CN106778597B - Intelligent vision detector based on image analysis - Google Patents
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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- 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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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/107—Static hand or arm
- G06V40/113—Recognition of static hand signs
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Abstract
The invention discloses an intelligent vision detector based on image analysis, which adopts a display screen to display vision detection marks with directions, identifies the gesture direction of a user based on an image analysis technology, and updates the direction and/or the size of the next vision detection mark according to each vision detection result until the detection is finished; compared with the prior art, the visual acuity test system can help a user to independently complete own visual acuity test, has the same visual acuity test mode as that of the current visual acuity test mechanism, and is very convenient to use.
Description
Technical Field
The invention relates to an image processing and pattern recognition technology, in particular to an intelligent vision detector based on image analysis.
Background
Along with the improvement of the technological level, the popularity of high-technology products such as computers, smart phones and tablet computers is higher and higher, the use of the electronic products really brings great convenience to our lives, but not negligibly, the use of the electronic products also brings great harm, and particularly, the damage to the eyesight is not negligibly.
The protection of vision is very important from the viewpoint of both beauty and health, and especially for teenagers in the growth period, the vision is easily degraded by external stimulation and self poor eye use habits.
Currently, vision testing is usually performed manually at a specific testing facility (e.g., a laboratory of a hospital or a prescription facility), so that the user cannot perform vision testing independently.
Disclosure of Invention
The invention aims to provide an intelligent vision detector based on image analysis, so as to achieve the aim of enabling a user to independently test the vision at any time and any place.
The purpose of the invention is realized by the following technical scheme:
an intelligent vision tester based on image analysis, comprising: the system comprises an image acquisition module, a face detection module, a gesture recognition module, an eye chart display module and a voice prompt and result display module; wherein:
the image acquisition module is used for acquiring an external image for the face detection module and the gesture recognition module to use;
the face detection module is used for carrying out face detection according to the image acquired by the image acquisition module, calibrating a gesture detection range if the face is detected for a plurality of times continuously, and informing the visual chart display module to start vision detection;
the visual acuity test chart display module is used for displaying visual acuity test marks with directions according to a visual acuity test algorithm and updating the direction and/or the size of the next visual acuity test mark according to a test result;
the gesture recognition module is used for detecting the outline of a hand through skin color in a calibrated gesture detection range and analyzing the outline to obtain the current gesture direction of the user;
the voice prompt and result display module is used for comparing the expected direction of the vision detection identification with the direction sent by the visual chart display module currently and the gesture direction identified by the gesture identification module, and outputting the obtained detection result in a voice broadcast and screen display mode.
The face detection process is as follows:
carrying out face detection based on a pre-trained Haar feature classifier, and removing an interference item with an area smaller than a preset value from a detection result of the Haar feature classifier;
and calculating the proportion of the skin color blocks in the detection result, and considering that one face is detected when the proportion reaches a certain value.
In the calibrated gesture detection range, detecting the hand contour through skin color detection and analyzing to obtain the current gesture direction of the user comprises the following steps:
cutting out the calibrated gesture detection range from the image;
obtaining the contour of a skin color block by a skin color detection method, and traversing to find out the maximum contour, namely the suspected gesture contour;
judging whether the gesture is interference or not according to the size and the length-width ratio of the suspected gesture outline, and if the gesture is interference, indicating that the user does not point; otherwise, indicating that a gesture outline is detected;
traversing all points on the gesture outline, searching for a point with the maximum distance from the gesture outline to the outline gravity center, and excluding an interference extreme point with the number of continuous descending points on two sides being smaller than a preset value;
calculating the average distance descending speed of descending points on two sides in the remaining extreme points, wherein the point with the highest descending speed is the most prominent point on the contour and corresponds to the finger tip point when a user points to a certain direction;
fitting a section of profile of the fingertip points in the anticlockwise direction into a straight line, calculating an included angle between the straight line and a transverse axis, and considering that the user points to the transverse direction if the included angle is smaller than a boundary angle, or considering that the user points to the vertical direction;
if the outline is judged to be transverse, the transverse relative position of the gravity center of the outline is checked, and the relative position is opposite to the direction, namely the gravity center indicates that the outline is leftwards in the right half part, and otherwise, the outline is rightwards; if the vertical direction is judged, the vertical relative position of the gravity center of the contour is checked, and the relative position is opposite to the direction, namely the gravity center is indicated to be upward at the lower half part, and is indicated to be downward otherwise.
