CN111551559A - LCD (liquid Crystal display) liquid crystal screen defect detection method based on multi-view vision system - Google Patents
LCD (liquid Crystal display) liquid crystal screen defect detection method based on multi-view vision system Download PDFInfo
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- 239000004973 liquid crystal related substance Substances 0.000 title claims abstract description 35
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- 238000007781 pre-processing Methods 0.000 claims abstract description 7
- 230000007246 mechanism Effects 0.000 claims description 19
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- 238000000034 method Methods 0.000 claims description 12
- 238000010191 image analysis Methods 0.000 claims description 4
- 238000001914 filtration Methods 0.000 claims description 3
- 238000007689 inspection Methods 0.000 claims 2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/36—Sorting apparatus characterised by the means used for distribution
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
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Abstract
The invention discloses a defect detection method of an LCD (liquid crystal display) liquid crystal screen based on a multi-view vision system, which comprises the following steps: s1, forming a multi-view vision system by adopting a plurality of cameras and setting parameters; s2, placing the LCD screen on a detection device and starting detection; s3, starting the multi-view vision system to shoot by the LCD screen in place; s4, preprocessing the image; s5, extracting image features; s6, performing 3D information matching according to the image characteristics; s7, judging whether the LCD screen has defects and performing classification analysis; s8, sorting the LCD screens; by repeating the steps from S2 to S8, batch detection of the LCD liquid crystal screens is realized. According to the invention, multi-angle image comparison analysis is realized by acquiring 2D images at different angles, 3D information such as depth information of a detected object is restored, the detection difficulty is greatly reduced, the interference of a surface protection film of a product and the internal real defect can be effectively distinguished, the misjudgment is reduced, the detection accuracy is improved, and the rework rate is effectively reduced.
Description
Technical Field
The invention relates to the technical field of visual inspection, in particular to a defect detection method for an LCD (liquid crystal display) liquid crystal screen based on a multi-view visual system.
Background
At present, the defect detection of the LCD liquid crystal screen in the LCD industry usually adopts a single area-array or line-scan camera to shoot, and then analyzes and detects the image shot by the camera, so as to determine whether the LCD liquid crystal screen has defects such as scratches, foreign matters, stains, and the like. However, the existing LCD liquid crystal panel defect detection method has the following problems:
1. if the shot object has a 3D scene with layers and surface boundaries, after the shot object is shot into a 2D image, the depth information of the object is lost, and the accuracy of the gray value in subsequent image analysis is seriously influenced;
2. if the interference of scratches, foreign matter adhesion and the like of a surface protective film of an LCD (liquid crystal display) screen is various, the shape is various and the background is complex, the characteristics of the defects are difficult to extract according to the 2D image losing the depth information, and the difficulty of defect detection and analysis is high;
3. the scratch and the foreign matter of the surface protection film outer surface of the LCD liquid crystal display do not belong to the defect, if the scratch and the foreign matter are not distinguished from the internal defect, misjudgment can be caused, the accuracy of defect detection is influenced, the passing rate of good products is reduced, and the rework rate is increased.
Accordingly, the prior art is deficient and needs improvement.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for detecting the defects of an LCD (liquid crystal display) based on a multi-view vision system.
The technical scheme of the invention is as follows:
a defect detection method for an LCD (liquid crystal display) liquid crystal screen based on a multi-view vision system comprises the following steps:
step S1, a multi-view vision system is formed by a plurality of cameras, and detection parameters are set; wherein one camera serves as a primary camera and the remaining cameras serve as secondary cameras;
step S2, placing the LCD liquid crystal screen to be detected on the detection equipment, and starting detection;
step S3, after the LCD screen is transferred in place, starting a multi-view vision system to shoot the LCD screen;
step S4, acquiring images shot by all cameras, and preprocessing each image, wherein the preprocessing comprises multiple types of contrast enhancement, denoising, filtering and image enhancement;
step S5, respectively extracting the characteristics of each preprocessed image, wherein the characteristics comprise point characteristics, line characteristics and area characteristics;
step S6, performing 3D information matching according to the characteristics of the image;
step S7, judging the defect condition of the LCD screen, and analyzing and processing the defect classification of the LCD screen;
step S8, sorting the LCD liquid crystal screen according to the defect analysis result;
the above-mentioned steps S2 to S8 are repeatedly circulated, and the LCD panels are inspected in batch.
