, the processing method for vision detection data as described above is executed to determine whether the testee's eye has realized a successful optotype following each time.

[0033] A vision detection system is provided, comprising:

[0034] The processing system for vision detection data as described above;

[0035] A vision judgment controller is configured to determine the vision of the testee based on the judgment result of the detection controller, comprising:

[0036] When it is determined that a successful optotype following is realized, the optotype displayed on the display interface of the display device is updated, and the updated optotype is improved by one vision level compared with the original optotype.

[0037] If the detection controller judges that the successful target following is achieved, the target of the next display is updated to the target of the next vision level until the detection controller judges that the successful target following is not achieved, and the vision level corresponding to the target displayed when the successful target following is achieved is determined as the vision of the tested person.

[0038] In some embodiments of the present application, the vision judgment controller determines the vision of the tested person according to the judgment result, comprising:

[0039] When the successful target following is not achieved, the target displayed on the display interface of the display device is updated, and the updated target is the target of the next vision level;

[0040] If the detection controller judges that the successful target following is achieved, the target of the next display is updated to the target of the next vision level until the detection controller judges that the successful target following is achieved, and the vision level corresponding to the target displayed when the successful target following is achieved is determined as the vision of the tested person. Advantages

[0041] Compared with the prior art, the advantages and positive effects of the application are that in the vision detection data processing method, system and vision detection system, a series of optotypes are designed, each optotype corresponds to a vision level, and when each vision level is tested, the display optotype moves back and forth on the display interface at a set speed in the transverse direction, and the to-and-fro moving optotype is used to induce the testee to follow the left and right repeated movement thereof; during the to-and-fro movement of the optotype, the eye movement image sequence of the testee watching the optotype is collected by an eye movement image collection device, and a detection controller parses a series of eye movement position data from the eye movement image sequence, constructs an eye movement curve with time or a frame sequence of the eye movement image as the horizontal axis and the horizontal data of the eye movement position data as the vertical axis, judges whether the eye movement curve continuously increases or continuously decreases, and the speed of the continuously increasing or continuously decreasing is within the speed interval of human eye movement, when the vision of the testee can reach the vision level corresponding to the currently displayed optotype, the eye of the testee can effectively follow the to-and-fro movement of the optotype, and the eye movement curve meets the characteristics of continuously increasing or continuously decreasing and the speed of continuously increasing or continuously decreasing being within the speed interval of human eye movement, that is, the optotype following can be realized, if the vision of the testee cannot reach the vision level corresponding to the currently displayed optotype, the eye of the testee does not have the ability to effectively follow the optotype, and the analyzed eye movement curve cannot simultaneously meet the conditions of having an inflection point, the position data before and after the inflection point continuously increasing or continuously decreasing, and the speed of continuously increasing or continuously decreasing being within the speed interval of human eye movement; based on the above processing and analysis of the vision detection data, whether the eye of the testee successfully follows the displayed optotype in the test of one vision level can be judged, if the optotype is successfully followed, it indicates that the vision of the testee can reach the vision level of the currently displayed optotype, and if the optotype cannot be successfully followed, the vision of the testee cannot reach the vision level of the currently displayed optotype.

[0042] The application can judge the vision level of the testee by displaying optotypes of different vision levels, without the testee holding the optotype, without the testee guiding the testee to watch the optotype, and without the testee feeding back whether the optotype is clearly seen, compared with the existing PL vision detection method, the application can truly reflect the vision level of the testee by inducing the eye movement of the testee to follow the optotype and testing the visual feedback signal of the testee after the brain and nervous system processing, and the test difficulty is low. BRIEF DESCRIPTION OF DRAWINGS

[0043] Fig. 1 is a structural schematic view of an optotype in the vision detection system according to the application;

[0044] Fig. 2 is a schematic view of the movement of the optotype in the vision detection system according to the application;

[0045] Fig. 3 is a schematic view of the movement of the optotype in the vision detection system according to the application;

[0046] Figure 4 is a schematic diagram of the steps of the visual acuity detection system of the present application;

[0047] Figure 5 is a schematic diagram of the steps of the visual acuity detection data processing method of the present application;

[0048] Figure 6 is a schematic diagram of the eye movement curve obtained in the visual acuity detection data processing of the present application;

[0049] Figure 7 is a schematic diagram of the eye movement curve obtained in the visual acuity detection data processing of the present application;

[0050] Figure 8 is a schematic diagram of the architecture of the visual acuity detection system of the present application. Best Mode for Carrying Out the Invention

[0051] The specific embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0052] The visual acuity detection data processing method of the present application is applied to the visual acuity detection system and solves the following problems of the existing visual acuity detection methods:

[0053] 1. The tested person must give a response, and if the tested person cannot give a response, the test result cannot be obtained.

