CN113269762A - 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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- 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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- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- 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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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T2207/10004—Still image; Photographic image
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Abstract
The invention provides a method and a system for detecting screen defects and a computer storage medium, wherein the method comprises the following steps: acquiring a screen image shot by a 2D camera; detecting and identifying abnormal areas in the screen image, establishing a coordinate system, and calculating position coordinate information of the abnormal areas in the screen image; moving the screen, and calibrating a coordinate origin point of the coordinate system and a view center of the 3D light field camera; calculating a movement compensation value according to the position coordinate information of the abnormal area, moving the screen, and placing the abnormal area in the view center 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 area, judging the bad type of the abnormal area, and judging whether the screen is qualified. By means of multiple progressive movements, high-precision position conversion of abnormal points in the screen between the 2D camera station and the 3D camera station is achieved, 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 defects and a computer storage medium.
Background
The screen has many kinds of bad points in the process of making conventional 2D AOI detection, it may be the pixel defect, it also may be the dust, when the dust is located the screen surface, then the screen is qualified product, and when the dust is located below the screen surface layer, then the screen is unqualified product, and traditional 2D camera can only judge position and size to dust or pixel is bad, can't judge which layer it specifically is located. In order to solve the above problems, a step-by-step shooting method combining a plurality of cameras is proposed in the prior art to judge the defect level, but the 3D camera has a small shooting view, and in order to improve the recognition accuracy, the precision of the product conversion between the 2D camera station and the 3D camera station needs to be further improved.
Disclosure of Invention
The invention aims to provide a screen defect detection method, a system and a computer storage medium.
The invention provides a method for detecting screen defects, which comprises the following steps:
acquiring a screen image shot by a 2D camera;
detecting and identifying abnormal areas in the screen image, establishing a coordinate system, and calculating position coordinate information of the abnormal areas in the screen image;
moving the screen, and calibrating the coordinate origin of the coordinate system and the view center of the 3D light field camera;
calculating a movement compensation value according to the position coordinate information of the abnormal area, moving a screen, and placing the abnormal area in the center of the visual field of the 3D light field camera;
and acquiring a 3D screen image shot by a 3D light field camera, calculating height position information of the abnormal area, judging the bad type of the abnormal area, and judging whether the screen is qualified.
As a further improvement of the present invention, "detecting and identifying an abnormal region in the screen image" specifically includes:
and detecting the abnormality of the identification point class in the screen image.
As a further improvement of the present invention, "acquiring a screen image taken 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 a 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 position 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 one point in the second screen image as a coordinate origin to obtain a pixel coordinate Dot (Dx, Dy) of the position of the point type anomaly in the second screen image.
As a further improvement of the present invention, "calibrating the coordinate origin of the coordinate system with the center of the field of view of the 3D light field camera" specifically includes:
moving a screen, and placing pixel points of the screen corresponding to the origin of coordinates in a visual field area of the 3D light field camera;
calculating a pixel difference between a coordinate origin and a visual field central point of the 3D light field camera, and multiplying the pixel difference by the pixel size of the 3D light field camera to obtain a first motion compensation value;
and moving the screen according to the first movement compensation value, and calibrating the coordinate origin and the view center of the 3D light field camera.
As a further improvement of the present invention, "calculating a motion compensation value according to the position coordinate information of the abnormal region, moving the screen, and positioning the abnormal region at the center of the field of view of the 3D light field camera" specifically includes:
multiplying the pixel coordinate by the pixel size of the 2D camera according to the pixel coordinate of the point type abnormity 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 motion compensation value, and placing the point-like abnormity in the center of the field 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, determining a bad type to which the abnormal region belongs, and determining whether the screen is qualified" specifically includes:
shooting to obtain a 3D image of the screen point type abnormal area;
calculating the distance between the point type abnormity and a reference layer;
and comparing the distance with a preset threshold value, and judging the bad type of the point type abnormity.
As a further improvement of the present invention, "calculating a distance of the point-like anomaly from a reference layer; comparing the distance with a preset threshold specifically comprises:
calculating the distance between the point type abnormity and a screen pixel layer;
when the distance is smaller than the height of the surface layer of the screen, judging that the point type abnormity is positioned in the screen;
and when the distance is larger than the height of the surface layer of the screen, judging that the point type abnormity is positioned on the surface of the screen.
