CN102914549B - Optical image matching detection method aiming at satellite-borne surface exposed printed circuit board (PCB) soldering joint quality - Google Patents
Optical image matching detection method aiming at satellite-borne surface exposed printed circuit board (PCB) soldering joint quality Download PDFInfo
- Publication number
- CN102914549B CN102914549B CN201210332167.9A CN201210332167A CN102914549B CN 102914549 B CN102914549 B CN 102914549B CN 201210332167 A CN201210332167 A CN 201210332167A CN 102914549 B CN102914549 B CN 102914549B
- Authority
- CN
- China
- Prior art keywords
- image
- ccd
- under test
- element under
- images
- 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.)
- Active
Links
Abstract
The invention provides an optical image matching detection method aiming at satellite-borne surface exposed printed circuit board (PCB) soldering joint quality. The method is that an image is partitioned, a block is taken as a unit for matching detection, the method has good real-time performance, and the online detection requirements can be satisfied. The specific process is that a template image which is suitable for a current element to be measured is searched from a standard database according to the PCB information of the element to be measured; the detection image of the element to be detected is obtained; the template image and the detection image are partitioned; and the relevancy of the two images is judged, and when the relevancy meets the threshold, whether the soldering joints of the image to be detected meet the requirements or not is judged. The partitioning process is carried out on the image on the basis of relevancy matching, so that the method not only has high matching success rate, but also greatly saves the computation time, and the real-time performance is improved; and a partitioning relevancy matching algorithm is simple and efficient and is easy to realize, and the method which is realized on the basis of the algorithm and is used for detecting the satellite-borne PCB soldering joint quality has good practicability.
Description
Technical field
The present invention relates to a kind of optical imagery matching detection method for spaceborne expression type printed circuit board (Printed Circuit Board, PCB) quality of welding spot, belong to quality of welding spot detection technique field.
Background technology
At present, in electronic equipment, expression type number of welds accounts for more than 80%, detection means is artificial visually examine's (if desired by the optical detection apparatus of certain enlargement factor) mainly, the impact of the objective factors such as industrial AOI (AutomatedOptical Inspection) the examined standard of system, is not applied in the production run of space product.Desk checking exists to be affected by human factors such as operator's experience, degree of fatigue and subjective sensations, do not have unified differentiation quantitative criteria, result of determination varies with each individual, and the consistance of criterion is poor, be difficult to ensure that 100% of solder joint detects, be easy to appearance undetected.。
Industry AOI system mainly adopts feature extraction comparison or every pixel interdependence than counterpart method, as " circuit board carries the research of components and parts detection system " of Northwestern Polytechnical University Zhang Jiling.These algorithms are complicated or cycle index is too much, cause real-time not to be very high, can not well be applicable to needs on-line checkingi and test item is many, detect accuracy requires high space product detection field.
Summary of the invention
The object of this invention is to provide a kind of optical imagery matching detection method for spaceborne expression type PCB quality of welding spot, the method is by carrying out piecemeal to image, and be that unit carries out matching detection with block, its real-time is good, can meet the needs of on-line checkingi.
For an optical imagery matching detection method for spaceborne expression type PCB quality of welding spot, concrete step is:
Step 101, to find from standard database according to the PCB information of element under test and be applicable to the template image of current element under test;
Step 102, CCD is made to be positioned at the dead ahead of element under test, and the spacing of adjustment CCD and element under test, on the image that CCD is gathered, the size of element under test is identical with the size of element under test on template image; CCD gathers element under test image, and is defined as image to be checked;
Step 103, be first w × h by size, form is that the template image of RGB24 converts 8 constant gray level images of size to; Template image is divided into m × n image block again, each block size is b × b, i.e. m=w/b, n=h/b; Ask the pixel average of each image block, obtain the pixel average matrix P that size is m × n;
Step 104, be W × H by size, form is that the image to be checked of RGB24 converts 8 constant gray level images of size to; Again image to be checked is divided into M × N number of image block, each block size is b × b, i.e. M=W/b, N=H/b; Ask the pixel average of each image block, obtain the pixel average matrix Q that size is M × N;
Step 105, initial time two matrixes initial point overlap, then order matrix P is in the enterprising line slip of matrix Q, often slides once, calculates the degree of correlation between two matrixes
when the degree of correlation calculated is less than setting threshold value, stops sliding, judge that the solder joint of this image to be checked meets the demands, otherwise continue to slide, when all relative position situations of sliding, the degree of correlation of two matrixes is still not less than setting threshold value, then judge that the solder joint of image to be checked does not meet the demands.
