CN110108712A - Multifunctional visual sense defect detecting system - Google Patents
Multifunctional visual sense defect detecting system Download PDFInfo
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- CN110108712A CN110108712A CN201910320820.1A CN201910320820A CN110108712A CN 110108712 A CN110108712 A CN 110108712A CN 201910320820 A CN201910320820 A CN 201910320820A CN 110108712 A CN110108712 A CN 110108712A
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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
- G01N21/8851—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
- G01N2021/8854—Grading and classifying of flaws
- G01N2021/8874—Taking dimensions of defect into account
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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
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Abstract
The present invention relates to the technical field of vision detection of product, refer in particular to a kind of Multifunctional visual sense defect detecting system, including rack, it is set to the monitor station of rack, secondary light source above monitor station and the image collecting device above secondary light source, the rack is installed with horizontal cross bar and the lifting mould group for driving horizontal cross bar to move up and down, this programme can carry out vision-based detection to a variety of different workpiece, context of detection includes the whether complete detection of components, the scratch of workpiece surface, material is dirty, the bad detection of weld tabs, the concentricity of round piece detects, the detection of workpiece size, workpiece placement position detection etc., not only effectively reduce the equipment input cost of production firm, effectively improve the Detection accuracy and efficiency of vision system, practicability is stronger.
Description
Technical field
The present invention relates to the technical field of vision detection of product, refer in particular to a kind of Multifunctional visual sense defect detecting system.
Background technique
In the process of product, it is often necessary to the detection of material or workpiece is carried out to product or semi-finished product, it is general to wrap
Include the whether complete detection of components, the scratch of workpiece surface, material dirt, the bad detection of weld tabs, the concentricity detection of round piece, work
The detection of part size, the detection of workpiece placement position etc., using artificial detection, not only efficiency is very low, that there is also omission factors is high,
The at high cost and lower problem of accuracy rate, artificial detection are limited to the subjective factor of people, missing inspection during saw blade Surface testing
Probability is very high；Omission factor is high, and production firm has economic loss, and cost of labor is also gradually increasing；It manually examines merely
It surveys, manually carries out a large amount of repetitive operation, sense tired out can be generated, constrain the efficiency of detection, rely on artificial detection, inspection merely
Surveying precision will certainly reduce, it is difficult to meet and produce demand under manufacturing environment in enormous quantities.
Summary of the invention
It is high that the technical problem to be solved in the present invention is to provide a kind of Detection accuracies, high-efficient, can be according to different workpieces
Testing requirements use the Multifunctional visual sense defect detecting system without detection method, in the case where being changed without hardware detection
Realize the comprehensive detection function of a variety of detection demands of various workpieces.
In order to solve the above-mentioned technical problem, the present invention adopts the following technical scheme: a kind of Multifunctional visual sense defects detection system
System, including rack, the monitor station, the secondary light source above monitor station and the figure above secondary light source that are set to rack
As acquisition device, the rack is installed with horizontal cross bar and the lifting mould group for driving horizontal cross bar to move up and down, vision inspection
Examining system includes the following steps:
Standard testing workpiece is placed in monitor station 2 by step A；
Step B, image collecting device 4 carry out Image Acquisition to the standard testing workpiece on monitor station 2 and obtain template image, and will
Template image is sent to image processor；
Step C, image processor carry out binary conversion treatment to collected template image；
Step D, image processor 7 carry out edge detection algorithm to the template image after binary conversion treatment and obtain standard testing workpiece
Shape information.
Step E, image processor establish the Template Information of standard testing workpiece using outline algorithm, remove standard survey
Trial work part；
Step F, is put into workpiece for measurement；Image collecting device 4 carries out Image Acquisition to the workpiece for measurement on monitor station 2 and is detected
Image, and will test image and be sent to image processor；
Step G, image processor 7 carry out binary conversion treatment to collected detection image；
Step H, image processor 7 carry out the shape that edge detection algorithm obtains workpiece for measurement to the detection image after binary conversion treatment
Shape information.
Shape information obtained in step F and Template Information are carried out shape matching algorithm by step I, image processor 7, if
Regular inspection measuring angle is 0 ~ 360 °；
Step J, outline: if outline success, determines OK, otherwise determine NG；
Step F to step J is repeated when detecting again.
