CN113269762B - Screen defect detection method, system and computer storage medium - Google Patents
Screen defect detection method, system and computer storage medium Download PDFInfo
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- CN113269762B CN113269762B CN202110604865.9A CN202110604865A CN113269762B CN 113269762 B CN113269762 B CN 113269762B CN 202110604865 A CN202110604865 A CN 202110604865A CN 113269762 B CN113269762 B CN 113269762B
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- 230000007547 defect Effects 0.000 title claims description 26
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- 238000000034 method Methods 0.000 claims abstract description 15
- 230000000007 visual effect Effects 0.000 claims abstract description 13
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
- G06T7/85—Stereo camera calibration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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Abstract
The invention provides a method, a system and a computer storage medium for detecting screen faults, wherein the method comprises the following steps: acquiring a screen image shot by a 2D camera; detecting and identifying an abnormal region in the screen image, establishing a coordinate system, and calculating position coordinate information of the abnormal region in the screen image; moving a screen, and calibrating a coordinate origin of a coordinate system and a visual field center of the 3D light field camera; calculating a movement compensation value according to the position coordinate information of the abnormal region, moving a screen, and placing the abnormal region in the field center of view of the 3D light field camera; and acquiring a 3D screen image shot by the 3D light field camera, calculating height position information of the abnormal region, judging the bad type of the abnormal region, and judging whether the screen is qualified or not. By utilizing repeated progressive movement, the high-precision position conversion of abnormal points in the screen between the 2D camera station and the 3D camera station is realized, and the influence of movement precision errors is reduced.
Description
Technical Field
The invention relates to the technical field of machine vision, in particular to a method and a system for detecting screen faults and a computer storage medium.
Background
The screen has many points of defects in the conventional 2D AOI detection process, which may be pixel defects or dust, when the dust is positioned on the surface of the screen, the screen is a qualified product, when the dust is positioned below the surface layer of the screen, the screen is a disqualified product, and the traditional 2D camera can only judge the position and the size of the dust or the pixel defects and cannot judge which layer the traditional 2D camera is positioned on. Aiming at the problems, a step-by-step shooting method combining a plurality of cameras is proposed in the prior art to realize the judgment of the defect level, but the 3D camera shooting field of view is small, so that the accuracy of the conversion of products between a 2D camera station and a 3D camera station needs to be further improved in order to improve the identification accuracy.
Disclosure of Invention
The invention aims to provide a method, a system and a computer storage medium for detecting screen faults.
The invention provides a screen defect detection method, which comprises the following steps:
acquiring a screen image shot by a 2D camera;
detecting and identifying an abnormal region in the screen image, establishing a coordinate system, and calculating position coordinate information of the abnormal region in the screen image;
moving the screen, and calibrating the coordinate origin of the coordinate system and the visual field center of the 3D light field camera;
calculating a movement compensation value according to the position coordinate information of the abnormal region, moving a screen, and placing the abnormal region in the field center of view of the 3D light field camera;
and acquiring a 3D screen image shot by a 3D light field camera, calculating the height position information of the abnormal region, judging the bad type of the abnormal region, and judging whether the screen is qualified or not.
As a further improvement of the present invention, "detecting and identifying abnormal areas in the screen image" specifically includes:
detecting the abnormal identification point class in the screen image.
As a further improvement of the present invention, "acquiring a screen image captured by a 2D camera" specifically includes the steps of:
acquiring a first screen image shot by a 2D camera;
performing binarization processing on the first screen image, and dividing the first screen image into a white screen area and a black background area;
and extracting the part of the first screen image, which is positioned in the screen area, to obtain a second screen image.
As a further improvement of the present invention, "calculating the positional information of the abnormal region in the screen image" specifically includes:
and establishing a coordinate system in the range of the second screen image by taking a point in the second screen image as a coordinate origin, and obtaining pixel coordinates Dot (Dx, dy) of the position of the point type abnormality in the second screen image.
As a further improvement of the present invention, "calibrating the coordinate origin of the coordinate system and the field center of view of the 3D light field camera" specifically includes:
moving a screen, and placing pixel points corresponding to the coordinate origin in the field of view area of the 3D light field camera;
calculating a pixel difference between a coordinate origin and a 3D light field camera visual field central point, and multiplying the pixel difference by the pixel size of the 3D light field camera to obtain a first movement compensation value;
and according to the first movement compensation value, moving the screen, and calibrating the coordinate origin and the 3D light field camera visual field center.
