CN112806953A - Automatic vision detection method and system - Google Patents
Automatic vision detection method and system Download PDFInfo
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- CN112806953A CN112806953A CN201911215989.7A CN201911215989A CN112806953A CN 112806953 A CN112806953 A CN 112806953A CN 201911215989 A CN201911215989 A CN 201911215989A CN 112806953 A CN112806953 A CN 112806953A
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- 230000004438 eyesight Effects 0.000 title claims abstract description 37
- 238000001514 detection method Methods 0.000 title claims abstract description 33
- 230000000007 visual effect Effects 0.000 claims abstract description 65
- 238000012360 testing method Methods 0.000 claims abstract description 34
- 238000000034 method Methods 0.000 claims description 18
- 238000012545 processing Methods 0.000 claims description 15
- 238000007405 data analysis Methods 0.000 claims description 12
- 230000008569 process Effects 0.000 claims description 7
- 230000009191 jumping Effects 0.000 claims description 3
- 230000004044 response Effects 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 claims description 2
- 238000007689 inspection Methods 0.000 claims 6
- 238000012216 screening Methods 0.000 abstract description 7
- 238000010606 normalization Methods 0.000 abstract description 2
- 230000036541 health Effects 0.000 description 4
- 230000004379 myopia Effects 0.000 description 4
- 208000001491 myopia Diseases 0.000 description 4
- 230000003247 decreasing effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/02—Subjective types, i.e. testing apparatus requiring the active assistance of the patient
- A61B3/028—Subjective types, i.e. testing apparatus requiring the active assistance of the patient for testing visual acuity; for determination of refraction, e.g. phoropters
- A61B3/032—Devices for presenting test symbols or characters, e.g. test chart projectors
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/0016—Operational features thereof
- A61B3/0033—Operational features thereof characterised by user input arrangements
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/0016—Operational features thereof
- A61B3/0041—Operational features thereof characterised by display arrangements
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Abstract
The invention provides an automatic vision detection method and system, wherein the information of a tested person is obtained, a visual chart test image is displayed through a screen, the tested person sees the image to make a gesture in a corresponding direction, a gesture recognition device recognizes the gesture direction, the system judges whether the gesture direction is consistent with the image direction or not, the system automatically records the test result of the tested person, and after the test is finished, the screen prompts the tested person to finish the test and automatically uploads the test result to the system. The invention has no manual intervention, and the detected person completes the detection independently, thereby having the advantages of reducing the cost, improving the efficiency and improving the unified normalization of the detection; the information of the tested person is automatically compared, the detection result is automatically recorded, and the data is uploaded, so that the system can work all weather, and the screening work can be carried out at any time.
Description
Technical Field
The invention relates to a health detection platform, in particular to an automatic vision detection method and system.
Background
The myopia of students in China shows the tendency of high incidence and low aging, and seriously affects the physical and mental health of children, which is a big problem in the future of related countries and nations, and the high attention is paid to the myopia and the myopia cannot be developed. Therefore, a visual system for big vision health data of students at school, a review and assessment basis for myopia prevention and control work and a system prevention and control scheme are needed to be provided for the national education department and the health system, the vision screening work is carried out, and files are established. The vision screening work mainly comprises vision detection and refraction detection, the establishment of a teenager eye health screening file radiates all students at school, the quantity is large, the number of people is large, and the work task is heavy.
The current vision detection realizes the operation mode:
1) traditional lamp house visual testing: a doctor stands on the lamp box side to command and complete the full detection process, and manually records detection data;
A. each tested person needs one-to-one service of a doctor, and is very hard;
B. the screening site is generally spread in a school auditorium or a gymnasium, the space is very large, the noise of many people is noisy, a doctor needs very loud sound to communicate with a tested person, the voice cannot be received, and the command cannot be transmitted or the transmission is wrong;
C. the detection data is manually input or recorded, the workload is large, and errors are easy to occur.
2) Electronic visual chart detection: a doctor sits beside the tested person and commands the mobile equipment to complete the full detection process, and the system automatically records detection data;
the testees need one-to-one doctor service, and the testees are huge in quantity, and the screening cost is greatly increased.