Preferably, in the step G, detection image is carried out to carry out image preprocessing before binary conversion treatment to eliminate
Unrelated information in image enhances detectability for information about and simplifies image data.
It preferably, further include spot-analysis algorithm and spacing detection step in the step I, after shape matching algorithm
Suddenly.
Preferably, the spot-analysis algorithm is analyzed the connected domain of same pixel in image, specific steps packet
It includes: now will test image and carry out binaryzation, segmentation obtains prospect background, carries out connected domain (Blob) detection, then to acquire
The process of Blob block.
Preferably, in the step G, Low threshold being adjusted to 46 in binary conversion treatment, high threshold 255.
Preferably, in the step I, edge pattern is quick, feature quantity 50%, profile length 20；And in profile
When matching, search parameter adjustment are as follows: number of searches 1, minimum score 70, ratio 100, overlap distance 0, search speed
It is set to LV5 with positioning accuracy, matching polarity is normal.
Preferably, in the step E, edge pattern is accurate, feature quantity 10%, profile length 20, the step
In J: number of searches 1, minimum score 80, ratio are set as 100, overlap distance 0, search speed and registration LV5,
It is normal with polarity.
Preferably, the secondary light source 3 is circular ring shape light source, the central axis of described image acquisition device 4 and secondary light source
Coaxial arrangement.
Preferably, the secondary light source is rectangular shaped light source, dome-geometry light source or square frame-shaped light source.
The beneficial effects of the present invention are: the present invention provides a kind of Multifunctional visual sense defect detecting systems, and this programme can
With to a variety of different workpiece carry out vision-based detection, context of detection include components it is whether complete detection, workpiece surface scratch,
Expect dirt, the bad detection of weld tabs, the concentricity detection of round piece, the detection of workpiece size, the detection of workpiece placement position etc., it is raw
Manufacturer is produced to no longer need to individually designed for different workpiece and manufacture the dedicated visual detection equipment for specific workpiece, it is only necessary to
The various of finished product after up to 20 kinds of components, semi-finished product can be realized in the Multifunctional visual sense defect detecting system of one playscript with stage directions invention
Defects detection not only effectively reduces the equipment input cost of production firm, effectively improve vision system Detection accuracy and
Efficiency, practicability are stronger.
Detailed description of the invention
Fig. 1 is the device structure schematic diagram of strip-shaped work vision detection system of the present invention.
Structural schematic diagram when Fig. 2 is the equipment hidden parts rack of strip-shaped work vision detection system of the present invention.
Fig. 3 is the detecting step functional block diagram of strip-shaped work vision detection system of the present invention.
Specific embodiment
For the ease of the understanding of those skilled in the art, below with reference to embodiment, the present invention is further illustrated, real
The content that the mode of applying refers to not is limitation of the invention.
As shown in Figure 1 to Figure 3, a kind of Multifunctional visual sense defect detecting system including rack, is set to the detection of rack
Platform, the secondary light source above monitor station and the image collecting device above secondary light source, the rack are installed with water
Flat cross bar and lifting mould group for driving horizontal cross bar to move up and down, vision detection system include the following steps:
Standard testing workpiece is placed in monitor station 2 by step A；
Step B, image collecting device 4 carry out Image Acquisition to the standard testing workpiece on monitor station 2 and obtain template image, and will
Template image is sent to image processor；
Step C, image processor carry out binary conversion treatment to collected template image；
Step D, image processor 7 carry out edge detection algorithm to the template image after binary conversion treatment and obtain standard testing workpiece
Shape information.
Step E, image processor establish the Template Information of standard testing workpiece using outline algorithm, remove standard survey
Trial work part；
Step F, is put into workpiece for measurement；Image collecting device 4 carries out Image Acquisition to the workpiece for measurement on monitor station 2 and is detected
Image, and will test image and be sent to image processor；
Step G, image processor 7 carry out binary conversion treatment to collected detection image；
Step H, image processor 7 carry out the shape that edge detection algorithm obtains workpiece for measurement to the detection image after binary conversion treatment
Shape information.