[0054] The visual acuity detection data processing method of the present application can determine whether the eye of the tested person successfully follows the moving optotypes, thereby determining the example level, without requiring the tested person to give any feedback, and the system can analyze the visual acuity level according to the physiological response of the tested person.

[0055] 2. The external environment for the test, such as light, the gaze of the tested person, etc., has relatively strict requirements.

[0056] In the test of the present application, two methods can be used to show the optotypes corresponding to the visual acuity level to the tested person: the first method is through virtual helmet reality, i.e., using virtual reality technology to immerse the tested person, without requirements for the external environment; the second method is through the display of a computer, a television, a mobile phone or a tablet, etc., without strict requirements for the external environment.

[0057] 3. The test result is highly dependent on the accuracy of the response of the tested person, and if the tested person gives a false or ambiguous response, the test result is inaccurate.

[0058] The test of the present application determines the visual acuity value of the tested person through the detection of the instinctive physiological response of the tested person, which cannot be controlled by the tested person and cannot be cheated.

[0059] 4. The human eye is simply used as an optical element for testing, and the complete visual process processed by the brain and the nervous system cannot be tested.

[0060] The application tests the visual feedback signal of the tested person after the brain and nervous system processing, and can truly reflect the visual level.

[0061] 5. The visual acuity chart test has low precision, and the size difference (log value) between the sizes of the adjacent two levels of the visual target is 0.1.

[0062] The application can further subdivide the sizes of the two levels in the visual acuity chart by moving the visual target to induce eye following, and combine the test data processing method, so as to achieve higher test precision.

[0063] 6. The traditional PL method provides physical cards, and the switching time of the cards is long.

[0064] In the visual acuity detection system, a series of visual target sequences corresponding to different visual levels are designed, each level of visual target is displayed by moving left and right in a certain time and range, and the tested person does not need to make subjective feedback, so that the rapid switching and testing can be realized.

[0065] In the embodiment of the application, as shown in FIG. 8, the display device 62 (such as the display of an electronic device such as a computer, a television, a mobile phone, a tablet computer, virtual reality or augmented reality, or a virtual reality helmet) is controlled by the detection controller 64 to display a series of visual targets corresponding to the visual levels to the tested person on the display interface, and the eye movement image acquisition device 63 is used to acquire the eye movement image sequence of the tested person watching the visual targets, the physiological response (eye fixation, following, saccade, tremor, etc.) of the eye of the tested person is analyzed by the detection controller 64 through the processing means of the eye movement image sequence, and then the visual judgment controller 61 compares with the stored high-precision visual value standard list to finally determine the visual value.

[0066] Specifically, as shown in FIG. 4, the following steps are included:

[0067] S101: Generate a series of visual targets, each visual target corresponds to a visual level.

[0068] In the embodiment of the present application, the target is various patterns filled with horizontal, vertical or horizontal and vertical superimposed black and white grids. A series of target images can be generated by the target generation module 60 based on the pattern of interest of the testee, the target image is outlined with the pattern of interest of the testee, and the inside is filled with horizontal, vertical and horizontal and vertical superimposed black and white grids. The targets of each visual acuity level are distinguished by the width of the black and white grids, as shown in FIG. 1. The target moves back and forth on the display interface at a set rate from left to right and then from right to left, as shown in FIGS. 2 and 3. The set rate meets the requirement that the testee's eyes can follow the target when the testee's visual acuity reaches the visual acuity level corresponding to the target. For the infant group, in order to attract their eyes to actively follow the movement of the target, different types of patterns (such as the characters of the animation of interest, animals or photos of mothers, etc.) can be combined to generate the target, and sound can be used to attract the infants to follow the target.

[0069] S102: Control the display device to display the target corresponding to the visual acuity level on the display interface thereof.

[0070] The detection controller 64 controls the computer, television, mobile phone, IPAD and other electronic devices to display a target image moving back and forth (left and right or up and down) at a uniform speed s1 to the testee through the display or virtual reality helmet thereof.

[0071] At the same time, in the initial stage of switching a target, the attention of the testee can be attracted by flashing the target, and then moving back and forth at a uniform speed s1, accompanied by audio to attract the testee to watch the screen. If the testee's visual acuity reaches the visual acuity level corresponding to the target image, the eyes can effectively follow the target. If the testee's visual acuity cannot reach the visual acuity level corresponding to the target image, the testee cannot effectively follow the target.