The invention also provides a system for detecting screen defects, which comprises:
the jig is used for placing the screen to be detected;
an image acquisition module comprising a 2D camera, a 3D light field camera, and a mating light source device configured to capture 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 implements the step of the screen defect detection method when executing the program;
and the PLC is configured for controlling the jig to move and realizing data transmission with the upper computer.
The invention also provides a computer storage medium, wherein a computer program is stored in the computer storage medium, and when the computer program runs, the equipment of the computer storage medium executes the steps of the screen defect detection method.
The invention has the beneficial effects that: according to the method provided by the invention, 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 multiple progressive movements, the influence of movement precision errors is reduced, and the abnormal points of the screen are ensured to be positioned in the shooting visual field of the 3D light field camera after station conversion, so that the hierarchical identification of the abnormal points of the screen is completed, the bad types of the abnormal points are judged, and the identification precision is improved.
Drawings
Fig. 1 is a flow chart illustrating a method for detecting a screen defect according to an embodiment of the invention.
Fig. 2 to 4 are schematic images related to steps of a screen defect detection method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clear, the technical solutions of the present application will be clearly and completely described below with reference to the detailed description of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art without any inventive work based on the embodiments in the present application are within the scope of protection of the present application.
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
For convenience in explanation, the description herein uses terms indicating relative spatial positions, such as "upper," "lower," "rear," "front," and the like, to describe one element or feature's relationship to another element or feature as illustrated in the figures. The term spatially relative position may encompass different orientations of the device in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements described as "below" or "above" other elements or features would then be oriented "below" or "above" 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 a screen defect, which is used to detect and determine a position of a defect in a screen, so as to distinguish whether the defect belongs to an upper-surface defect or a lower-surface defect, in this embodiment, taking a mobile phone screen as an example, the method for detecting a screen defect includes the steps of:
s1: a first screen image captured by a 2D camera is acquired.
Specifically, step S1 includes the following steps:
s11: and detecting that the position of the jig for placing the mobile phone and the position of the 2D camera are positioned on the same vertical line, 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 or the like, which has a large shooting view, but cannot identify a hierarchical region where a defective point is located in an image shot by the industrial CCD camera, and the industrial CCD camera usually shoots a gray image, and if the industrial CCD camera is a color camera, after shooting an image of an open-ring workpiece, the method further includes the steps of: and carrying out gray processing on the opening circular ring workpiece image.
Illustratively, as shown in fig. 2, the first screen image is obtained by shooting, wherein the lighted screen area is usually white or light gray with a larger gray value, and the background part such as a jig is usually black or dark gray with a smaller gray value.
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 subjected to binarization processing and is divided into a white screen area and a black background area.
S14: and extracting a part positioned in the screen area in the first screen image to obtain a second screen image.
Specifically, a preset pixel gray value is set as a threshold, or the threshold is calculated through a current common algorithm, the gray value of a pixel point in the first screen image is set to be 255 when the gray value is larger than the threshold, and is set to be 0 when the gray value is smaller than the threshold. 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 the subsequent detection and identification precision is improved.
Illustratively, as shown in fig. 3, a partial enlarged view of the second screen image extracted in the first screen image is shown.
S2: and detecting and identifying abnormal areas in the screen image, establishing a coordinate system, and calculating the position coordinate information of the abnormal areas in the screen image.
For example, in this embodiment, the detection method is used to identify point anomalies, and according to actual needs, the size of a point anomaly may be defined as being smaller than one pixel point or several pixel points, which may be a screen pixel defect or dust, and when the point anomaly is a screen pixel defect or dust in a screen, the product is an unqualified product, and when the point anomaly is dust on a surface of the screen, the product is a qualified product. The point type abnormity 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 abnormal area in the image is obviously different from the gray value of the normal screen area, and the area with the gray value obviously different from the surrounding area in the second image is identified, namely the point abnormal area can be identified in the second screen image.
Illustratively, as shown in the white circle box of FIG. 3, is a point-like anomaly.
After the point anomaly is detected and identified, a coordinate system is established in the range of the second screen image by taking one point in the second screen image as a coordinate origin, and then the pixel coordinate Dot (Dx, Dy) of the position of the point anomaly in the second screen image can be calculated.
S3: and moving the screen, and calibrating the coordinate origin of the coordinate system and the view 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 a lens are split once, 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, the 3D light field camera has high precision, the visual field is small, and the whole screen is difficult to shoot.
