CN111583137A - Electronic screen color spot detection device and method based on machine vision technology - Google Patents
Electronic screen color spot detection device and method based on machine vision technology Download PDFInfo
- Publication number
- CN111583137A CN111583137A CN202010338789.7A CN202010338789A CN111583137A CN 111583137 A CN111583137 A CN 111583137A CN 202010338789 A CN202010338789 A CN 202010338789A CN 111583137 A CN111583137 A CN 111583137A
- Authority
- CN
- China
- Prior art keywords
- image
- electronic screen
- detection
- electronic
- screen
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 65
- 238000000034 method Methods 0.000 title claims abstract description 46
- 238000005516 engineering process Methods 0.000 title claims abstract description 16
- 230000007547 defect Effects 0.000 claims abstract description 55
- 238000001914 filtration Methods 0.000 claims abstract description 30
- 238000007781 pre-processing Methods 0.000 claims abstract description 26
- 239000000428 dust Substances 0.000 claims description 16
- 238000003709 image segmentation Methods 0.000 claims description 8
- 238000004891 communication Methods 0.000 claims description 7
- 239000000284 extract Substances 0.000 claims description 5
- 238000000605 extraction Methods 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 3
- 238000003708 edge detection Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 11
- 238000009776 industrial production Methods 0.000 abstract description 4
- 230000011218 segmentation Effects 0.000 abstract description 3
- 230000009286 beneficial effect Effects 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
Classifications
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- G—PHYSICS
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
-
- 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
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
- G06T2207/20032—Median filtering
-
- 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
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Quality & Reliability (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses an electronic screen color spot detection device and method based on a machine vision technology, which can be used for carrying out image acquisition and preprocessing on an electronic screen based on the machine vision technology so as to analyze and feed back the defects of the electronic screen, and is high in detection efficiency, stable in detection accuracy, low in detection cost and suitable for large-scale detection requirements of industrial production. In order to improve the accuracy of the algorithm, median filtering in different directions is respectively selected to finish the combined filtering processing of the image; then, the characteristics that the brightness of the combined filtered image and the Gaussian mean filtered image is uniform but the gray level of the defect area is obviously different are fully utilized, the parts of the given template area with the average gray level difference value larger than the standard value are respectively extracted, and the result is comprehensively processed to complete the primary segmentation of the image.
Description
Technical Field
The invention relates to the technical field of electronic screen detection, in particular to an electronic screen color spot detection device and method based on a machine vision technology.
Background
In the production process of electronic products, strict defect detection is required to ensure the production quality. The detection of current electronic screen defect mainly relies on traditional artifical viewing to go on, detects the restriction that the main part received subjective and objective aspect defect, and this kind of detection means not only appears lou examining, the false retrieval scheduling problem easily, and reliability and stability are difficult to guarantee, and detection efficiency is not high moreover, the real-time is poor, and the cost that detects the needs is also very high. For the mass industrial production today, the manual inspection method cannot meet the requirement of the industrial production, so that the research of a suitable electronic screen defect detection system to realize the automatic online real-time detection of the electronic screen defects becomes an urgent requirement in the field of the current electronic product production.
Disclosure of Invention
Aiming at the defects in the technology, the invention provides an electronic screen color spot detection device and method based on a machine vision technology.
The technical scheme adopted by the invention for solving the technical problems is as follows:
an electronic screen color spot detection device based on machine vision technology comprises:
the image acquisition module is used for acquiring an image of the electronic screen to be detected;
the image preprocessing module is in communication connection with the image acquisition module and is used for preprocessing the acquired image;
the defect classification detection module is in communication connection with the image preprocessing module and is used for carrying out color spot detection on the preprocessed image; and
and the electronic screen defect detection system is communicated with the defect classification detection module and is used for displaying a color spot detection result.
Preferably, the image acquisition module is a CCD industrial camera.
Preferably, the environment of image acquisition is: the collection environment is a dark room, and the electronic screen is a state that the screen is lighted without displaying any pattern.