[0072] S103: Collect the eye movement image sequence of the testee and send it to the detection controller.

[0073] The eye movement image acquisition device 63 acquires the eye movement image sequence of the testee watching the target during the display of the target, that is, the eye movement image sequence is acquired in time sequence.

[0074] S104: Call the visual acuity detection data processing method to analyze the eye movement image sequence of the testee, and judge whether the testee's eyes can successfully follow the movement of the target. If yes, go to S105; if not, go to S107.

[0075] The algorithm is called by the detection controller 64.

[0076] Specifically, as shown in FIG. 5, the visual acuity detection data processing method provided by the present application comprises:

[0077] S1: acquiring eye movement image sequence of the testee during the display of the test target on the display device at a set speed.

[0078] That is, a series of image frames of the test target viewed by the testee's eyes. If the testee's vision level reaches the vision level corresponding to the test target, the test target can be effectively followed, and if the testee's vision level cannot reach the vision level corresponding to the test target, the test target cannot be effectively followed.

[0079] S2: analyzing the eye movement image sequence to obtain eye movement position data.

[0080] Based on the eye movement image sequence, the eye movement trajectory of the testee is recorded in real time, and is saved in the form of two-dimensional or three-dimensional coordinates. In the embodiment of the present application, in order to simplify the calculation amount and complexity, the eye movement position coordinate relationship is established with time as the horizontal axis and the single-dimensional coordinate data of the eye movement as the vertical axis. For a series of continuous eye movement image sequences, the eye movement position data is simplified to, for example, [100, 101, 102, 103, …, 100]. Here, the single-dimensional refers to the horizontal data or the vertical data. When the test target moves back and forth in the horizontal direction, the single-dimensional data refers to the horizontal data of the eye movement position data. When the test target moves back and forth in the vertical direction, the single-dimensional data refers to the vertical data of the eye movement position data.

[0081] In the embodiment of the present application, first, the blink frame and the eye movement loss frame are identified from the eye movement image sequence. For the blink frame, the eye movement position of the previous frame of the blink frame is used to replace the eye movement position of the blink frame. For the eye movement loss frame, the position of the eye movement loss frame is identified. If the eye movement loss frame is in the middle of the image sequence, the eye movement position of the loss frame is compensated according to the effective eye movement positions of the frames before and after the identified position. If the loss frame is at the head or tail of the image sequence, it is directly discarded.

[0082] In identifying the blink frame, whether the blink occurs is judged according to the iris area in the acquired eye movement data. When the iris area is smaller than the normal area, it can be set as a blink, and the normal area can be obtained by photographing in the normal open-eye state during the initial detection of the testee and stored as a reference. When the blink is identified, whether the blink affects the extraction of the effective eye movement position is judged according to the length and width of the iris. When the length of the iris is greater than 2 times the width, it is considered that the blink frame cannot extract the effective eye movement position data, and the eye movement position of the previous frame of the blink frame is used to replace the eye movement position of the blink frame.

[0083] In identifying the missing frame, if any coordinate information or iris position, area information cannot be obtained from the current image frame, it is considered as eye movement position loss; for the missing frame, its data is marked as -1, for example [100, 101, -1, 103, …, 100], and the effective eye movement positions before and after the marked position are used for compensation, for example: [100, 101, -1, -1, -1, -1-1, 107....], a total of 5 frames of eye movement position data are lost in this data, so according to the difference between the front and rear positions 107-101=6, it is evenly distributed in the 5 frames, and the new data queue is as follows: [100, 101, 102, 103, 104, 105, 106, 107....], thereby constructing a continuous eye movement position curve.

[0084] If the beginning or end part of the obtained data has a missing eye phenomenon, the data of the missing eye part is directly discarded at this time. For example: [-1, -1, -1, -1, -1, 100, 102, 100, 102...] and [100, 102, 100, 102, -1, -1, -1, -1, -1...], in the two data, there are missing eye data at the beginning and the end respectively, the data of the missing eye movement position is directly discarded, and only the remaining data can be retained.

[0085] The eye movement data processed by the above two steps is subjected to bilateral filtering. The core idea of bilateral filtering is that when smoothing, not only the spatial distance (i.e. positional relationship) of the pixels in the neighborhood is considered, but also the similarity of the pixel values. This method is particularly effective in preserving edge information, because it can distinguish between noise and edges, and only smooths the noise part, while the edges and other important details are kept as much as possible.

