CN108982512A - A kind of circuit board detecting system and method based on machine vision - Google Patents
A kind of circuit board detecting system and method based on machine vision Download PDFInfo
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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
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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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
- G01N21/956—Inspecting patterns on the surface of objects
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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
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
- G01N2021/8893—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques providing a video image and a processed signal for helping visual decision
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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
- G01N21/956—Inspecting patterns on the surface of objects
- G01N2021/95638—Inspecting patterns on the surface of objects for PCB's
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
- G01N2201/10—Scanning
- G01N2201/102—Video camera
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Abstract
The circuit board detecting system and method based on machine vision that the invention discloses a kind of.In the present invention: camera carries out shooting image information to the circuit board on production line working platform；Image information is transmitted to image capture module by camera；Image information is converted to Binary Signal Transmission to terminal device and handled by image capture module；By image positioning acquisition, image enhancement, image denoising, image segmentation, picture edge characteristic extract, the image of flawless standard component is handled by above step and is fabricated to standard picture by the several steps of defects detection；By by testing image and standard picture pixel-by-pixel compared with carry out detection defect.The present invention carries out processing identification to image by computer and detects defect by camera collecting circuit board image information, without artificial range estimation, improves testing efficiency, reduces omission factor；And reduce cost of human resources.
Description
Technical field
The invention belongs to circuit board detecting field, more particularly to a kind of circuit board detecting system based on machine vision and
Its method.
Background technique
With the fast development of electronics integrated technology, the electronic component integrated level of circuit board is also continuously increased, this
It is required that production technology becomes increasingly complex, cost can also improve.Therefore after being laid with component, it is necessary to be examined to circuit board
It surveys, detects defect, circuit board damage caused by avoiding because of defect.
The several methods such as the mainly artificial range estimation of circuit board detecting method traditional at present, electric logging device and X-ray, however he
Respectively have itself defect, be unable to satisfy the demand of a large amount of high speed circuit boards detections.
The vision-based detection of people is most easy and practical, the strongest detection mode of adaptability.But it is overly dependent upon human eye use
Magnifying glass checks printed circuit board.Due to the limitation of physiologic factor, the detection manually estimated is compared inefficiency, leakage
Inspection rate is relatively high, vulnerable to the interference of external factor, is extremely difficult to the test request that circuit board production line is accurate, recyclable.Meanwhile
The detection method can lead to test employee's visual impairment, and even for the printed circuit board of intermediate complex, artificial mesh
Surveying inspection method also seems unable to do what one wishes.
Electric logging device is most common printed circuit board production test method, and advantage is fault-detecting ability by force and detects
It is high-efficient.But to, product category numerous users few with quantity, it usually needs the probe for constantly replacing needle bed causes to examine
Survey inefficiency.
The shortcomings that in order to make up traditional detection defect of printed circuit board method, the production efficiency and product for improving circuit board are closed
Lattice rate reduces production cost；The generation of automatic optics inspection circuit board technology there has been market, and detection technique is with machine vision
Ei premise；Machine vision refers to the things using computer sense organ real world, instead of the visual performance of human eye.Compare other
Detection technique improves a lot in terms of detection accuracy, efficiency and stationarity, therefore has developed into printed circuit board (PCB) detecting
Main flow direction.
A kind of currently designed circuit board detecting system and method based on machine vision carry out defects detection to circuit board,
By camera collecting circuit board image information, and processing identification is carried out to image by computer and detects defect, is not necessarily to people
Work range estimation, improves testing efficiency, reduces omission factor；And reduce cost of human resources.
Summary of the invention
The circuit board detecting system and method based on machine vision that the purpose of the present invention is to provide a kind of, pass through camera shooting
Head collecting circuit board image information, and processing identification is carried out to image by computer and detects defect, without artificial range estimation, mention
High testing efficiency, reduces omission factor；And reduce cost of human resources.
In order to solve the above technical problems, the present invention is achieved by the following technical solutions:
The present invention is a kind of circuit board detecting system based on machine vision, comprising: camera, workbench, Image Acquisition
Card, control circuit, driver and terminal device；It is equipped with a lighting apparatus above the workbench and carries out light adjustment；The end
End equipment is connected to the control circuit by serial communication；The control circuit is connect with camera and driver respectively；The control
Circuit control camera processed is taken pictures；The driving circuit is connect with a servo motor；The control circuit passes through driver
Control the operation of servo motor；The servo motor is connect with workbench；Assembly line on the Serve Motor Control workbench
It runs the camera and shooting image information is carried out to the circuit board on production line working platform；The camera passes image information
Transport to image capture module；Image information is converted to Binary Signal Transmission to terminal device and carried out by described image acquisition module
Processing；The terminal device carries out decision circuitry plate with the presence or absence of defect by extracting characteristic information to Image Information Processing.