As a further improvement of the present invention, "calculating a motion compensation value from the abnormal region position coordinate information, moving a screen, and placing the abnormal region at the center of the 3D light field camera field of view" specifically includes:
multiplying the pixel coordinates by the pixel size of the 2D camera according to the pixel coordinates of the point type abnormality in the second screen image coordinate system to respectively obtain second movement compensation values in the X direction and the Y direction;
and moving the screen according to the movement compensation value, and placing the point type anomaly in the field center of view of the 3D light field camera.
As a further improvement of the present invention, "acquiring a 3D screen image captured by a 3D light field camera, calculating height position information of the abnormal region, judging a type of failure to which the abnormal region belongs, and judging whether the screen is qualified" specifically includes:
shooting to obtain a 3D image of the screen point type abnormal region;
calculating the distance between the point type anomaly and the reference layer;
and comparing the distance with a preset threshold value, and judging the bad type of the point type abnormality.
As a further improvement of the present invention, "calculate the distance of the point-like anomaly from the reference layer; the comparing the distance with the magnitude of the preset threshold value specifically comprises:
calculating the distance between the point type abnormality and the screen pixel layer;
when the distance is smaller than the surface layer height of the screen, judging that the point type abnormality is located in the screen;
and when the distance is larger than the height of the surface layer of the screen, judging that the point type abnormality is positioned on the surface of the screen.
The invention also provides a system for detecting the screen failure, which comprises:
the jig is used for placing a screen to be detected;
an image acquisition module comprising a 2D camera, a 3D light field camera and a matched light source device, configured to capture a screen image;
the upper computer comprises a memory and a processor, wherein the memory stores a computer program capable of running on the processor, and the processor realizes the steps of the screen failure detection method when executing the program;
and the PLC is configured to control the movement of the jig and realize data transmission with the upper computer.
The present invention also provides a computer storage medium in which a computer program is stored, and which when executed causes a device in which the computer storage medium is located to perform the steps of the above-described screen defect detection method.
The beneficial effects of the invention are as follows: by the method provided by the invention, the high-precision position conversion of the abnormal points in the screen between the 2D camera station and the 3D camera station is realized by utilizing repeated progressive movement, the influence of movement precision errors is reduced, the abnormal points of the screen are ensured to be positioned in the shooting view field of the 3D light field camera after the station conversion, the hierarchical identification of the abnormal points of the screen is finished, the bad types of the abnormal points of the screen are judged, and the identification precision is improved.
Drawings
Fig. 1 is a flowchart of a method for detecting a screen defect according to an embodiment of the invention.
Fig. 2 to 4 are schematic diagrams of images related to steps of a method for detecting a screen failure according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to the specific embodiments of the present application and the corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and are not to be construed as limiting the present invention.
For purposes of illustration, terms such as "upper," "lower," "rear," "front," and the like, are used herein to describe one element or feature's relationship to another element or feature as illustrated in the figures. The term spatially relative position may include different orientations of the device in use or operation than that illustrated in the figures. For example, if the device in the figures is turned over, elements described as "below" or "over" other elements or features would then be oriented "below" or "over" the other elements or features. Thus, the exemplary term "below" can encompass both a spatial orientation of below and above.
As shown in fig. 1, the present invention provides a method for detecting and judging a position of a defective defect in a screen, so as to distinguish the defective defect from a surface defect or a subsurface defect, in this embodiment, taking a mobile phone screen detection as an example, the method includes the steps of:
s1: a first screen image captured by a 2D camera is acquired.
Specifically, step S1 includes the steps of:
s11: and detecting that the position of the jig with the mobile phone is positioned at the same vertical line with the position of the 2D camera, and turning on a light source arranged above the shooting position.
S12: and controlling the 2D camera to acquire the surface image of the mobile phone screen in the vertical direction.
The 2D camera is an industrial CCD camera, etc., which has a larger shooting field of view, but cannot identify a hierarchical area where a defective point is located in an image shot by the industrial CCD camera, and the industrial CCD camera usually shoots to obtain a gray-scale image, and if the industrial CCD camera is a color camera, after shooting to obtain an image of an open-loop workpiece, the method further comprises the steps of: and carrying out grey-scale treatment on the opening ring workpiece image.