The method for detecting the color spots of the electronic screen by adopting the electronic screen color spot detection device based on the machine vision technology comprises the following steps:
the method comprises the following steps that firstly, an image acquisition module is adopted to acquire an image of an electronic screen to be detected;
secondly, preprocessing the acquired image by adopting the image preprocessing module;
thirdly, respectively designing an algorithm to detect the defects by adopting the defect classification detection module according to respective characteristics of the screen defects;
and fourthly, designing a user interface of the electronic screen defect detection system by using an interface editing tool of Matlab and displaying a color spot detection result.
Preferably, the image acquisition process is as follows: fixing two ends of the electronic product by using a clamp fixed on the measuring table to keep the electronic product horizontal, photographing the electronic screen in a lighting state along the vertical direction by using a camera, digitizing the acquired image of the electronic product and transmitting the digitized image to related software of a computer for next image preprocessing.
Preferably, the image preprocessing process in the step two is as follows: firstly, binarization and edge detection are carried out to determine the position of an electronic screen area, secondly, geometric correction is adopted to keep the target area horizontal, which is beneficial to carrying out target extraction operation, and finally, color space conversion is carried out to improve the contrast ratio between the screen defect and the periphery, so that the defect detection is carried out later.
Preferably, the image preprocessing process in the second step includes a dust removal process, an image filtering process, and an image segmentation process.
Preferably, the dust removal treatment is: the method comprises the steps of firstly turning on a system light source, collecting an image, then solving the position and the area of dust, and finally, carrying out combined comparison on a dust area and a defect area to eliminate the influence of the dust on an image detection result.
Preferably, the image filtering process is a combined filtering process, that is, a gaussian filtered image is used as an initial image of mean filtering to reduce the influence of texture and brightness unevenness, and then the combined filtering process is completed by using median filtering. Compared with a single filtering mode, the image background after combined filtering is more uniform, and the subsequent image segmentation is facilitated.
Preferably, the image segmentation processing is: firstly, dividing a local threshold to preliminarily extract defects, then judging whether the defects are reasonable or not through local contrast, and finally extracting the defects.
Compared with the prior art, the invention has the beneficial effects that: the device and the method for detecting the color spots on the electronic screen based on the machine vision technology can acquire and preprocess the image of the electronic screen based on the machine vision technology, further analyze the defects of the electronic screen and feed back the defects, have high detection efficiency, stable detection accuracy and low detection cost, and are suitable for large-scale detection requirements of industrial production. In order to improve the accuracy of the algorithm, median filtering in different directions is respectively selected to finish the combined filtering processing of the image; then, the characteristics that the brightness of the combined filtered image and the Gaussian mean filtered image is uniform but the gray level of the defect area is obviously different are fully utilized, the parts of the given template area with the average gray level difference value larger than the standard value are respectively extracted, and the result is comprehensively processed to complete the primary segmentation of the image.
Detailed Description
The present invention is described in further detail below to enable those skilled in the art to practice the invention with reference to the description.
The invention provides an electronic screen color spot detection device based on a machine vision technology, which comprises:
the image acquisition module is used for acquiring an image of the electronic screen to be detected;
the image preprocessing module is in communication connection with the image acquisition module and is used for preprocessing the acquired image;
the defect classification detection module is in communication connection with the image preprocessing module and is used for carrying out color spot detection on the preprocessed image; and
and the electronic screen defect detection system is communicated with the defect classification detection module and is used for displaying a color spot detection result.
As an embodiment of the present invention, the image capturing module is a CCD industrial camera.
As an embodiment of the present invention, the environment of image acquisition is: the collection environment is a dark room, and the electronic screen is a state that the screen is lighted without displaying any pattern.