Specifically, step S3 includes the steps of:
s31: and moving the screen, and placing pixel points corresponding to the coordinate origin in the center of the field of view of the 3D light field camera.
Carry out the first time earlier and remove, will place the tool of cell-phone and shoot the field of vision within range to 3D light field camera and remove, because the fixed position of initial of coordinates point definition at the screen usually, consequently accomplish the 2D camera and shoot the back, can follow fixed path with the tool and move to 3D light field camera in the field of vision, through the first time removal that the precision is lower, move the cell-phone from 2D camera station to 3D light field camera station.
S32: and calculating a pixel difference between the coordinate origin and the center point of the 3D light field camera view, and multiplying the pixel difference by the pixel size of the 3D light field camera to obtain a first movement compensation value, so that the conversion of the pixel coordinate and the world coordinate is completed, wherein the first movement compensation value is that the coordinate origin is moved to the distance which is actually required to be moved by the center of the 3D light field camera view.
S33: and according to the first motion compensation value, moving the screen, and calibrating the coordinate origin and the view center of the 3D light field camera.
Through steps S32 and S33, a second movement is performed to calibrate the coordinate origin with the center of the field of view of the 3D light field camera, and since the accuracy of the first movement is low, error compensation is performed using the second movement and preparation is made for a third movement.
In summary, in step S3, a high precision calibration of the origin of coordinates and the center of the field of view of the 3D light field camera is achieved by the first and second movements.
S4: and calculating a movement compensation value according to the position coordinate information of the abnormal area, moving the screen, and placing the abnormal area in the center of the visual field 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 anomaly obtained in step S2, the pixel coordinates are multiplied by the pixel size of the 2D camera to obtain second motion compensation values in the X direction and the Y direction, respectively, so as to complete the conversion between the pixel coordinates and the world coordinates, where the second motion compensation value is the actual distance between the screen pixel point corresponding to the origin of the coordinates and the point anomaly.
S42: and moving the screen according to the motion compensation value, and placing the point type abnormity in the center of the field of view of the 3D light field camera.
Thus, in step S4, the third movement positions the point-like anomaly at the center of the field of view of the 3D light field camera, thereby ensuring that the 3D picture taken by the 3D light field camera contains information about the point-like anomaly.
In summary, through the steps S3 and S4, by using three times of progressive movement, high-precision position conversion of the abnormal point in the screen between the 2D camera station and the 3D camera station is realized, the influence of movement precision errors is reduced, and it is ensured that the abnormal point in the screen is located in the shooting field of view of the 3D light field camera after station conversion, thereby completing hierarchical identification of the abnormal point in the screen, determining a bad type of the abnormal point, and improving the identification precision.
S5: acquiring a 3D screen image shot by a 3D light field camera, calculating height position information of an abnormal area, judging the bad type of the abnormal area, and judging whether the screen is qualified.
Specifically, step S5 includes:
s51: and shooting to obtain a 3D image of the abnormal area of the screen point class.
Illustratively, as shown in fig. 4, a 3D image of a screen displayed at an angle is taken by a 3D light field camera.
S52: and calculating the distance between the point class abnormity and the reference layer.
For example, in the present embodiment, the distance between the point-like 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, other layers with relatively fixed height positions may be selected as the reference layer according to the detection object.
S53: and comparing the distance with a preset threshold value, and judging the bad type of the point type abnormity.
For example, in the present embodiment, when the distance is smaller than the height of the screen surface layer, that is, the point-like anomaly is located between the pixel layer and the screen surface layer, the point-like anomaly is determined to be located inside the screen, and the product is an unqualified product for a bad defect affecting the quality of the product; when the distance is larger than the height of the surface layer of the screen, judging that the point type abnormity is positioned on the surface of the screen, and the surface layer is erasable dust, and the product is a qualified product. In some other embodiments of the present invention, layers with other height values may also be selected as the preset threshold according to different detection objects and considering factors such as product dimensional tolerance.
The invention also provides a system for detecting screen defects, which comprises: tool, image acquisition module, host computer and PLC controller.
The jig is used for placing a screen to be detected and 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 for shooting 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 executes the program to realize the steps of the screen defect detection method.
The PLC is configured to control the jig to move and realize data transmission with the upper computer.
The invention also provides a computer storage medium, wherein a computer program is stored in the computer storage medium, and when the computer program runs, the equipment of the computer storage medium executes the steps of the screen defect detection method.