As shown in fig. 2, for example, a first screen image is obtained, in which a lit screen area is usually white or bright gray with a larger gray value, and a background portion such as a jig is usually black or dark gray with a smaller gray value in the figure.
In some embodiments of the present invention, after step S1, the method further includes performing binarization processing on the first screen image, which includes the steps of:
s13: the first screen image is binarized to divide it into a white screen area and a black background area.
S14: and extracting the part of the first screen image located in the screen area to obtain a second screen image.
Specifically, a preset pixel gray value is set as a threshold value, or the threshold value is calculated through a currently common algorithm, the pixel gray value in the first screen image is set to 255 which is larger than the threshold value, and 0 which is smaller than the threshold value, and the pixel gray in the image can be divided into a screen area and a background area due to obvious color difference between the screen part and the background part in the image, wherein the screen area is white, and the background image area is black. After the screen area in the first screen image is extracted, an enlarged screen area image is obtained, interference of irrelevant information is reduced, and follow-up detection and recognition accuracy is improved.
Illustratively, as shown in fig. 3, a partial enlarged view of the second screen image extracted from the first screen image.
S2: detecting and identifying an abnormal region in the screen image, establishing a coordinate system, and calculating position coordinate information of the abnormal region in the screen image.
In this embodiment, the detection method is used to identify a dot anomaly, and the size of the dot anomaly may be defined as less than one pixel or several pixels, which may be a screen pixel defect or dust, etc., when the dot anomaly is a screen pixel defect or dust in a screen, the product is an unqualified product, and when the dot anomaly is a screen surface dust, the product is a qualified product. The point type anomaly has a relatively determined coordinate position in a coordinate system, and is more suitable for the detection method provided by the invention.
The gray value of the point type abnormal region in the image is obviously different from the gray value of the normal screen region, and the region with obvious difference between the gray value in the second image and the surrounding region is identified, so that the point type abnormal region can be identified in the second screen image.
Illustratively, as shown in the white circle box in fig. 3, a point type anomaly is present.
After detecting and identifying the point type abnormality, a coordinate system is established in the range of the second screen image by taking a point in the second screen image as the origin of coordinates, and then the pixel coordinates Dot (Dx, dy) of the point type abnormality in the second screen image can be calculated and obtained.
S3: and moving the screen, and calibrating the coordinate origin of the coordinate system and the visual field center of the 3D light field camera.
The 3D light field camera is provided with a special micro lens at the front end of the CCD, light rays passing through the lens are split at one time, information such as position intensity of a plurality of angle spaces can be recorded, then a 3D image of a shooting object is formed through digital focusing, so that depth information of each point in the 3D image can be identified, and the 3D light field camera has high precision, and meanwhile, the field of view is small, so that the whole screen is difficult to shoot.
Specifically, step S3 includes the steps of:
s31: and (3) moving the screen, and placing the pixel points corresponding to the coordinate origins in the field center of view of the 3D light field camera.
Firstly, moving the jig with the mobile phone into the shooting visual field range of the 3D light field camera for the first time, and moving the mobile phone from the 2D camera station to the 3D light field camera station through the first movement with lower precision after the 2D camera shooting is completed because the origin of coordinates is usually defined at a fixed position of a screen, wherein the jig can be moved into the 3D light field camera visual field along a fixed path.
S32: calculating a pixel difference of the coordinate origin from the 3D light field camera visual field center point, multiplying the pixel difference by the pixel size of the 3D light field camera to obtain a first movement compensation value, thereby completing conversion of pixel coordinates and world coordinates, wherein the first movement compensation value is the distance that the coordinate origin needs to be actually moved when moving to the 3D light field camera visual field center.
S33: and according to the first movement compensation value, moving the screen, and calibrating the coordinate origin and the 3D light field camera visual field center.
Through step S32 and step S33, the second movement is performed, the origin of coordinates and the center of the field of view of the 3D light field camera are calibrated, and due to the low accuracy of the first movement, the error compensation is performed by using the second movement, and preparation is performed for the three movements.
In summary, in step S3, high-precision calibration of the origin of coordinates and the center of field of view of the 3D light field camera is achieved by the first movement and the second movement.
S4: and calculating a movement compensation value according to the position coordinate information of the abnormal region, moving the screen, and placing the abnormal region in the field center of view of the 3D light field camera.