[0086] Specifically, the bilateral filter is composed of two Gaussian functions: one is a spatial distance-based Gaussian function, which is responsible for calculating the spatial proximity between pixels; the other is a pixel value difference-based Gaussian function, which is responsible for calculating the similarity of pixel values. The edge preservation property of bilateral filtering is mainly realized by combining the spatial domain function and the value domain kernel function in the convolution process. A typical kernel function is a Gaussian distribution function, as shown below: ; is the standard deviation of the spatial domain Gaussian function, is the standard deviation of the value domain Gaussian function, and Ω represents the definition domain of convolution. It can be seen that in the flat area of the image, the value changes very little, and the value domain weight is close to 1, at this time the spatial domain weight plays a major role, which is equivalent to directly Gaussian blurring this area, and in the edge area, there will be a large difference, at this time the value domain coefficient will decrease, resulting in the decrease of the distribution of the whole kernel function at this place, and the edge detail information is maintained.

[0087] After the above processing, the inflection point position of the eye movement position data, i.e. the position at which the eye ball switches following the target (switching from left to right or from bottom to top), is obtained using a standard deviation algorithm, and is the maximum or minimum value in the array, denoted as the inflection point position.

[0088] S3: constructing an eye movement curve with time or a frame sequence of eye movement images as the horizontal axis and the single-dimensional data of the eye movement position data as the vertical axis.

[0089] As shown in the examples of FIGS. 6 and 7, the eye movement curve constructed with time as the horizontal axis and the single-dimensional data of the eye movement position data as the vertical axis (in the case of successful target following), FIG. 6 corresponds to the eye movement curve when the eye ball follows the target moving from left to right or from bottom to top, and FIG. 7 corresponds to the eye movement curve when the eye ball follows the target moving from right to left or from top to bottom. When establishing the coordinate system, the eye ball moving from left to right or from bottom to top corresponds to the single-dimensional data gradually increasing, and the eye movement curve shown in FIG. 6 is constructed, and the eye ball moving from right to left or from top to bottom corresponds to the single-dimensional data gradually decreasing, and the eye movement curve shown in FIG. 7 is constructed. FIGS. 6 and 7 show the eye movement curve constructed from the data between the two inflection points.

[0090] S4: determining whether the eye movement curve continuously increases or decreases and the speed of continuously increasing or decreasing is within a preset interval.

[0091] Using a sliding window mode, the data before and after each inflection point position is continuously analyzed to determine whether it continuously increases or decreases and the speed satisfies the speed interval of human eye movement (i.e. the preset interval), and if so, further lowest displacement distance calculation is performed to determine whether the eye movement position data all reaches the lowest displacement distance, and if so, step S5 is entered, otherwise step S6 is entered.

[0092] The lowest displacement distance is used to limit the effective movement of the eye ball, and below the lowest displacement distance represents that the eye ball does not move, which is micro movement not following the target movement. In the embodiments of the present application, the difference between the eye movement positions of two frames of eye movement images is calculated to compare with the lowest displacement distance, and when the difference between the eye movement positions is greater than the lowest displacement distance, it represents that the eye ball produces effective movement, otherwise it is invalid micro movement.

[0093] In some embodiments of the present application, the local slope of the eye movement curve can also be used to determine whether the eye movement position data reaches the lowest displacement distance, and the local slope reflects the position change of two frames of eye movement images, and the greater the slope, the greater the position difference, and the smaller the slope, the smaller the position difference.

[0094] S5: determining that the eye of the tested person successfully follows the displayed target.

[0095] It indicates that the tested person can effectively follow the currently displayed optotypes, i.e. the tested person's vision can reach the vision level corresponding to the current optotypes.

[0096] S6: Determine that the tested person's eye fails to successfully follow the displayed optotypes.

[0097] It indicates that the tested person cannot effectively follow the currently displayed optotypes, i.e. the tested person's vision cannot reach the vision level corresponding to the current optotypes.

[0098] S105: Determine whether the current optotypes are the highest vision level.

[0099] If the current optotypes are the highest vision level, jump to S110 to determine that the tested person's vision is not less than the highest level of vision level that can be measured by the current device; if the current optotypes are not the highest level, jump to S106.

[0100] S106: Display optotypes of a higher level, return to step S102.

[0101] The screen is switched to a higher level of optotype image moving uniformly in the longitudinal direction at a rate s2, and at the same time, audio can be accompanied to attract the tested person to watch the screen. And jump to S102 to perform eye tracking and trajectory analysis again.

[0102] S107: Determine whether the current optotypes are the lowest vision level.

[0103] If the current optotypes are the lowest level of optotypes, jump to S111 to determine that the tested person cannot pass the lowest level of optotype detection; if the current optotypes are not the lowest level, jump to S108.