Shape information obtained in step F and Template Information are carried out shape matching algorithm by step I, image processor 7, if
Regular inspection measuring angle is 0 ~ 360 °；
Step J, outline: if outline success, determines OK, otherwise determine NG；
Step F to step J is repeated when detecting again.
Preferably, in the step G, detection image is carried out to carry out image preprocessing before binary conversion treatment to eliminate
Unrelated information in image enhances detectability for information about and simplifies image data.Firstly, carrying out two to obtained image
Value processing, the image information feature for filtering out and being not belonging to solder horn itself in image is reached with this.Pass through binaryzation obtaining
After the image of processing, carry out contours extract is carried out to different solder horns, obtains feature object image outline, meanwhile, it is taken turns with these
Exterior feature establishes matching primary template respectively.Then template matching and matching are carried out to late detection image with primary template, and
The image that will match to passes through the coordinate system established out and provides its opposite position coordinates.To reach and identify different soldering irons
Head and detect its whether corresponding position testing goal.
Image preprocessing is to come out each character image sorting to give identification module identification, this process is known as scheming
As pretreatment.In image analysis, the processing carried out before feature extraction, segmentation and matching is carried out to input picture.Image is pre-
The main purpose of processing is to eliminate unrelated information in image, restores useful real information, enhances for information about detectable
Property and to the maximum extent simplify data, to improve the reliability of feature extraction, image segmentation, matching and identification.
Binaryzation is exactly to set 0 or 255 for the gray value of the pixel on image, that is, whole image is showed
The process of apparent black and white effect.It is 0 or 255 that the binary conversion treatment of image, which is exactly by the gray value of the point on image, that is,
Whole image is showed into apparent black and white effect.The gray level image of 256 brightness degrees is chosen by threshold value appropriate
And it obtains and still can reflect the whole binary image with local feature of image.In Digital Image Processing, bianry image is accounted for
There is very important status, especially in practical image procossing, the system constituted with binary Images Processing realization is very
More, the processing and analysis of Yao Jinhang bianry image first have to a Binary Sketch of Grey Scale Image, obtain binary image, so
Being conducive to when being further processed to image, the set property of image is only related with the position of point that pixel value is 0 or 255,
The multilevel values for not further relating to pixel make processing become simple, and data processing and decrement it is small.In order to obtain ideal two
It is worth image, the region that the general boundary definition using closing, connection does not overlap.All gray scales are greater than or equal to the pixel quilt of threshold value
It is judged to belonging to certain objects, gray value is 255 expressions, and otherwise these pixels are excluded other than object area, gray scale
Value is 0, indicates the object area of background or exception.
Outline algorithm, the identification matching based on profile, needs image to split channel, finds edge, be converted to wheel
Wide (polygonal segments, characteristic summary etc.), then carries out outline (image and images match, image and template matching).Journey
Sequence person selects to be suitble to image abstraction method and matching process according to different situations.
The matching of profile mainly solves size, and position rotates angle, the matching problem between precision different images.Method
Including Contour moment, pairwise geometric histograms, convex closure and convex defect, ratings match etc..
It preferably, further include spot-analysis algorithm and spacing detection step in the step I, after shape matching algorithm
Suddenly.
Preferably, the spot-analysis algorithm is analyzed the connected domain of same pixel in image, specific steps packet
It includes: now will test image and carry out binaryzation, segmentation obtains prospect background, carries out connected domain (Blob) detection, then to acquire
The process of Blob block.
By taking the Defect Detection of plastic bottle as an example:
Main use algorithm in the present embodiment has: image preprocessing-Binarization methods, outline algorithm and spot point
Analyse algorithm.
Firstly, carrying out binary conversion treatment to obtained image, is reached with this and filter out periphery unwanted picture letter
Breath.It is obtaining after the image of binary conversion treatment, contours extract is carried out to it, obtaining feature object image outline, meanwhile, with
This profile establishes matching primary template.Then template matching and matching are carried out to late detection image with primary template, and
The image that will match to passes through the coordinate system established out and provides its opposite position coordinates, and carries out position benefit to subsequent algorithm
Region just to limit algorithm detection.Finally, being calculated to limit using spot-analysis algorithm the template position coordinate by obtaining
Method detection zone avoids breakfast or characteristics of image interference detection results of the outer image of body profile on image.Finally, spot-analysis
It obtains and detects and be not belonging to itself or feature situation against regulation on cylinder, to realize testing goal.