Specifically, step S4 includes the following steps:
s41: according to the pixel coordinates Dot (Dx, dy) of the point type anomaly obtained in step S2, the pixel coordinates are multiplied by the pixel size of the 2D camera, so that second motion compensation values in the X direction and the Y direction can be obtained respectively, and conversion of the pixel coordinates and world coordinates is completed, wherein the second motion compensation values are the actual distances between the screen pixel points corresponding to the origin of coordinates and the point type anomaly.
S42: and (3) moving the screen according to the movement compensation value, and placing the point type anomaly in the field center of view of the 3D light field camera.
In step S4, the point type anomaly is located at the center of the field of view of the 3D light field camera by the third movement, so as to ensure that the 3D photograph shot by the 3D light field camera contains the information of the point type anomaly.
In summary, through step S3 and step S4, three progressive movements are utilized to realize high-precision position conversion of abnormal points in the screen between the 2D camera station and the 3D camera station, so that the influence of movement precision errors is reduced, the abnormal points of the screen are ensured to be positioned in the shooting view field of the 3D light field camera after station conversion, and therefore, the hierarchical identification of the abnormal points of the screen is completed, the bad types of the abnormal points of the screen are judged, and the identification precision is improved.
S5: and acquiring a 3D screen image shot by a 3D light field camera, calculating height position information of an abnormal region, judging the type of the abnormal region, and judging whether the screen is qualified or not.
Specifically, step S5 includes:
s51: and shooting to obtain a 3D image of the screen point type abnormal region.
Exemplary, as shown in fig. 4, is a screen 3D image captured by a 3D light field camera and displayed at an angle.
S52: and calculating the distance between the point type anomaly and the reference layer.
Illustratively, in the present embodiment, the distance between the dot-class anomaly and the screen pixel layer is calculated using the screen pixel layer as a reference layer. In some other embodiments of the present invention, a layer having a relatively fixed height position may be selected as the reference layer according to the detection object.
S53: comparing the distance with a preset threshold value, and judging the bad type of the abnormal point class.
In this embodiment, when the distance is smaller than the height of the surface layer of the screen, that is, the point type anomaly is located between the pixel layer and the surface layer of the screen, it is determined that the point type anomaly is located inside the screen, and the product is a defective product that affects the quality of the product; when the distance is greater than the surface layer height of the screen, the judgment point type abnormality is positioned on the surface of the screen, the judgment point type abnormality is erasable surface dust, and the product is a qualified product. In some other embodiments of the present invention, layers with other height values may be selected as the preset threshold according to the detected objects, and considering factors such as product dimensional tolerance.
The invention also provides a system for detecting the screen failure, which comprises: tool, image acquisition module, host computer and PLC controller.
The jig is used for placing a screen to be detected, and the screen to be detected is controlled by the PLC to move in multiple directions in a plane.
The image acquisition module comprises a 2D camera, a 3D light field camera and a matched light source device, and is configured to shoot screen images.
The upper computer comprises a memory and a processor, wherein the memory stores a computer program capable of running on the processor, and the processor realizes the steps of the screen failure detection method when executing the program.
The PLC controller is configured to control the movement of the jig and realize data transmission with the upper computer.
The present invention also provides a computer storage medium in which a computer program is stored, and which when executed causes a device in which the computer storage medium is located to perform the steps of the above-described screen defect detection method.
It should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is for clarity only, and that the skilled artisan should recognize that the embodiments may be combined as appropriate to form other embodiments that will be understood by those skilled in the art.
The above list of detailed descriptions is only specific to practical embodiments of the present invention, and is not intended to limit the scope of the present invention, and all equivalent embodiments or modifications that do not depart from the spirit of the present invention should be included in the scope of the present invention.
Claims (10)
1. A screen defect detection method, characterized by comprising the steps of:
acquiring a screen image shot by a 2D camera;
detecting and identifying an abnormal region in the screen image, establishing a coordinate system, and calculating position coordinate information of the abnormal region in the screen image;
moving the screen, and calibrating the coordinate origin of the coordinate system and the visual field center of the 3D light field camera;
calculating a movement compensation value according to the position coordinate information of the abnormal region, moving a screen, and placing the abnormal region in the field center of view of the 3D light field camera;
and acquiring a 3D screen image shot by a 3D light field camera, calculating the height position information of the abnormal region, judging the bad type of the abnormal region, and judging whether the screen is qualified or not.