Preferably, the lighting apparatus uses LED light, and the lighting apparatus uses ring illumination mode；Terminal device is
Computer；Processing and recognition detection are carried out to image by the software algorithm on computer.
A kind of circuit board detecting method based on machine vision, comprising the following steps:
SS01, image ground positioning acquisition
Position is adjusted by servo motor, brand is carried out after the camera positioning circuit board under test and acquires image information；
The image information of acquisition is transmitted through image pick-up card and is transmitted to terminal device by the camera to be handled
SS02, image enhancement
The terminal device carries out image preprocessing after receiving image information；By linearly transporting behind selected greyscale transformation region
Image is carried out greyscale transformation by the gray value for calculating modification image；
SS03, image denoising
Processing denoising is carried out to image by weighted mean filter method；
To one window neighborhood of template pixel placement on image, the window neighborhood is square or rectangle or cross
Shape；The window neighborhood includes the pixel that object pixel closes on and centered on object pixel；By calculating window line by line or by column
The average value of all pixels replaces original pixel value in mouthful；
The shapes and sizes for keeping window, pixel centered on pixel each in original image is replaced with average value one by one；
SS04, image segmentation；
It is compared according to the gray value of the gray value of object to be measured and ambient background, gray proces is carried out to image, by setting
Determine threshold value, judges whether the pixel in image belongs to object to be measured region；
Carrying out image threshold segmentation method is split using Two-dimensional Maximum inter-class variance split plot design；
SS05, picture edge characteristic extract；
The image obtained by Two-dimensional Maximum inter-class variance Threshold segmentation is subjected to edge detection, template image to be measured is believed
Breath is highlighted；Wherein, image border is determined by the position of detection image gray value stepped change；By calculating edge gray scale
The single order or second dervative of variation carry out detection image marginal point；
Method for detecting image edge uses the Sobel operator in 8 directions；Pass through Sobel operator detection level direction, Vertical Square
It examines at the edge for obtaining eight directions to the first differential of the edge in, 45 °, 135 °, 180 °, 225 °, 270 °, 315 ° eight directions
Survey template；
Given threshold carries out binaryzation to testing image, is just taken with eight templates respectively with digital picture phase convolution respectively
Maximum value replaces the gray value of respective pixel, successively traverses all pixels of image, completes the edge detection to image；
SS06, defects detection
The image of flawless standard component is fabricated to standard picture by above step processing；By by testing image with
Standard picture compares pixel-by-pixel carries out detection defect.
The invention has the following advantages:
1, the present invention is by camera collecting circuit board image information, and by computer to image carry out processing identification with
Defect is detected, without artificial range estimation, testing efficiency is improved, reduces omission factor；And reduce cost of human resources.
2, the present invention reduces picture noise by weighted average filter method, saves the useful letter of image well
Breath；And traditional Sobel operator is improved, it improves and extracts edge feature effect；To improve defects detection effect
Certainly, it implements any of the products of the present invention and does not necessarily require achieving all the advantages described above at the same time.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, will be described below to embodiment required
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is a kind of system block diagram of circuit board detecting system based on machine vision of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all other
Embodiment shall fall within the protection scope of the present invention.
Refering to Figure 1, the present invention is a kind of circuit board detecting system based on machine vision, comprising: camera, work
Make platform, image pick-up card, control circuit, driver and terminal device；It is equipped with a lighting apparatus above workbench and carries out light tune
It is whole；Terminal device is connected to the control circuit by serial communication；Control circuit is connect with camera and driver respectively；Control electricity
Road control camera is taken pictures；Driving circuit is connect with a servo motor；Control circuit passes through driver control servo motor
Operation；Servo motor is connect with workbench；Assembly line operation camera on Serve Motor Control workbench is to assembly line work
The circuit board made on platform carries out shooting image information；Image information is transmitted to image capture module by camera；Image Acquisition mould
Image information is converted to Binary Signal Transmission to terminal device and handled by block；Terminal device passes through to Image Information Processing
It extracts characteristic information and carries out decision circuitry plate with the presence or absence of defect.
Wherein, lighting apparatus uses LED light, and lighting apparatus uses ring illumination mode；Terminal device is computer；Pass through
Software algorithm on computer carries out processing and recognition detection to image.