As an embodiment of the present invention, the present invention further provides an electronic screen color spot detection method based on a machine vision technology, including the following steps:
the method comprises the following steps that firstly, an image acquisition module is adopted to acquire an image of an electronic screen to be detected;
secondly, preprocessing the acquired image by adopting the image preprocessing module;
thirdly, respectively designing an algorithm to detect the defects by adopting the defect classification detection module according to respective characteristics of the screen defects;
and fourthly, designing a user interface of the electronic screen defect detection system by using an interface editing tool of Matlab and displaying a color spot detection result.
As an embodiment of the present invention, the image acquisition process includes: the method comprises the steps of fixing two ends of an electronic product (such as a mobile phone, a watch, a tablet personal computer and the like) by using a clamp fixed on a measuring table, keeping the electronic product horizontal, photographing an electronic screen in a lighting state along the vertical direction by using a camera, digitizing an acquired image of the electronic product, and transmitting the digitized image to relevant software of a computer for next image preprocessing.
As an embodiment of the invention, the acquired electronic screen image must be preprocessed before the defect detection, so that the interference of irrelevant factors during the screen defect detection is reduced, and the detection efficiency of the algorithm is improved.
The image preprocessing process in the second step is as follows: firstly, binarization and edge detection are carried out to determine the position of an electronic screen area, secondly, geometric correction is adopted to keep the target area horizontal, which is beneficial to carrying out target extraction operation, and finally, color space conversion is carried out to improve the contrast ratio between the screen defect and the periphery, so that the defect detection is carried out later. Through the preprocessing operation, the target area to be detected is successfully extracted, an electronic screen image is obtained, and the detection efficiency of the algorithm is greatly improved.
As an embodiment of the present invention, the color spot is a pixel region having a color different from that of the surrounding area, which is formed by a damaged flat cable connecting the electronic screen and the main board or an abnormal operation unit.
And the image preprocessing process in the second step comprises dust removal processing, image filtering processing and image segmentation processing.
As an embodiment of the invention, in an actual working environment, dust inevitably exists on an electronic screen, so that the accuracy of a detection result is influenced.
The dust removal treatment comprises the following steps: the method comprises the steps of firstly turning on a system light source, collecting an image, then solving the position and the area of dust, and finally, carrying out combined comparison on a dust area and a defect area to eliminate the influence of the dust on an image detection result.
As an embodiment of the present invention, the present invention provides a combined filtering method for the characteristics of low contrast, blurred edge, and susceptibility to uneven texture and background brightness of block defects.
The image filtering processing is combined filtering processing, namely, a Gaussian filtered image is used as an initial image of mean filtering to reduce the influence of uneven texture and brightness, and then the median filtering is used for completing the combined filtering processing of the image. Compared with a single filtering mode, the image background after combined filtering is more uniform, and the subsequent image segmentation is facilitated.
As an embodiment of the present invention, the image segmentation process includes: firstly, dividing a local threshold to preliminarily extract defects, then judging whether the defects are reasonable or not through local contrast, and finally extracting the defects.
In order to improve the accuracy of the algorithm, median filtering in different directions is respectively selected to complete the combined filtering processing of the image. Then, the characteristics that the brightness of the combined filtered image and the Gaussian mean filtered image is uniform but the gray level of the defect area is obviously different are fully utilized, the parts of the given template area with the average gray level difference value larger than the standard value are respectively extracted, and the result is comprehensively processed to complete the primary segmentation of the image.
The algorithm utilizes the processing results of the same image in different filtering modes, and compared with a common defect detection algorithm based on image registration and standard template difference, the algorithm omits the template establishment and registration process, saves a large amount of time and storage space, simultaneously avoids misdetection caused by inaccurate matching and then extracts the area, combines the morphological principle to obtain the peripheral area, then respectively calculates the average gray scale of the two areas on the original image, and similarly extracts the part of which the average gray scale difference is larger than the standard value. The step is to further screen the defect area which is extracted preliminarily, and is established on the basis of the original image, so that the influence of uneven image brightness on the detection result can be eliminated.
While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.