Outline: the identification matching based on profile needs image to split channel, finds edge, it is (more to be converted to profile
Side shape is approached, and characteristic is summarized etc.), then carry out outline (image and images match, image and template matching).Programmer's root
According to different situations, select to be suitble to image abstraction method and matching process.
The matching of profile mainly solves size, and position rotates angle, the matching problem between precision different images.Method
Including Contour moment, pairwise geometric histograms, convex closure and convex defect, ratings match etc..
Image preprocessing: being to come out each character image sorting to give identification module identification, this process is known as scheming
As pretreatment.In image analysis, the processing carried out before feature extraction, segmentation and matching is carried out to input picture.Image is pre-
The main purpose of processing is to eliminate unrelated information in image, restores useful real information, enhances for information about detectable
Property and to the maximum extent simplify data, to improve the reliability of feature extraction, image segmentation, matching and identification.
Binaryzation is exactly to set 0 or 255 for the gray value of the pixel on image, that is, whole image is showed
The process of apparent black and white effect.It is 0 or 255 that the binary conversion treatment of image, which is exactly by the gray value of the point on image, that is,
Whole image is showed into apparent black and white effect.The gray level image of 256 brightness degrees is chosen by threshold value appropriate
And it obtains and still can reflect the whole binary image with local feature of image.In Digital Image Processing, bianry image is accounted for
There is very important status, especially in practical image procossing, the system constituted with binary Images Processing realization is very
More, the processing and analysis of Yao Jinhang bianry image first have to a Binary Sketch of Grey Scale Image, obtain binary image, so
Being conducive to when being further processed to image, the set property of image is only related with the position of point that pixel value is 0 or 255,
The multilevel values for not further relating to pixel make processing become simple, and data processing and decrement it is small.In order to obtain ideal two
It is worth image, the region that the general boundary definition using closing, connection does not overlap.All gray scales are greater than or equal to the pixel quilt of threshold value
It is judged to belonging to certain objects, gray value is 255 expressions, and otherwise these pixels are excluded other than object area, gray scale
Value is 0, indicates the object area of background or exception.
Spot-analysis algorithm: refer to that the connected domain to same pixel in image is analyzed.Its process be exactly by image into
Row binaryzation, segmentation obtain prospect background, then carry out connected domain (Blob) detection, thus the process to Blob block.Connection
Domain, referring in image has one piece of connected region composed by Similar color, textural characteristics.
Preferably, in the step G, Low threshold being adjusted to 46 in binary conversion treatment, high threshold 255.Preferably,
In the step I, edge pattern is quick, feature quantity 50%, profile length 20；And in outline, search parameter
Adjustment are as follows: number of searches 1, minimum score 70, ratio 100, overlap distance 0, search speed and positioning accuracy are all set
It is set to LV5, matching polarity is normal.Preferably, in the step E, edge pattern is accurate, feature quantity 10%, profile length
Be 20, in the step J: number of searches 1, minimum score 80, ratio are set as 100, overlap distance 0, search speed with
Registration LV5, matching polarity are normal.
In the present solution, include that overall profile identification and local configuration identify to the shape matching algorithm of workpiece, it is especially suitable
Shape matching algorithm when containing multiple products in a packing box.By taking the detection of solder horn complete product as an example.
Overall profile identification: in whole outline identification software algorithm, it is special to be directed to the multiple and different solder horn of workpiece
Sign extracts identification, and establishes matching template respectively, outline is carried out convenient for image of the later period to acquisition, therefore, it is determined that being
It is no there are misplaced, leakage is put.When Image Acquisition, carry out adopting figure under 1.4 apertures, the time for exposure of 30 μ s, and carry out image soft
Part processing.Binary conversion treatment is carried out to image first, Low threshold is adjusted to 46, high threshold 255.Under this group of parameter, figure
As that will be presented as that background is pure white, workpiece is completely black, to obtain the fine definition of image.Each workpiece is carried out with image after processing
Template matching, when establishing template, in contour detecting parameter, quickly, feature quantity selects 50%, profile length for edge pattern selection
Selection 20, the contour feature of different solder horns can be obtained with this parameter.And in outline, search parameter adjustment are as follows: search
Quantity is 1, minimum score 70, ratio 100, overlap distance 0, and search speed and positioning accuracy are set to LV5, is matched
Polarity is normal.Thus parameter can stable matching recognize same light source irradiation under soldering iron contour feature, therefore, it is determined that whether depositing
It is put in leakage, it is misplaced.