A kind of circuit board detecting method based on machine vision, comprising the following steps:
SS01, image ground positioning acquisition
Position is adjusted by servo motor, camera carries out brand acquisition image information after positioning circuit board under test；Camera shooting
The image information of acquisition is transmitted through image pick-up card and is transmitted to terminal device by head to be handled
SS02, image enhancement
Terminal device carries out image preprocessing after receiving image information；It is repaired behind selected greyscale transformation region by linear operation
Image is carried out greyscale transformation by the gray value of picture of changing plan；
SS03, image denoising
Processing denoising is carried out to image by weighted mean filter method；
To one window neighborhood of template pixel placement on image, window neighborhood is square or rectangle or cross；Window
Mouthful neighborhood includes the pixel that object pixel closes on and centered on object pixel；Pass through line by line or by column all pictures in calculation window
The average value of element replaces original pixel value；
The shapes and sizes for keeping window, pixel centered on pixel each in original image is replaced with average value one by one；
SS04, image segmentation；
It is compared according to the gray value of the gray value of object to be measured and ambient background, gray proces is carried out to image, by setting
Determine threshold value, judges whether the pixel in image belongs to object to be measured region；
Carrying out image threshold segmentation method is split using Two-dimensional Maximum inter-class variance split plot design；
SS05, picture edge characteristic extract；
The image obtained by Two-dimensional Maximum inter-class variance Threshold segmentation is subjected to edge detection, template image to be measured is believed
Breath is highlighted；Wherein, image border is determined by the position of detection image gray value stepped change；By calculating edge gray scale
The single order or second dervative of variation carry out detection image marginal point；
Method for detecting image edge uses the Sobel operator in 8 directions；Pass through Sobel operator detection level direction, Vertical Square
It examines at the edge for obtaining eight directions to the first differential of the edge in, 45 °, 135 °, 180 °, 225 °, 270 °, 315 ° eight directions
Survey template；
Given threshold carries out binaryzation to testing image, is just taken with eight templates respectively with digital picture phase convolution respectively
Maximum value replaces the gray value of respective pixel, successively traverses all pixels of image, completes the edge detection to image；
SS06, defects detection
The image of flawless standard component is fabricated to standard picture by above step processing；By by testing image with
Standard picture compares pixel-by-pixel carries out detection defect.
It is worth noting that, included each unit is only drawn according to function logic in the above system embodiment
Point, but be not limited to the above division, as long as corresponding functions can be realized；In addition, each functional unit is specific
Title is also only for convenience of distinguishing each other, the protection scope being not intended to restrict the invention.
In addition, those of ordinary skill in the art will appreciate that realizing all or part of the steps in the various embodiments described above method
It is that relevant hardware can be instructed to complete by program, corresponding program can store to be situated between in a computer-readable storage
In matter, the storage medium, such as ROM/RAM, disk or CD.
Present invention disclosed above preferred embodiment is only intended to help to illustrate the present invention.There is no detailed for preferred embodiment
All details are described, are not limited the invention to the specific embodiments described.Obviously, according to the content of this specification,
It can make many modifications and variations.These embodiments are chosen and specifically described to this specification, is in order to better explain the present invention
Principle and practical application, so that skilled artisan be enable to better understand and utilize the present invention.The present invention is only
It is limited by claims and its full scope and equivalent.
Claims (3)
1. a kind of circuit board detecting system based on machine vision characterized by comprising camera, workbench, Image Acquisition
Card, control circuit, driver and terminal device；
It is equipped with a lighting apparatus above the workbench and carries out light adjustment；The terminal device passes through serial communication and control electricity
Road connection；The control circuit is connect with camera and driver respectively；The control circuit control camera is taken pictures；Institute
Driving circuit is stated to connect with a servo motor；The control circuit passes through the operation of driver control servo motor；The servo
Motor is connect with workbench；Assembly line operation on the Serve Motor Control workbench
The camera carries out shooting image information to the circuit board on production line working platform；The camera passes image information
Transport to image capture module；Image information is converted to Binary Signal Transmission to terminal device and carried out by described image acquisition module
Processing；
The terminal device carries out decision circuitry plate with the presence or absence of defect by extracting characteristic information to Image Information Processing.
2. a kind of circuit board detecting system based on machine vision according to claim 1, which is characterized in that the illumination
Equipment uses LED light, and the lighting apparatus uses ring illumination mode.