Disclosure of Invention
The invention provides an automatic vision detection method and system, which solve the problems of a large number of detected visions, large workload and easy error, and adopts the following technical scheme:
an automatic vision detection method and system comprises the following steps:
s1, obtaining information of a tested person, and identifying the identity of the tested person through code scanning of an intelligent terminal or face recognition of a camera;
s2, starting testing, and displaying a test image of the visual chart through a screen;
s3, the tested person sees the image to make a gesture in a corresponding direction;
s4, acquiring an image by a camera, and identifying a gesture direction by a gesture identification device;
s5, judging whether the gesture direction is consistent with the image direction by the system;
s6, the system automatically records the test result of the tested person;
and S7, finishing the test, prompting the tested person to finish the test by a screen, and automatically uploading a test result to the system.
Further, in step S1 and step S2, before the test is started, the subject stands and designates a position based on the screen presentation information, and learns the gesture based on the content displayed on the screen.
Further, the steps S2-S7 need to be performed twice, and the left and right eyes of the subject are tested respectively.
Further, in step S5, the system determines whether the gesture direction is consistent with the image direction, randomly points to the optotypes from 4.0, each line points to 1 optotype, and automatically jumps one line downward after the answer is right until the answer is wrong;
randomly pointing different visual targets one by one from the beginning to answer wrong rows:
1)4.0 error response: no longer indicating sighting mark, automatically judging result "< 4.0";
2)4.1-4.2 errors: directly jumping up a line of sighting marks;
3)4.3-4.6 answers wrong: the line needs 3 visual targets, the line vision is answered for 2, and the visual targets in the line are skipped up by 2 wrong answers;
4)4.7-4.9 answers wrong: the line needs to indicate 5 visual targets, the line vision is answered for 3, and the visual targets in the line are skipped up by answering 3 wrongly;
5)5.0-5.3 wrong answers: the line needs 7 visual targets, the line's vision is answered 4 pairs, and the line's visual targets are skipped over 4 wrong answers.
Further, in step S2, the screen is replaced by a mechanical visual chart, the mechanical visual chart includes a back plate, a visual target motor, a light-emitting plate, and a visual target, the light-emitting plate is provided with a red indicator below each visual target, the visual target motor is fixed on the back plate, a motor shaft at the front end passes through the light-emitting plate to be fixedly connected with the visual target, each visual target corresponds to one visual target motor, the visual target motor line and the red indicator are connected to an adjusting device, and the adjusting device is connected to the system of the method and receives the system command.
Further, the control device is provided with an input device for sending instructions to an adjusting device, and the adjusting device is used for randomly adjusting the visual targets of the mechanical visual chart, including adjusting the number, the line number and the angle of the visual targets.
After the sighting target is adjusted, when the sighting target is selected, the sighting target is selected through a red indicating lamp, or a handheld mobile device emits sound for indication.
The visual chart monitoring system comprises a visual chart display screen, handheld mobile equipment, a gesture recognition device and a control device, wherein the control device comprises a service processing device and a data analysis device, and the control device is respectively connected with the gesture recognition device, the visual chart display screen and the handheld mobile equipment;
the gesture recognition device is provided with a camera and is used for shooting the image of the detected person through the camera; the gesture recognition device is connected with the data analysis device, and the data analysis device recognizes the gesture of the detected person by analyzing the image;
the handheld mobile equipment is connected with the service processing device and used for receiving a relevant result of whether the gesture is correct or not;
the data analysis device can send the result of the gesture recognition processing to the business processing device.
The control device is also connected with an intelligent terminal code scanning or camera face recognition device for recognizing the identity of the entering tested person.
The service processing device can also receive data for the operation of the handheld mobile equipment and process the data.
The vision automatic detection method and the system provided by the invention have the advantages that a doctor does not need to participate, the testee autonomously completes the vision detection process, and the system automatically records the detection data.