Further, the multi-view vision system described in step S1 adopts a plurality of cameras to form the multi-view vision system, and the plurality of cameras are all connected to the computer through SDK interfaces for transmitting data.
Further, the setting of the detection parameters in step S1 includes calibrating the positions, heights, and distances of the plurality of cameras, and calibrating the included angle between each camera and the detection object.
Further, the detection device of step S2 includes a conveying mechanism, a grasping mechanism, and a positioning detection mechanism; the conveying mechanism consists of a conveying belt and a servo motor for driving the conveying belt to work and is used for transferring the LCD screen; the grabbing mechanism consists of a manipulator and a motor for driving the manipulator to work and is used for grabbing the LCD screen; the positioning detection mechanism is composed of a plurality of cameras and a light source and is used for positioning and shooting images of the LCD screen.
Further, the step S3 of starting the multi-view vision system to shoot the LCD screen is to shoot the LCD screen by using a plurality of cameras simultaneously.
Further, the manner of acquiring the images captured by all the cameras in step S4 is that the computer synchronously captures the images currently captured by the cameras through the SDK interfaces of all the cameras.
Further, step S5 uses an image algorithm to extract the features of each preprocessed image, so as to obtain the position of the desired target.
Further, the implementation of step S6 is realized by performing quality feature detection and fitting 3D information matching.
Further, step S7 determines whether the LCD panel has a defect through 2D image analysis and 3D information matching, wherein if no defect exists, it is determined that the current LCD panel is good, otherwise, it is further analyzed whether the defect is a real defect inside the LCD panel; if the parallax errors of the defects in the multiple images are different, the defects are scratches or foreign matters are attached to the surface protection film of the LCD screen, and the current LCD screen is judged to be a suspected defective product; otherwise, judging that the current LCD screen is a defective product.
Further, in step S8, the defect analysis result is outputted by the computer, and the detected LCD panel is sorted to a good product sorting location, a suspected defective product sorting location, or a defective product sorting location according to the defect analysis result by the computer-controlled manipulator and the conveyor belt.
By adopting the scheme, the invention has the following beneficial effects:
according to the invention, the product is shot synchronously by adopting a plurality of cameras, multi-angle image comparison analysis is realized by acquiring 2D images at different angles, 3D information such as depth information of a detected object is restored, the detection difficulty is reduced, the surface protection film interference and the internal real defect of the product can be effectively distinguished, the misjudgment is reduced, the detection accuracy is improved, and the rework rate is effectively reduced.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a flow chart of the steps of the method for detecting the defects of the LCD liquid crystal screen based on the multi-view vision system according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The invention is described in detail below with reference to the figures and the specific embodiments.