Local configuration identification: due to wherein there is 3 templates that can not identify from front, need to detect workpiece type from side, therefore
Increase the local detail of 3 workpiece of side station inspection.In Image Acquisition, under 4.0 apertures, the time for exposure of 400 μ s into
Row adopts figure, and carries out software processing.After acquiring the image, outline is carried out to 3 workpiece respectively, is obtaining template contours inspection
Survey numerical parameter setting are as follows: edge pattern is accurate, feature quantity 10%, profile length 20, thus can get the feature wheel of template
It is wide.And the search parameter in later period outline are as follows: number of searches 1, minimum score 80, ratio are set as 100, overlapping
Distance 0, search speed and registration LV5, matching polarity are normal.Under same illumination condition, which can guarantee workpiece
Stablize identification.
Preferably, the secondary light source 3 is circular ring shape light source, the central axis of described image acquisition device 3 and secondary light source 3
Coaxial arrangement, effectively improve image collecting device 4 institute collected workpiece image integrality, reduction distortion rate.Certainly, described
Secondary light source 3 can also be rectangular shaped light source, dome-geometry light source or square frame-shaped light source, according to the shape of detected workpiece and detection side
Formula angle reasonably selects, to obtain the workpiece image information of optimum detection.
In the description of the present invention, it should be noted that " laterally (X) ", " vertical if any term " center " for the noun of locality
To (Y) ", " vertical (Z) " " length ", " width ", " thickness ", "upper", "lower", "front", "rear", "left", "right", "vertical", " water
It is flat ", "top", "bottom", "inner", "outside", " clockwise ", the indicating positions such as " counterclockwise " and positional relationship be based on the figure
Orientation or positional relationship, be merely for convenience of narration the present invention and simplify description, rather than the device of indication or suggestion meaning or
Element must have a particular orientation, be constructed and be operated with particular orientation, should not be understood as limiting specific protection model of the invention
It encloses.
In addition, being used for description purposes only if any term " first ", " second ", it is not understood to indicate or imply relatively heavy
The property wanted or the quantity for implicitly indicating technical characteristic." first " is defined as a result, " second " feature can be expressed or implicit include
One or more this feature, in the present description, " several " are meant that two or more, unless otherwise clearly having
The restriction of body.
In the present invention, except as otherwise clear stipulaties and restriction, should make if any term " assembling ", " connected ", " connection " term
Broad sense goes to understand, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It is also possible to mechanical connect
It connects；It can be directly connected, be also possible to be connected by intermediary, can be and be connected inside two elements.For ability
For the those of ordinary skill of domain, the concrete meaning of above-mentioned term in the present invention can be understood as the case may be.
Several embodiments of the invention above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
Limitations on the scope of the patent of the present invention therefore cannot be interpreted as.It should be pointed out that for those of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to guarantor of the invention
Protect range.Therefore, the scope of protection of the patent of the invention shall be subject to the appended claims.