The displaying the vision test identification with the direction according to the vision test algorithm, and the updating the direction and/or the size of the next vision test identification according to the test result comprises:
the vision detection marks have N rows from large to small, and each row comprises a plurality of vision detection marks with the same size and different directions;
in the initial stage, randomly selecting a visual detection identifier in one direction from the ith row to display;
then, the vision detection identification in the other direction randomly selected from the ith row is continuously used for displaying, and if the detection results are correct for multiple times, a descending mode is entered; if the detection result is wrong for a plurality of times continuously, entering an ascending mode;
in a descending mode, randomly selecting a visual detection identifier in one direction from the (i + 1) th row for displaying; in the ascent mode, a visual acuity test indicia display in one direction is randomly selected from row i-1.
In the descending mode, if the detection results of the continuous times are correct and i +1 is equal to N, the vision detection is finished; if the continuous multiple detection results are correct and i +1 is smaller than N, randomly selecting a visual detection identifier in one direction from the i +2 th row for display; if the detection results are wrong for a plurality of times continuously, the vision detection is finished;
in the ascending mode, if the detection results of the continuous times are wrong and i-1 is equal to 1, the vision detection is finished; if the continuous detection results are wrong for multiple times and i +1 is larger than 1, randomly selecting a visual detection identifier in one direction from the (i-2) th row for display; and if the detection results of the continuous times are correct, the vision detection is finished.
According to the technical scheme provided by the invention, the vision detection marks with directions are displayed by adopting the display screen, the gesture direction of the user is recognized based on the image analysis technology, and the direction and/or the size of the next vision detection mark is updated according to each vision detection result until the detection is finished; compared with the prior art, the visual acuity test system can help a user to independently complete own visual acuity test, has the same visual acuity test mode as that of the current visual acuity test mechanism, and is very convenient to use.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a schematic diagram of an intelligent vision tester based on image analysis according to an embodiment of the present invention;
fig. 2 is a flowchart of the operation of the intelligent vision tester based on image analysis according to the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic diagram of an intelligent vision tester based on image analysis according to an embodiment of the present invention. As shown in fig. 1, it mainly includes: the system comprises an image acquisition module, a face detection module, a gesture recognition module, an eye chart display module and a voice prompt and result display module; wherein:
the image acquisition module is used for acquiring an external image for the face detection module and the gesture recognition module to use;
the face detection module is used for carrying out face detection according to the image acquired by the image acquisition module, calibrating a gesture detection range if the face is detected for a plurality of times continuously, and informing the visual chart display module to start vision detection;
the visual acuity test chart display module is used for displaying visual acuity test marks with directions according to a visual acuity test algorithm and updating the direction and/or the size of the next visual acuity test mark according to a test result;
the gesture recognition module is used for detecting the outline of a hand through skin color in a calibrated gesture detection range and analyzing the outline to obtain the current gesture direction of the user;
the voice prompt and result display module is used for comparing the expected direction of the current vision detection identification with the direction sent by the visual chart display module with the gesture direction (namely the actual direction) identified by the gesture identification module, and outputting the obtained detection result in a voice broadcast and screen display mode.
For easy understanding, the operation of the intelligent vision tester will be described in detail with reference to fig. 2.
Before the vision test is started, the external image is collected by the image collection module, and for example, the real-time image can be collected continuously at a proper short interval (for example, 2 s). The human face detection module is used for identifying whether a human face exists or not, after the human face is detected, the human face size is checked to prevent the station position from being too close or too far, the human face position is checked to prevent the station position from being too biased, whether the human face is an effective human face is finally determined, when the effective human face is detected twice continuously, the vision test can be started, a gesture detection range is calibrated, and a jacket range can be selected as the gesture detection range in order to remove background interference.
Illustratively, the face detection may be performed as follows: carrying out face detection based on a pre-trained Haar feature classifier, and removing an interference item with an area smaller than a preset value from a detection result of the Haar feature classifier; and calculating the proportion of the skin color blocks in the detection result, and considering that one face is detected when the proportion reaches a certain value.
After the vision test starts, the vision test table display module displays a vision test mark with a direction on a display screen based on a vision test algorithm, at the moment, after an image is collected, a gesture recognition algorithm is used for recognition in a gesture detection range, after a certain direction of a user is recognized, whether the direction is correct or not is judged, a judgment result is broadcasted and displayed, and the direction and/or the size of the next vision test mark is updated according to the vision test algorithm.
And then, repeating the vision detection according to the mode until the detection is finished.
Illustratively, the visual acuity test indicia with directions may be conventional E-indicia.