Referring to fig. 1, the present invention provides a defect detection method for an LCD liquid crystal display based on a multi-view vision system, comprising the following steps:
step S1, calibrating the positions, heights and distances of a plurality of cameras, and calibrating the included angle between each camera and the detected object;
the system comprises a multi-view vision system, a camera module and a display module, wherein the multi-view vision system is formed by a plurality of cameras, one camera is used as a main camera to shoot front images, and the rest cameras are used as auxiliary cameras to shoot side images;
step S2, placing the LCD liquid crystal screen to be detected on the detection equipment, and starting detection;
the detection equipment comprises a conveying mechanism, a grabbing mechanism and a positioning detection mechanism; the conveying mechanism consists of a conveying belt and a servo motor for driving the conveying belt to work and is used for transferring the LCD screen; the grabbing mechanism consists of a manipulator and a linear motor for driving the manipulator to work and is used for grabbing the LCD screen; the positioning detection mechanism consists of a plurality of cameras and light sources, and the positions corresponding to the cameras and the light sources form shooting positions together for positioning and shooting images of the LCD screen;
step S3, after the LCD screen is transferred in place, starting a multi-view vision system to shoot the LCD screen;
the LCD screen is transferred in place, namely the LCD screen to be detected is placed on a conveyor belt, the conveyor belt is driven to transfer the LCD screen to a station corresponding to the positioning detection mechanism through the action of a servo motor, and then the manipulator is driven to grab and position the LCD screen to a shooting position formed by a camera and a light source through the action of a linear motor;
step S4, acquiring images shot by all cameras, and preprocessing each image, wherein the preprocessing comprises multiple types of contrast enhancement, denoising, filtering and image enhancement;
step S5, respectively extracting the characteristics of each preprocessed image, wherein the characteristics comprise point characteristics, line characteristics and area characteristics;
step S6, performing 3D information matching according to the characteristics of the image;
step S7, judging the defect condition of the LCD screen, and analyzing and processing the defect classification of the LCD screen;
step S8, sorting the LCD liquid crystal screen according to the defect analysis result;
the above-mentioned steps S2 to S8 are repeatedly circulated, and the LCD panels are inspected in batch.
As a preferred embodiment, the binocular vision system is formed by two cameras, specifically, the two cameras are high-definition cameras, and both the two cameras are connected to a computer through an SDK interface for data transmission.
In this embodiment, the step S3 of starting the multi-view vision system to shoot the LCD screen is to shoot the LCD screen by using two cameras at the same time.
In this embodiment, the manner of acquiring the images captured by all the cameras in step S4 is that the computer synchronously captures the images currently captured by the cameras through the SDK interfaces of all the cameras.
In this embodiment, step S5 employs the algorithm including the Faster R-CNN to extract the features of each preprocessed image, respectively, so as to obtain the position of the desired target.
In this embodiment, step S6 uses the HOG features to perform quality feature detection, and uses the K-nearest neighbor method to calculate the orientation and perform least square plane fitting to implement 3D information matching.
In this embodiment, step S7 determines whether the LCD panel has a defect through 2D image analysis and 3D information matching, where if no defect exists, it is determined that the current LCD panel is good, otherwise, it is further analyzed whether the defect is a real defect inside the LCD panel; further, if the parallax difference of the defect in the two images is different, the defect is that the surface protective film of the LCD screen is scratched or foreign matters are attached, and the current LCD screen is judged to be a suspected defective product; otherwise, judging that the current LCD screen is a defective product.
In this embodiment, in step S8, the defect analysis result is outputted by the computer, and the detected LCD panel is sorted to a good product sorting location, a suspected defective product sorting location, or a defective product sorting location according to the defect analysis result by the computer-controlled manipulator and the conveyor belt.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, the product is shot synchronously by adopting a plurality of cameras, multi-angle image comparison analysis is realized by acquiring 2D images at different angles, 3D information such as depth information of a detected object is restored, the detection difficulty is reduced, the surface protection film interference and the internal real defect of the product can be effectively distinguished, the misjudgment is reduced, the detection accuracy is improved, and the rework rate is effectively reduced.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A defect detection method for an LCD (liquid crystal display) based on a multi-view vision system is characterized by comprising the following steps:
step S1, a multi-view vision system is formed by a plurality of cameras, and detection parameters are set; wherein one camera serves as a primary camera and the remaining cameras serve as secondary cameras;
step S2, placing the LCD liquid crystal screen to be detected on the detection equipment, and starting detection;
step S3, after the LCD screen is transferred in place, starting a multi-view vision system to shoot the LCD screen;
step S4, acquiring images shot by all cameras, and preprocessing each image, wherein the preprocessing comprises multiple types of contrast enhancement, denoising, filtering and image enhancement;
step S5, respectively extracting the characteristics of each preprocessed image, wherein the characteristics comprise point characteristics, line characteristics and area characteristics;
step S6, performing 3D information matching according to the characteristics of the image;
step S7, judging the defect condition of the LCD screen, and analyzing and processing the defect classification of the LCD screen;
and step S8, sorting the LCD liquid crystal screen according to the defect analysis result.