Claims (10)
1. An electronic screen color spot detection device based on machine vision technology, comprising:
the image acquisition module is used for acquiring an image of the electronic screen to be detected;
the image preprocessing module is in communication connection with the image acquisition module and is used for preprocessing the acquired image;
the defect classification detection module is in communication connection with the image preprocessing module and is used for carrying out color spot detection on the preprocessed image; and
and the electronic screen defect detection system is in communication connection with the defect classification detection module and is used for displaying a color spot detection result.
2. The machine-vision-technology-based electronic screen stain detection device of claim 1, wherein the image acquisition module is a CCD industrial camera.
3. The device for detecting color spots on an electronic screen based on machine vision technology as claimed in claim 1, wherein the environment of image acquisition is a dark room, and the electronic screen is a state in which the screen is lighted without displaying any pattern.
4. A method for electronic screen stain detection using the device of any of claims 1-3, comprising the steps of:
the method comprises the following steps that firstly, an image acquisition module is adopted to acquire an image of an electronic screen to be detected;
secondly, preprocessing the acquired image by adopting the image preprocessing module;
thirdly, respectively designing an algorithm to detect the defects by adopting the defect classification detection module according to respective characteristics of the screen defects;
and step four, designing a user interface of the electronic screen defect detection system by using an interface editing tool of Matlab and displaying a color spot detection result.
5. The method for electronic screen stain detection as recited in claim 4, wherein the image acquisition process is: fixing two ends of the electronic product by using a clamp fixed on the measuring table; keeping the electronic product horizontal, and photographing the electronic screen in a lighting state along the vertical direction by using a camera; and digitizing the acquired electronic product image and transmitting the digitized electronic product image to relevant software of a computer for further image preprocessing.
6. The method for detecting color spots on an electronic screen according to claim 4, wherein the image preprocessing process in the second step is as follows: carrying out binarization and edge detection to determine the position of an electronic screen area; the geometric correction is adopted to keep the target area horizontal, so that the target extraction operation is facilitated; performing color space conversion improves the contrast of screen defects with the surroundings.
7. The method for detecting color stains on an electronic screen according to claim 4, wherein the image preprocessing in the second step comprises a dust removal process, an image filtering process and an image segmentation process.
8. The method for detecting color spots on an electronic screen according to claim 7, wherein the dust removal process is: turning on a system light source and collecting an image; obtaining the position and the area of the dust; and jointly comparing the dust area with the defect area to eliminate the influence of dust on the image detection result.
9. The method of electronic screen stain detection as claimed in claim 7 wherein the image filtering process is a combined filtering process, i.e. a gaussian filtered image is used as the initial image for mean filtering to reduce the effects of texture and brightness non-uniformity, and then the combined filtering process is performed on the image using median filtering.
10. The method of electronic screen stain detection as recited in claim 7, wherein the image segmentation process is: dividing by using a local threshold to preliminarily extract defects; and judging whether the defects are reasonable or not through the local contrast, and finally realizing the extraction of the defects.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010338789.7A CN111583137A (en) | 2020-04-26 | 2020-04-26 | Electronic screen color spot detection device and method based on machine vision technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010338789.7A CN111583137A (en) | 2020-04-26 | 2020-04-26 | Electronic screen color spot detection device and method based on machine vision technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111583137A true CN111583137A (en) | 2020-08-25 |
Family
ID=72116947