It should be understood that although the present description refers to embodiments, not every embodiment contains only a single technical solution, and such description is for clarity only, and those skilled in the art should make the description as a whole, and the technical solutions in the embodiments can also be combined appropriately to form other embodiments understood by those skilled in the art.
The above-listed detailed description is only a specific description of a possible embodiment of the present invention and is not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention are included in the scope of the present invention.
Claims (10)
1. A screen defect detection method is characterized by comprising the following steps:
acquiring a screen image shot by a 2D camera;
detecting and identifying abnormal areas in the screen image, establishing a coordinate system, and calculating position coordinate information of the abnormal areas in the screen image;
moving the screen, and calibrating the coordinate origin of the coordinate system and the view center of the 3D light field camera;
calculating a movement compensation value according to the position coordinate information of the abnormal area, moving a screen, and placing the abnormal area in the center of the visual field of the 3D light field camera;
and acquiring a 3D screen image shot by a 3D light field camera, calculating height position information of the abnormal area, judging the bad type of the abnormal area, and judging whether the screen is qualified.
2. The method for detecting the screen defect according to claim 1, wherein the detecting and identifying the abnormal area in the screen image specifically comprises:
and detecting the abnormality of the identification point class in the screen image.
3. The method for detecting the screen defect according to claim 2, wherein the step of acquiring the screen image shot by the 2D camera comprises the following steps:
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 a part of the first screen image, which is positioned in the screen area, to obtain a second screen image.
4. The method for detecting the screen defect according to claim 3, wherein the step of calculating the position information of the abnormal area in the screen image specifically comprises the steps of:
and establishing a coordinate system in the range of the second screen image by taking one point in the second screen image as a coordinate origin to obtain a pixel coordinate Dot (Dx, Dy) of the position of the point type anomaly in the second screen image.
5. The method for detecting the screen defect according to claim 4, wherein the step of calibrating the coordinate origin of the coordinate system and the center of the field of view of the 3D light field camera specifically comprises the steps of:
moving a screen, and placing pixel points of the screen corresponding to the origin of coordinates in a visual field area of the 3D light field camera;
calculating a pixel difference between a coordinate origin and a visual field central point of the 3D light field camera, and multiplying the pixel difference by the pixel size of the 3D light field camera to obtain a first motion compensation value;
and moving the screen according to the first movement compensation value, and calibrating the coordinate origin and the view center of the 3D light field camera.
6. The method for detecting the screen defect according to claim 4, wherein the step of calculating a motion compensation value according to the position coordinate information of the abnormal region, moving the screen, and placing the abnormal region in the center of the field of view of the 3D light field camera specifically comprises the steps of:
multiplying the pixel coordinate by the pixel size of the 2D camera according to the pixel coordinate of the point type abnormity 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 motion compensation value, and placing the point-like abnormity in the center of the field of view of the 3D light field camera.
7. The method for detecting the screen defect according to claim 2, wherein the steps of acquiring a 3D screen image shot by a 3D light field camera, calculating height position information of the abnormal area, judging the defect type of the abnormal area, and judging whether the screen is qualified specifically comprise:
shooting to obtain a 3D image of the screen point type abnormal area;
calculating the distance between the point type abnormity and a reference layer;
and comparing the distance with a preset threshold value, and judging the bad type of the point type abnormity.
8. The method for detecting screen failure according to claim 7, wherein the distance between the point-like anomaly and a reference layer is calculated; comparing the distance with a preset threshold specifically comprises:
calculating the distance between the point type abnormity and a screen pixel layer;
when the distance is smaller than the height of the surface layer of the screen, judging that the point type abnormity is positioned in the screen;
and when the distance is larger than the height of the surface layer of the screen, judging that the point type abnormity is positioned on the surface of the screen.
9. A screen defect detection system, comprising:
the jig is used for placing the screen to be detected;
an image acquisition module comprising a 2D camera, a 3D light field camera, and a mating light source device configured to capture screen images;
an upper computer, which comprises a memory and a processor, wherein the memory stores a computer program capable of running on the processor, and the processor executes the program to realize the steps of the screen defect detection method according to any one of claims 1 to 8;
and the PLC is configured for controlling the jig to move and realizing data transmission with the upper computer.
10. A computer storage medium having a computer program stored therein, wherein the computer program when executed causes an apparatus of the computer storage medium to perform the steps of the screen defect detection method according to any one of claims 1 to 8.
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