Drawings
FIG. 1 is a schematic diagram of an automated vision testing system provided by the present invention;
FIG. 2 is a schematic flow chart of an automatic vision testing method provided by the present invention;
FIG. 3 is a schematic view of the operation of the judgment;
FIG. 4 is a schematic diagram of a mechanical eye chart;
fig. 5 is an enlarged schematic view of a part of the structure of fig. 4.
Detailed Description
As shown in fig. 1, the automatic vision detection system provided by the present invention includes an eye chart display screen, a handheld mobile device, a gesture recognition device, and a control device, where the control device includes a service processing device and a data analysis device, and the control device is connected to the gesture recognition device, the eye chart display screen, and the handheld mobile device, respectively.
The gesture recognition device is provided with a camera and is used for shooting the image of the measured person through the camera, and the image comprises gestures. The gesture recognition device is connected with the data analysis device, and the data analysis device recognizes the gesture of the detected person by analyzing the image.
The handheld mobile equipment is connected with the service processing device and used for receiving the relevant result of whether the gesture is correct or not. The service processing device can receive data and process the data for the operation of the handheld mobile equipment.
The data analysis device can send the result of the gesture recognition processing to the business processing device.
The control device is also connected with an intelligent terminal code scanning or camera face recognition device for recognizing the identity of the entering tested person.
As shown in fig. 2, the automatic vision detection method includes the following steps:
s1, obtaining information of a tested person, and identifying the identity of the tested person through code scanning of an intelligent terminal or face recognition of a camera;
s2, starting testing, and displaying a test image of the visual chart through a screen;
s3, the tested person sees the image to make a gesture in a corresponding direction;
s4, acquiring an image by a camera, and identifying a gesture direction by a gesture identification device;
s5, judging whether the gesture direction is consistent with the image direction by the system;
s6, the system automatically records the test result of the tested person;
and S7, finishing the test, prompting the tested person to finish the test by a screen, and automatically uploading a test result to the system.
Before the test is started in step S2, the testee can specify a position according to the screen prompt information station and learn gesture actions according to the content displayed on the screen. The gesture recognition is carried out on the establishment of a detection model, a lightweight deep neural network MobileNet-SSD network structure is adopted, the convolution can be decomposed in a lightweight, low-delay and deep manner, and the training efficiency and accuracy are improved.
The data preprocessing of gesture recognition includes random crop, random expansion, random horizontal flipping, random scaling, brightness, hue, saturation, contrast. The learning rate is continuously decreased in cos manner, and then is suddenly increased and then continuously decreased. In recognition, the input image is selected in a plurality of sizes.
After the test is started, the steps S2-S7 are performed twice, and the left and right eyes of the subject are tested.
In step S4, the gesture recognition apparatus monitors the user' S movement through the camera and recognizes the gesture direction.
As shown in fig. 3, when the test is performed in step S5, the system determines whether the gesture direction is consistent with the image direction, and randomly points to the optotypes from 4.0 by using the standard detection mode, each line indicates 1 optotype, and after the answer is answered, the system automatically jumps down one line until the answer is wrong.
Randomly pointing different visual targets one by one from the beginning to answer wrong rows:
1)4.0 error response: no longer indicating sighting mark, automatically judging result "< 4.0";
2)4.1-4.2 errors: directly jumping up a line of sighting marks;
3)4.3-4.6 answers wrong: the line needs 3 visual targets, the line vision is answered for 2, and the visual targets in the line are skipped up by 2 wrong answers;
4)4.7-4.9 answers wrong: the line needs to indicate 5 visual targets, the line vision is answered for 3, and the visual targets in the line are skipped up by answering 3 wrongly;
5)5.0-5.3 wrong answers: the line needs 7 visual targets, the line's vision is answered 4 pairs, and the line's visual targets are skipped over 4 wrong answers.
The optotype for each row is randomly determined by the system, but is not repeated.
However, because the system adopts the screen display visual chart, the tested person can not successfully learn the gesture actions according to the content displayed on the screen within the effective time, or the gesture identification is unclear for 3 times in the test process, and the tested person can carry out direction designation by holding the mobile device for testing.