Claims (9)
1. Multifunctional visual sense defect detecting system, including rack (1), image processor (7), the monitor station for being set to rack (1)
(2), the image collecting device (4) for being located at the secondary light source (3) above monitor station (2) and being located above secondary light source (3), it is special
Sign is: the rack (1) is installed with horizontal cross bar (5) and the lifting mould group for driving horizontal cross bar (5) to move up and down
(6), vision detection system includes the following steps:
Standard testing workpiece is placed in monitor station (2) by step A；
Step B, image collecting device (4) carry out Image Acquisition to the standard testing workpiece on monitor station (2) and obtain template image,
And template image is sent to image processor；
Step C, image processor carry out binary conversion treatment to collected template image；
Step D, image processor (7) carry out edge detection algorithm to the template image after binary conversion treatment and obtain standard testing work
The shape information of part；
Step E, image processor establish the Template Information of standard testing workpiece using outline algorithm, remove standard testing work
Part；
Step F, is put into workpiece for measurement；Image collecting device (4) carries out Image Acquisition to the workpiece for measurement on monitor station (2) and obtains
Detection image, and will test image and be sent to image processor；
Step G, image processor (7) carry out binary conversion treatment to collected detection image；
Step H, image processor (7) carry out edge detection algorithm to the detection image after binary conversion treatment and obtain workpiece for measurement
Shape information；
Shape information obtained in step F and Template Information are carried out shape matching algorithm, setting by step I, image processor (7)
Detection angles are 0 ~ 360 °；
Step J, outline: if outline success, determines OK, otherwise determine NG；
Step F to step J is repeated when detecting again.
2. Multifunctional visual sense defect detecting system according to claim 1, it is characterised in that: in the step G, to inspection
Altimetric image carry out binary conversion treatment before carry out image preprocessing to eliminate information unrelated in image, enhance for information about can
Detection property and simplified image data.
3. Multifunctional visual sense defect detecting system according to claim 1, it is characterised in that: in the step I, shape
It further include spot-analysis algorithm and spacing detection step after matching algorithm.
4. Multifunctional visual sense defect detecting system according to claim 3, it is characterised in that: the spot-analysis algorithm is
The connected domain of same pixel in image is analyzed, specific steps include: that now will test image to carry out binaryzation, and segmentation obtains
Then prospect background carries out connected domain (Blob) detection, to acquire the process of Blob block.
5. Multifunctional visual sense defect detecting system according to claim 1, it is characterised in that: in the step G, binaryzation
Adjusting Low threshold to 46 in processing, high threshold 255.
6. Multifunctional visual sense defect detecting system according to claim 5, it is characterised in that: in the step I, edge mould
Formula is quick, feature quantity 50%, profile length 20；And in outline, search parameter adjustment are as follows: number of searches is
1, minimum score 70, ratio 100, overlap distance 0, search speed and positioning accuracy are set to LV5, are matching polarity just
Often.
7. Multifunctional visual sense defect detecting system according to claim 5, it is characterised in that: in the step E, edge mould
Formula is accurate, feature quantity 10%, profile length 20, in the step J: number of searches 1, minimum score 80, ratio
It is set as 100, overlap distance 0, search speed and registration LV5, matching polarity are normal.
8. Multifunctional visual sense defect detecting system according to claim 1, it is characterised in that: the secondary light source (3) is
Circular ring shape light source, the central axis setting of described image acquisition device (4) and secondary light source (3).
9. Multifunctional visual sense defect detecting system according to claim 1, it is characterised in that: the secondary light source (3) is
Rectangular shaped light source, dome-geometry light source or square frame-shaped light source.
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| CN110706277A (en) * | 2019-09-12 | 2020-01-17 | 创新奇智(合肥)科技有限公司 | Method for detecting object rotation angle based on chain code histogram |
| 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 |
| US20210172884A1 (en) * | 2019-12-02 | 2021-06-10 | Juki Corporation | Inspection device and inspection method |
| CN113379726A (en) * | 2021-06-30 | 2021-09-10 | 深圳中科飞测科技股份有限公司 | Line detection method, device, equipment and computer readable storage medium |
| CN113959951A (en) * | 2021-11-21 | 2022-01-21 | 天津宏华焊研机器人科技有限公司 | Machine vision device for online detection of workpiece assembly and detection method |
| CN114184616A (en) * | 2021-11-25 | 2022-03-15 | 安徽布拉特智能科技有限公司 | Detection device for blue film for lithium battery and control method thereof |
| CN114354631A (en) * | 2022-01-12 | 2022-04-15 | 绍兴职业技术学院 | Valve blank surface defect detection method based on vision |
| CN115753791A (en) * | 2022-11-10 | 2023-03-07 | 哈尔滨耐是智能科技有限公司 | Defect detection method, device and system based on machine vision |
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