Illustratively, the gesture direction detection may be performed as follows: 1) cutting out the calibrated gesture detection range from the image; 2) obtaining the contour of a skin color block by a skin color detection method, and traversing to find out the maximum contour, namely the suspected gesture contour; 3) judging whether the gesture is interference or not according to the size and the length-width ratio of the suspected gesture outline, and if the gesture is interference, indicating that the user does not point; otherwise, indicating that a gesture outline is detected; 4) traversing all points on the gesture outline, searching for a point with the maximum distance from the gesture outline to the outline gravity center, and excluding an interference extreme point with the number of continuous descending points on two sides being smaller than a preset value; 5) calculating the average distance descending speed of descending points on two sides in the remaining extreme points, wherein the point with the highest descending speed is the most prominent point on the contour and corresponds to the finger tip point when a user points to a certain direction; 6) fitting a section of profile of the fingertip points in the anticlockwise direction into a straight line, calculating an included angle between the straight line and a transverse axis, and considering that the user points to the transverse direction if the included angle is smaller than a boundary angle, or considering that the user points to the vertical direction; 7) if the outline is judged to be transverse, the transverse relative position of the gravity center of the outline is checked, and the relative position is opposite to the direction, namely the gravity center indicates that the outline is leftwards in the right half part, and otherwise, the outline is rightwards; if the vertical direction is judged, the vertical relative position of the gravity center of the contour is checked, and the relative position is opposite to the direction, namely the gravity center is indicated to be upward at the lower half part, and is indicated to be downward otherwise.
For example, the visual acuity test chart display module displays the visual acuity test marks with the directions, and updating the direction and/or the size of the next visual acuity test mark according to the detection result can be realized by the following steps:
there are N rows (e.g., 14 rows) of visors from large to small, each row containing several visors of the same size but different directions.
In the initial stage, randomly selecting a visual detection identifier in one direction from the ith row (8 th row) for display;
then, the vision testing mark randomly selected from the ith row in the other direction is continuously used for displaying, and if the testing results are correct for a plurality of times (for example, twice), a descending mode is entered; if the detection result is wrong for a plurality of times continuously, entering an ascending mode;
in a descending mode, randomly selecting a vision detection identifier in one direction from the (i + 1) th row for display, and if the detection result is correct for a plurality of times continuously and i +1 is equal to N, finishing the vision detection; if the continuous multiple detection results are correct and i +1 is smaller than N, randomly selecting a visual detection identifier in one direction from the i +2 th row for display; if the detection results are wrong for a plurality of times continuously, the vision detection is finished;
in the ascending mode, randomly selecting a vision detection identifier in one direction from the (i-1) th row for display, and if the detection result is wrong for a plurality of times continuously and i-1 is equal to 1, finishing the vision detection; if the continuous detection results are wrong for multiple times and i +1 is larger than 1, randomly selecting a visual detection identifier in one direction from the (i-2) th row for display; and if the detection results of the continuous times are correct, the vision detection is finished.
According to the invention, image processing and mode recognition technology is utilized, corresponding software part development can be carried out based on an android platform, images are finally acquired through android equipment, and the pointing condition of a user is analyzed through face recognition and gesture recognition, so that a portable vision detection tool borne on the android equipment is realized.
According to the scheme of the embodiment of the invention, the vision detection identification with the direction is displayed by adopting the display screen, the gesture direction of the user is identified based on the image analysis technology, and the direction and/or the size of the next vision detection identification is updated according to each vision detection result until the detection is finished; compared with the prior art, the visual acuity test system can help a user to independently complete own visual acuity test, has the same visual acuity test mode as that of the current visual acuity test mechanism, and is very convenient to use.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to perform all or part of the above described functions.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (4)
1. An intelligent vision tester based on image analysis, comprising: the system comprises an image acquisition module, a face detection module, a gesture recognition module, an eye chart display module and a voice prompt and result display module; wherein:
the image acquisition module is used for acquiring an external image for the face detection module and the gesture recognition module to use;
the face detection module is used for carrying out face detection according to the image acquired by the image acquisition module, calibrating a gesture detection range if the face is detected for a plurality of times continuously, and informing the visual chart display module to start vision detection;
the visual acuity test chart display module is used for displaying visual acuity test marks with directions according to a visual acuity test algorithm and updating the direction and/or the size of the next visual acuity test mark according to a test result;