In some cases, the screen is in trouble or the subject is unable to adapt to the light source of the screen, and the present invention also has an alternative mechanical eye chart for the screen.
As shown in fig. 4 and 5, the present invention employs a mechanical visual chart, which includes a back plate 1, a sighting mark motor 2, a light-emitting plate 3, and sighting marks 5, each sighting mark 5 of the visual chart is fixed by the following sighting mark motor 2, the sighting mark motor 2 employs a stepping motor, and a motor shaft 5 of the sighting mark motor is connected to the sighting mark 5. The rear end of the sighting mark motor 2 is fixed on the back plate 1.
The mechanical visual chart is connected to an adjusting device, the adjusting device is connected with a control device, the adjusting device is in line connection with the visual target motors 2 of all the visual targets 5, and the random rotation of the visual targets 5 is controlled through the adjusting device.
The adjustment method comprises the following steps:
1) inputting the number of the adjusted sighting marks into the control device, for example, inputting 5, and then adjusting the sighting marks of the next person to be tested by the mechanical visual chart, wherein the number of the adjustment is 5; the input total number of the adjusted sighting mark number is generally 3-8; if not, no adjustment is carried out;
2) when the control device inputs the adjusted line number, for example, input 3, the three lines of sighting marks are randomly adjusted before the next person to be measured, and the total number of the sighting marks is adjusted to 5; or 6-8 is input, the optotypes from the 6 th line to the 8 th line are adjusted, and 5 optotypes are adjusted in total; setting the adjusted line number, and reporting an error if the number of all the visual targets of the line number is less than the adjusted visual target number; if not, randomly selecting all the line numbers by default;
3) the angle of adjustment is input in the control device, which can be set to 90 degrees, 180 degrees and 270 degrees, and after selection, when the selected line number and the number of the sighting marks are adjusted, the corresponding angle is adjusted clockwise; if not, the selected sighting target is randomly adjusted.
4) After the sighting target is adjusted, when the sighting target is selected, the sighting target can be selected by arranging a red indicating lamp below each sighting target on the luminous plate or by sending sound to indicate through handheld mobile equipment.
The test of the visual chart is realized by gesture recognition at each time or by selecting the visual target direction through handheld mobile equipment.
The invention detects through artificial intelligence and electronic visual chart. The method has the following advantages:
1) the human intervention is not needed, the detected person completes the detection independently, and the method has the advantages of reducing the cost, improving the efficiency and improving the unified normalization of the detection;
2) automatically comparing the information of the testee, automatically recording the detection result and uploading data;
3) the recognition degree is 99.9%, and the device works in all weather;
4) the system is packaged into an all-in-one machine which can be placed in schools to carry out screening work at any time.
Claims (10)
1. An automatic vision detection method and system comprises the following steps:
s1, obtaining information of a tested person, and identifying the identity of the tested person through code scanning of an intelligent terminal or face recognition of a camera;
s2, starting testing, and displaying a test image of the visual chart through a screen;
s3, the tested person sees the image to make a gesture in a corresponding direction;
s4, acquiring an image by a camera, and identifying a gesture direction by a gesture identification device;
s5, judging whether the gesture direction is consistent with the image direction by the system;
s6, the system automatically records the test result of the tested person;
and S7, finishing the test, prompting the tested person to finish the test by a screen, and automatically uploading a test result to the system.
2. The automatic vision inspection method of claim 1, wherein: in step S1 and step S2, before starting the test, the subject stands at a designated position according to the screen prompt information and learns the gesture motion according to the contents displayed on the screen.
3. The automatic vision inspection method of claim 1, wherein: the steps S2 to S7 need to be performed twice, and the left and right eyes of the subject are tested respectively.