[0104] S108: Determine whether the lower level of optotypes has passed the test.

[0105] If it passes, jump to S112 to determine that the tested person's vision is one level lower than the vision level corresponding to the current optotypes; if it fails, jump to S109.

[0106] S109: Display optotypes of a lower level, return to step S102.

[0107] The screen is switched to a lower level of optotype image moving uniformly in the longitudinal direction at a speed s0, and at the same time, audio can be accompanied to attract the tested person to watch the screen. And jump to S102 to perform eye tracking and trajectory analysis again.

[0108] Finally, according to the test conclusions of S110, S111 and S112, the tested person's vision value is output.

[0109] It should be pointed out that the above description is not a limitation of the present application, and the present application is not limited to the above examples. Changes, modifications, additions or substitutions made by those skilled in the art within the spirit and scope of the present application should also be within the protection scope of the present application.

Claims

1. A method of processing vision test data, characterized by, The method comprises: S1, displaying a target on a display device back and forth at a set speed and collecting a sequence of eye movement images of a testee; The target corresponds to a visual acuity level; the sequence of eye movement images is obtained by the testee watching the target; S2, analyzing the sequence of eye movement images to obtain eye movement position data; S3, constructing an eye movement curve with a time or a sequence of frames of eye movement images as a horizontal axis and one-dimensional data of the eye movement position data as a vertical axis; the one-dimensional data is longitudinal data or transverse data; S4, judging whether the eye movement curve continuously increases or continuously decreases and the continuously increasing or continuously decreasing speed is within a preset interval; the preset interval is a human eye movement speed interval; if yes, proceeding to step S5; if not, proceeding to step S6; S5, determining that the testee successfully follows the displayed target; S6, determining that the testee fails to successfully follow the displayed target.

2. The method of processing vision test data according to claim 1, wherein, In step S4, when the eye movement curve continuously increases or decreases and the continuously increasing or continuously decreasing speed is within the preset interval, the method further comprises: calculating a minimum displacement distance of eye movement; proceeding to step S5 when the eye movement position data all reaches the minimum displacement distance of eye movement; otherwise, proceeding to step S6.

3. The method of claim 1, wherein, Step S2 specifically comprises: S21, identifying a blink frame from the sequence of eye movement images; S22, replacing the eye movement position of the blink frame with the eye movement position of a previous frame of the blink frame.

4. The method of claim 1, wherein, Step S2 specifically comprises: S23, identifying an eye movement loss frame from the sequence of eye movement images; S24, identifying a position of the eye movement loss frame; S25, compensating the eye movement position data of the eye movement loss frame according to effective eye movement position data of frames before and after the identified position.

5. The method of claim 1, wherein, Step S2 specifically comprises: S26, performing bilateral filtering processing on the eye movement position data.

6. The method of claim 4, wherein, In step S23, if the identified eye movement loss frame is located at a beginning part or an ending part of the sequence of eye movement images, the eye movement loss frame is discarded.

7. A processing system of vision test data, characterized by The system comprises a display device and an eye movement image collection device; wherein, the display device is configured to display a target on a display interface thereof; the eye movement image collection device is configured to collect a sequence of eye movement images of a testee watching the target; The system further comprises: a detection controller configured to control the display device to display a target back and forth on a display interface thereof at a set speed; the target corresponds to a visual acuity level; when displaying a target corresponding to a visual acuity level each time, the processing method for visual acuity detection data according to any one of claims 1-6 is executed to judge whether the testee successfully follows the target each time.

8. A vision detection system characterized by, The system comprises: The processing system for visual acuity detection data according to claim 7; a visual acuity judgment controller configured to determine the visual acuity of the testee based on the judgment result of the detection controller, comprising: when it is judged that the testee successfully follows the target each time, updating the target displayed on the display interface of the display device; the updated target is improved by one visual acuity level compared with the original target; If the detection controller judges that the successful target following is achieved, the target of the vision level increased by one is displayed again until the detection controller judges that the successful target following is not achieved, and the vision level corresponding to the target displayed when the successful target following is last judged to be achieved is determined as the vision of the tested person.

9. The visual acuity detection system of claim 8, wherein, The vision judgment controller determines the vision of the tested person according to the judgment result, comprising: When it is judged that the successful target following is not achieved, the target displayed on the display interface of the display device is updated, and the updated target is of a vision level decreased by one compared with the original target; If the detection controller judges that the successful target following is not achieved, the target of the vision level decreased by one is displayed again until the detection controller judges that the successful target following is achieved, and the vision level corresponding to the target displayed when the successful target following is currently judged to be achieved is determined as the vision of the tested person.

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