2. The method for detecting the defects of the LCD based on the multi-view vision system as claimed in claim 1, wherein the multi-view vision system of step S1 adopts a plurality of cameras to form the multi-view vision system, and the plurality of cameras are connected with the computer through SDK interfaces for transmitting data.
3. The method as claimed in claim 1, wherein the setting of the inspection parameters in step S1 includes calibrating the position, height and distance of the cameras, and calibrating the included angle between each camera and the inspection object.
4. The method for detecting the defects of the LCD liquid crystal screen based on the multi-view vision system as claimed in claim 2, wherein the detection device of step S2 comprises a conveying mechanism, a grabbing mechanism and a positioning detection mechanism; the conveying mechanism consists of a conveying belt and a servo motor for driving the conveying belt to work and is used for transferring the LCD screen; the grabbing mechanism consists of a manipulator and a motor for driving the manipulator to work and is used for grabbing the LCD screen; the positioning detection mechanism is composed of a plurality of cameras and a light source and is used for positioning and shooting images of the LCD screen.
5. The method for detecting the defects of the LCD liquid crystal screen based on the multi-vision system as claimed in claim 1, wherein the step S3 of starting the multi-vision system to shoot the LCD liquid crystal screen is to shoot the LCD liquid crystal screen by using a plurality of cameras simultaneously.
6. The method for detecting defects of LCD based on multi-view vision system as claimed in claim 2, wherein the manner of acquiring the images taken by all the cameras in step S4 is that the computer synchronously captures the images currently taken by the cameras through the SDK interfaces of all the cameras.
7. The method for detecting defects of LCD based on multi-vision system as claimed in claim 1, wherein step S5 employs image algorithm to extract the features of each preprocessed image respectively, so as to obtain the position of the desired target.
8. The method for detecting the defects of the LCD liquid crystal display based on the multi-vision system as claimed in claim 1, wherein the step S6 is implemented by performing quality feature detection and fitting 3D information matching.
9. The method for detecting the defects of the LCD liquid crystal screen based on the multi-view vision system as claimed in claim 1, wherein the step S7 is used for judging whether the LCD liquid crystal screen has defects through 2D image analysis and 3D information matching, wherein if the defects do not exist, the current LCD liquid crystal screen is judged to be good, otherwise, whether the defects are real defects inside the LCD liquid crystal screen is further analyzed; further, if the parallax errors of the defects in the multiple images are different, the defects are scratches or foreign matters are attached to the surface protection film of the LCD screen, and the current LCD screen is judged to be a suspected defective product; otherwise, judging that the current LCD screen is a defective product.
10. The method as claimed in claim 4, wherein the step S8 is to output the defect analysis result by the computer, and then to sort the detected LCD screen to a good product sorting location, a suspected defective product sorting location or a defective product sorting location according to the defect analysis result by the computer-controlled manipulator and the conveyor belt.
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Cited By (5)
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| CN112881430A (en) * | 2021-03-10 | 2021-06-01 | 深圳汇义科技有限公司 | Display screen defect monitoring system based on image recognition and detection method thereof |
| CN113686873A (en) * | 2021-08-10 | 2021-11-23 | 广东省威汇智能科技有限公司 | Vehicle-mounted multi-connected screen based testing device and method |
| CN116165216A (en) * | 2023-03-16 | 2023-05-26 | 苏州鼎纳自动化技术有限公司 | Liquid crystal display micro scratch flaw 3D detection method, system and computing equipment |
| CN116500058A (en) * | 2023-06-28 | 2023-07-28 | 信丰云创(深圳)信息有限公司 | Display screen detection system and display screen detection method |
| CN117092116A (en) * | 2023-10-20 | 2023-11-21 | 上海嘉朗实业南通智能科技有限公司 | Automobile aluminum alloy casting defect detection system and method based on machine vision |
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Application publication date: 20200818 |
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