2. The screen defect detection method according to claim 1, wherein "detecting the identification abnormal region in the screen image" specifically includes:
detecting the abnormal identification point class in the screen image.
3. The screen defect detection method according to claim 2, wherein the step of acquiring the screen image photographed by the 2D camera specifically comprises the steps of:
acquiring a first screen image shot by a 2D camera;
performing binarization processing on the first screen image, and dividing the first screen image into a white screen area and a black background area;
and extracting the part of the first screen image, which is positioned in the screen area, to obtain a second screen image.
4. The screen defect detection method according to claim 3, wherein "calculating the positional information of the abnormal region in the screen image" specifically includes:
and establishing a coordinate system in the range of the second screen image by taking a point in the second screen image as a coordinate origin, and obtaining pixel coordinates Dot (Dx, dy) of the position of the point type abnormality in the second screen image.
5. The method of claim 4, wherein calibrating the coordinate origin of the coordinate system and the field center of view of the 3D light field camera specifically comprises:
moving a screen, and placing pixel points corresponding to the coordinate origin in the field of view area of the 3D light field camera;
calculating a pixel difference between a coordinate origin and a 3D light field camera visual field central point, and multiplying the pixel difference by the pixel size of the 3D light field camera to obtain a first movement compensation value;
and according to the first movement compensation value, moving the screen, and calibrating the coordinate origin and the 3D light field camera visual field center.
6. The method of claim 4, wherein calculating a motion compensation value based on the abnormal region position coordinate information, moving a screen, and positioning the abnormal region at the center of the 3D light field camera field of view comprises:
multiplying the pixel coordinates by the pixel size of the 2D camera according to the pixel coordinates of the point type abnormality in the second screen image coordinate system to respectively obtain second movement compensation values in the X direction and the Y direction;
and moving the screen according to the movement compensation value, and placing the point type anomaly in the field center of view of the 3D light field camera.
7. The screen defect detection method according to claim 2, wherein "acquiring a 3D screen image captured by a 3D light field camera, calculating height position information of the abnormal region, judging a type of defect to which the abnormal region belongs, and judging whether a screen is qualified" specifically includes:
shooting to obtain a 3D image of the screen point type abnormal region;
calculating the distance between the point type anomaly and the reference layer;
and comparing the distance with a preset threshold value, and judging the bad type of the point type abnormality.
8. The screen defect detection method according to claim 7, wherein "calculate the distance of the point-like anomaly from a reference layer; the comparing the distance with the magnitude of the preset threshold value specifically comprises:
calculating the distance between the point type abnormality and the screen pixel layer;
when the distance is smaller than the surface layer height of the screen, judging that the point type abnormality is located in the screen;
and when the distance is larger than the height of the surface layer of the screen, judging that the point type abnormality is positioned on the surface of the screen.
9. A screen defect detection system, comprising:
the jig is used for placing a screen to be detected;
an image acquisition module comprising a 2D camera, a 3D light field camera and a matched light source device, configured to capture a screen image;
a host computer comprising a memory and a processor, the memory storing a computer program executable on the processor, the processor implementing the steps of the screen defect detection method of any one of claims 1-8 when the program is executed;
and the PLC is configured to control the movement of the jig and realize data transmission with the upper computer.
10. A computer storage medium, characterized in that a computer program is stored therein, and that the computer program, when run, causes a device in which the computer storage medium is located to perform the steps of the screen defect detection method according to any one of claims 1-8.
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| CN113567464B (en) * | 2021-06-16 | 2022-11-04 | 美晟通科技(苏州)有限公司 | Transparent medium stain position detection method and device |
| CN114152626B (en) * | 2022-02-07 | 2022-05-24 | 盛吉盛(宁波)半导体科技有限公司 | Method and device applied to defect height measurement |
| CN116013189B (en) * | 2022-09-26 | 2023-10-17 | 领先光学技术(江苏)有限公司 | Mini LED/Micro LED screen brightness correction method and device |
| CN115598136B (en) * | 2022-10-28 | 2023-08-08 | 深圳市元硕自动化科技有限公司 | Screen gluing quality detection device |
| CN115876086B (en) * | 2023-02-22 | 2023-05-30 | 广州思林杰科技股份有限公司 | Detection method and detection system for high-density connector |
| CN117218125B (en) * | 2023-11-09 | 2024-05-03 | 荣耀终端有限公司 | Display screen defect detection method, device, storage medium, device and system |
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