4. The automatic vision inspection method of claim 1, wherein: in step S5, the system judges whether the gesture direction is consistent with the image direction, randomly points to the sighting marks from 4.0, each line points to 1 sighting mark, and automatically jumps downwards one line after the answer is right until the answer is wrong;
randomly pointing different visual targets one by one from the beginning to answer wrong rows:
1)4.0 error response: no longer indicating sighting mark, automatically judging result "< 4.0";
2)4.1-4.2 errors: directly jumping up a line of sighting marks;
3)4.3-4.6 answers wrong: the line needs 3 visual targets, the line vision is answered for 2, and the visual targets in the line are skipped up by 2 wrong answers;
4)4.7-4.9 answers wrong: the line needs to indicate 5 visual targets, the line vision is answered for 3, and the visual targets in the line are skipped up by answering 3 wrongly;
5)5.0-5.3 wrong answers: the line needs 7 visual targets, the line's vision is answered 4 pairs, and the line's visual targets are skipped over 4 wrong answers.
5. The automatic vision inspection method of claim 1, wherein: in step S2, the screen is replaced by a mechanical visual chart, the mechanical visual chart includes a back plate, a target motor, a light-emitting plate, and a target, the light-emitting plate is provided with a red indicator below each target, the target motor is fixed on the back plate, a motor shaft at the front end passes through the light-emitting plate to be fixedly connected with the target, each target corresponds to a target motor, the target motor line and the red indicator are connected to an adjusting device, and the adjusting device is connected to the system of the method and receives the system instruction.
6. The automatic vision inspection method of claim 5, wherein: the control device is provided with an input device for sending instructions to an adjusting device, and the adjusting device is used for randomly adjusting the visual targets of the mechanical visual chart, including adjusting the number, the line number and the angle of the visual targets.
7. The automatic vision inspection method of claim 5, wherein: after the sighting target is adjusted, when the sighting target is selected, the sighting target is selected through a red indicating lamp, or a handheld mobile device emits sound for indication.
8. The vision automatic detection system according to claim 1, characterized in that: the visual chart monitoring system comprises a visual chart display screen, handheld mobile equipment, a gesture recognition device and a control device, wherein the control device comprises a service processing device and a data analysis device, and the control device is respectively connected with the gesture recognition device, the visual chart display screen and the handheld mobile equipment;
the gesture recognition device is provided with a camera and is used for shooting the image of the detected person through the camera; the gesture recognition device is connected with the data analysis device, and the data analysis device recognizes the gesture of the detected person by analyzing the image;
the handheld mobile equipment is connected with the service processing device and used for receiving a relevant result of whether the gesture is correct or not;
the data analysis device can send the result of the gesture recognition processing to the business processing device.
9. The vision automatic detection system of claim 8, wherein: the control device is also connected with an intelligent terminal code scanning or camera face recognition device for recognizing the identity of the entering tested person.
10. The vision automatic detection system of claim 8, wherein: the service processing device can also receive data for the operation of the handheld mobile equipment and process the data.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114305317A (en) * | 2021-12-23 | 2022-04-12 | 广州视域光学科技股份有限公司 | Method and system for intelligently distinguishing user feedback optotypes |
| CN114305316A (en) * | 2021-12-24 | 2022-04-12 | 苏州紫橙网新信息科技有限公司 | Vision detection method and system, vision detection all-in-one machine and storage medium |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108968905A (en) * | 2018-06-19 | 2018-12-11 | 湖州师范学院 | Method, apparatus, system and the computer readable storage medium to give a test of one's eyesight |
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Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108968905A (en) * | 2018-06-19 | 2018-12-11 | 湖州师范学院 | Method, apparatus, system and the computer readable storage medium to give a test of one's eyesight |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114305317A (en) * | 2021-12-23 | 2022-04-12 | 广州视域光学科技股份有限公司 | Method and system for intelligently distinguishing user feedback optotypes |
| CN114305317B (en) * | 2021-12-23 | 2023-05-12 | 广州视域光学科技股份有限公司 | Method and system for intelligently distinguishing user feedback optotype |
| CN114305316A (en) * | 2021-12-24 | 2022-04-12 | 苏州紫橙网新信息科技有限公司 | Vision detection method and system, vision detection all-in-one machine and storage medium |
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Application publication date: 20210518 |