the gesture recognition module is used for detecting the outline of a hand through skin color in a calibrated gesture detection range and analyzing the outline to obtain the current gesture direction of the user;
the voice prompt and result display module is used for comparing the expected direction of the current vision detection identification with the direction sent by the visual chart display module with the gesture direction identified by the gesture identification module, and outputting the obtained detection result in a voice broadcast and screen display mode;
in the calibrated gesture detection range, detecting the hand contour through skin color detection and analyzing to obtain the current gesture direction of the user comprises the following steps:
cutting out the calibrated gesture detection range from the image;
obtaining the contour of a skin color block by a skin color detection method, and traversing to find out the maximum contour, namely the suspected gesture contour;
judging whether the gesture is interference or not according to the size and the length-width ratio of the suspected gesture outline, and if the gesture is interference, indicating that the user does not point; otherwise, indicating that a gesture outline is detected;
traversing all points on the gesture outline, searching for a point with the maximum distance from the gesture outline to the outline gravity center, and excluding an interference extreme point with the number of continuous descending points on two sides being smaller than a preset value;
calculating the average distance descending speed of descending points on two sides in the remaining extreme points, wherein the point with the highest descending speed is the most prominent point on the contour and corresponds to the finger tip point when a user points to a certain direction;
fitting a section of profile of the fingertip points in the anticlockwise direction into a straight line, calculating an included angle between the straight line and a transverse axis, and considering that the user points to the transverse direction if the included angle is smaller than a boundary angle, or considering that the user points to the vertical direction;
if the outline is judged to be transverse, the transverse relative position of the gravity center of the outline is checked, and the relative position is opposite to the direction, namely the gravity center indicates that the outline is leftwards in the right half part, and otherwise, the outline is rightwards; if the vertical direction is judged, the vertical relative position of the gravity center of the contour is checked, and the relative position is opposite to the direction, namely the gravity center is indicated to be upward at the lower half part, and is indicated to be downward otherwise.
2. The intelligent vision tester based on image analysis of claim 1, wherein the human face detection process is as follows:
carrying out face detection based on a pre-trained Haar feature classifier, and removing an interference item with an area smaller than a preset value from a detection result of the Haar feature classifier;
and calculating the proportion of the skin color blocks in the detection result, and considering that one face is detected when the proportion reaches a certain value.
3. The intelligent vision tester as claimed in claim 1, wherein the step of displaying the vision test marks with directions according to the vision test algorithm, and the step of updating the direction and/or size of the next vision test mark according to the test result comprises:
the vision detection marks have N rows from large to small, and each row comprises a plurality of vision detection marks with the same size and different directions;
in the initial stage, randomly selecting a visual detection identifier in one direction from the ith row to display;
then, the vision detection identification in the other direction randomly selected from the ith row is continuously used for displaying, and if the detection results are correct for multiple times, a descending mode is entered; if the detection result is wrong for a plurality of times continuously, entering an ascending mode;
in a descending mode, randomly selecting a visual detection identifier in one direction from the (i + 1) th row for displaying; in the ascent mode, a visual acuity test indicia display in one direction is randomly selected from row i-1.
4. The intelligent vision tester as claimed in claim 3, wherein the testing device comprises a display device,
in the descending mode, if the detection results of the continuous times are correct and i +1 is equal to N, the vision detection is finished; if the continuous multiple detection results are correct and i +1 is smaller than N, randomly selecting a visual detection identifier in one direction from the i +2 th row for display; if the detection results are wrong for a plurality of times continuously, the vision detection is finished;
in the ascending mode, if the detection results of the continuous times are wrong and i-1 is equal to 1, the vision detection is finished; if the continuous detection results are wrong for multiple times and i +1 is larger than 1, randomly selecting a visual detection identifier in one direction from the (i-2) th row for display; and if the detection results of the continuous times are correct, the vision detection is finished.
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| CN109171637A (en) * | 2018-09-30 | 2019-01-11 | 苏州安视沛清科技有限公司 | Vision testing method, device, computer storage medium and computer equipment |
| CN110353622A (en) * | 2018-10-16 | 2019-10-22 | 武汉交通职业学院 | A kind of vision testing method and eyesight testing apparatus |
| CN110338748B (en) * | 2019-06-13 | 2022-03-08 | 宁波明星科技发展有限公司 | Method for quickly positioning vision value, storage medium, terminal and vision detector |
| CN110432859B (en) * | 2019-07-31 | 2021-10-19 | 刘葳 | Vision detection method and device |
| CN110916609A (en) * | 2019-12-19 | 2020-03-27 | 北京九辰智能医疗设备有限公司 | Vision detection device |
| CN114639114A (en) * | 2020-11-30 | 2022-06-17 | 华为技术有限公司 | Vision detection method and electronic equipment |
| CN113243886B (en) * | 2021-06-11 | 2021-11-09 | 四川翼飞视科技有限公司 | Vision detection system and method based on deep learning and storage medium |
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