3. a kind of circuit board detecting method based on machine vision as described in claim 1-2 is any one, which is characterized in that packet
Include following steps:
SS01, image ground positioning acquisition
Position is adjusted by servo motor, brand is carried out after the camera positioning circuit board under test and acquires image information；It is described
The image information of acquisition is transmitted through image pick-up card and is transmitted to terminal device by camera to be handled
SS02, image enhancement
The terminal device carries out image preprocessing after receiving image information；It is repaired behind selected greyscale transformation region by linear operation
Image is carried out greyscale transformation by the gray value of picture of changing plan；
SS03, image denoising
Processing denoising is carried out to image by weighted mean filter method；
To one window neighborhood of template pixel placement on image, the window neighborhood is square or rectangle or cross；Institute
Stating window neighborhood includes pixel that object pixel closes on and centered on object pixel；Pass through line by line or by column institute in calculation window
There is the average value replacement original pixel value of pixel；
The shapes and sizes for keeping window, pixel centered on pixel each in original image is replaced with average value one by one；
SS04, image segmentation；
It is compared according to the gray value of the gray value of object to be measured and ambient background, gray proces is carried out to image, by setting threshold
Value, judges whether the pixel in image belongs to object to be measured region；
Carrying out image threshold segmentation method is split using Two-dimensional Maximum inter-class variance split plot design；
SS05, picture edge characteristic extract；
The image that will be obtained by Two-dimensional Maximum inter-class variance Threshold segmentation carries out edge detection, template image information to be measured into
Row highlights；Wherein, image border is determined by the position of detection image gray value stepped change；By calculating edge grey scale change
Single order or second dervative carry out detection image marginal point；
Method for detecting image edge uses the Sobel operator in 8 directions；By Sobel operator detection level direction, vertical direction,
The first differential of the edge in 45 °, 135 °, 180 °, 225 °, 270 °, 315 ° eight directions obtains the edge detection in eight directions
Template；
Given threshold carries out binaryzation to testing image, just takes maximum respectively with digital picture phase convolution with eight templates respectively
The gray value of value replacement respective pixel, successively traverses all pixels of image, completes the edge detection to image；
SS06, defects detection
The image of flawless standard component is fabricated to standard picture by above step processing；By by testing image and standard
Image pixel by pixel, which compares, carries out detection defect.
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| CN110335233A (en) * | 2019-04-24 | 2019-10-15 | 武汉理工大学 | Express-way guard-rail plates defect detecting system and method based on image processing techniques |
| CN110517231A (en) * | 2019-08-13 | 2019-11-29 | 云谷（固安）科技有限公司 | Shield the detection method and device of body showing edge |
| CN110530896A (en) * | 2019-09-05 | 2019-12-03 | 珠海格力智能装备有限公司 | Detection method and device, storage medium and processor |
| CN111272766A (en) * | 2020-02-20 | 2020-06-12 | 上海普密德自动化科技有限公司 | Surface defect detection system based on vision technology and detection method thereof |
| CN111300061A (en) * | 2020-02-20 | 2020-06-19 | 吉林建筑大学 | Heat pipe production device, production control method and computer program product |
| CN111571599A (en) * | 2020-05-29 | 2020-08-25 | 杭州申昊科技股份有限公司 | Explosion-proof inspection robot and inspection method thereof |
| CN111929631A (en) * | 2020-08-21 | 2020-11-13 | 国网江苏省电力有限公司盐城供电分公司 | Display defect detection system and detection method for power display equipment |
| CN111972700A (en) * | 2019-05-22 | 2020-11-24 | 上海烟草集团有限责任公司 | Cigarette appearance detection method and device, equipment, system and medium thereof |
| CN111999314A (en) * | 2020-10-28 | 2020-11-27 | 南京大量数控科技有限公司 | Device and method for automatically checking deformation of flexible PCB in processing process |
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| CN112577973A (en) * | 2020-12-16 | 2021-03-30 | 深圳市燕麦科技股份有限公司 | Flexible circuit board detection device |
| CN113298793A (en) * | 2021-06-03 | 2021-08-24 | 中国电子科技集团公司第十四研究所 | Circuit board surface defect detection method based on multi-view template matching |
| CN113781419A (en) * | 2021-08-31 | 2021-12-10 | 广州大学 | Defect detection method, visual system, device and medium for flexible PCB |
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| CN110335233B (en) * | 2019-04-24 | 2023-06-30 | 武汉理工大学 | Highway guardrail plate defect detection system and method based on image processing technology |
| CN110335233A (en) * | 2019-04-24 | 2019-10-15 | 武汉理工大学 | Express-way guard-rail plates defect detecting system and method based on image processing techniques |
| CN111972700A (en) * | 2019-05-22 | 2020-11-24 | 上海烟草集团有限责任公司 | Cigarette appearance detection method and device, equipment, system and medium thereof |
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