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010338789.7A Pending CN111583137A (en) | 2020-04-26 | 2020-04-26 | Electronic screen color spot detection device and method based on machine vision technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111583137A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117782521A (en) * | 2023-12-28 | 2024-03-29 | 上海艺嘉智慧科技集团有限公司 | LED light curtain display delay measurement method and system thereof |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105301810A (en) * | 2015-11-24 | 2016-02-03 | 上海斐讯数据通信技术有限公司 | Screen defect detecting method and screen defect detecting device |
| CN107678192A (en) * | 2017-07-16 | 2018-02-09 | 中科院成都信息技术股份有限公司 | A kind of Mura defects detection method and system based on machine vision |
| CN108490656A (en) * | 2018-04-13 | 2018-09-04 | 凌云光技术集团有限责任公司 | Liquid crystal display image detection method and device |
| CN110445921A (en) * | 2019-09-06 | 2019-11-12 | 东北大学 | A kind of Mobile phone screen backlight foreign matter defect diagnostic method and device based on machine vision |
| CN110657946A (en) * | 2018-06-29 | 2020-01-07 | 上海微电子装备（集团）股份有限公司 | Screen defect detection system, screen detection line and screen defect detection method |
-
2020
- 2020-04-26 CN CN202010338789.7A patent/CN111583137A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105301810A (en) * | 2015-11-24 | 2016-02-03 | 上海斐讯数据通信技术有限公司 | Screen defect detecting method and screen defect detecting device |
| CN107678192A (en) * | 2017-07-16 | 2018-02-09 | 中科院成都信息技术股份有限公司 | A kind of Mura defects detection method and system based on machine vision |
| CN108490656A (en) * | 2018-04-13 | 2018-09-04 | 凌云光技术集团有限责任公司 | Liquid crystal display image detection method and device |
| CN110657946A (en) * | 2018-06-29 | 2020-01-07 | 上海微电子装备（集团）股份有限公司 | Screen defect detection system, screen detection line and screen defect detection method |
| CN110445921A (en) * | 2019-09-06 | 2019-11-12 | 东北大学 | A kind of Mobile phone screen backlight foreign matter defect diagnostic method and device based on machine vision |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117782521A (en) * | 2023-12-28 | 2024-03-29 | 上海艺嘉智慧科技集团有限公司 | LED light curtain display delay measurement method and system thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111524101A (en) | Electronic screen defect detection method based on machine vision technology | |
| CN104749184B (en) | Automatic optical detection method and system | |
| CN109916910B (en) | Photovoltaic glass edge defect detection system and corresponding method | |
| CN111812103B (en) | Image acquisition device, visual detection system and detection point extraction method | |
| CN108665458B (en) | Method for extracting and identifying surface defects of transparent body | |
| CN111289538A (en) | PCB element detection system and detection method based on machine vision | |
| CN113252568A (en) | Lens surface defect detection method, system, product and terminal based on machine vision | |
| CN102901735B (en) | System for carrying out automatic detections upon workpiece defect, cracking, and deformation by using computer | |
| CN108827597B (en) | Light spot uniformity detection method and detection system of structured light projector | |
| CN110108712A (en) | Multifunctional visual sense defect detecting system | |
| CN110717909A (en) | Metal surface scratch detection method and device | |
| CN106228541A (en) | Screen positioning method and device in visual inspection | |
| CN112084964A (en) | Product identification apparatus, method and storage medium | |
| CN104749801B (en) | High Precision Automatic optical detecting method and system | |
| CN111583137A (en) | Electronic screen color spot detection device and method based on machine vision technology | |
| CN112987356B (en) | Liquid crystal display panel bottom foreign matter filtering device | |
| CN114037682A (en) | Two-dimensional automatic detection method for optical element surface defects | |
| CN107248151B (en) | Intelligent liquid crystal display detection method and system based on machine vision | |
| CN111563869B (en) | Stain test method for quality inspection of camera module | |
| CN114964032B (en) | Blind hole depth measurement method and device based on machine vision | |
| CN111307817A (en) | Online detection method and system for PCB production process of intelligent production line | |
| KR101993654B1 (en) | Inspecting apparatus mura of display panel and method thereof | |
| CN212321466U (en) | Image acquisition device and visual detection system | |
| CN113240629B (en) | Edge-based image matching narrow-gap weld initial point positioning device and method | |
| JP5239275B2 (en) | Defect detection method and defect detection apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200825 |
|
| RJ01 | Rejection of invention patent application after publication |