When element under test is too large, when all details of element under test cannot be represented in the piece image that CCD gathers, gather multiple image by mobile CCD, and splice multiple image, obtain image to be checked, the acquisition process of this image to be checked is:
In whole splicing, CCD is according to the image of acquisition order element under test from top to bottom, from left to right;
Step 201, using CCD gather the first width (i.e. the image in the element under test lower left corner) as splice benchmark image, gather the image of the next position with seasonal CCD, and enter step 202;
Step 202, judge that whether image that CCD gathers is the image of element under test left column, if so, then enter step 203, otherwise enter step 204;
Step 203, the image gathered with current C CD is for template image, with its lower images for target image, on selected template image, a pixel overlaps with a pixel on target image, respectively to upper right, bottom right, upper left, lower-left movable platen image, the often mobile degree of correlation once calculating two picture registration positions, judge whether preset times S mobile Minimum relevance weight obtained is less than setting threshold value, if, then the position relationship of two images during Minimum relevance weight is defined as the best stitching position of two width images, two width images are spliced by best stitching position, otherwise again obtain a width ccd image and calculate the degree of correlation again, until two width images splice with best stitching position,
Step 204, the image gathered with current C CD is for template image, with its left-side images for target image, on selected template image, a pixel overlaps with a pixel on target image, respectively to upper right, bottom right, upper left, lower-left movable platen image, the often mobile degree of correlation once calculating two picture registration positions, judge whether S the mobile Minimum relevance weight obtained is less than setting threshold value, if, then the position relationship of two images during Minimum relevance weight is defined as the best stitching position of two width images, two width images are spliced by best stitching position, otherwise again obtain a width ccd image and calculate the degree of correlation again, until two width images splice with best stitching position,
Step 205, judge that whether spliced image to be checked is complete, if imperfect, then CCD gathers the image of the next position, and returns step 202.
Beneficial effect
The present invention has carried out piecemeal process to image on the basis of relevant matches, both ensure that the high success rate of coupling, has saved computing time in a large number again, improve real-time; Piecemeal relevant matches algorithm of the present invention is simply efficient, and be easy to realize, the spaceborne PCB quality of welding spot detection method realized on its basis has good practicality.
Secondly, the present invention is directed to larger detecting element, use the element under test image of degree of correlation matching method to multi collect to splice, make the present invention be used in the detection of the quality of welding spot to larger element.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the optical imagery matching detection method of PCB quality of welding spot.
Fig. 2 is the schematic diagram of image to be checked and template image shiding matching.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in detail.
As shown in Figure 1, the present invention is directed to the optical imagery matching detection method of spaceborne expression type PCB quality of welding spot, concrete step is:
Step 101, to find from standard database according to the PCB information of element under test and be applicable to the template image of current element under test.
Standard database has the template image of various element, and the element on this template image is all that welding is excellent, template image is obtained by a large amount of sampling.Therefore the present invention chooses the template image of element under test from standard database, so that ensuing coupling uses.
Step 102, CCD is made to be positioned at the dead ahead of element under test, and the spacing of adjustment CCD and element under test, on the image that CCD is gathered, the size of element under test is identical with the size of element under test on template image; CCD gathers element under test image, and is defined as image to be checked;
The condition that the present invention uses is: light-source brightness is uniform and stable, CCD need demarcate, the spacing of CCD camera and PCB must meet the demands, that is: on the image that gathers of CCD, the size of element under test is identical with the size of element under test on template image, and image to be checked like this and template image just have the value of matching judgment quality of welding spot quality; The present invention determines the distance between CCD and element under test by eye-observation.
Step 103, be first w × h by size, form is that the template image of RGB24 converts 8 constant gray level images of size to; Template image is divided into m × n image block again, each block size is b × b, i.e. m=w/b, n=h/b; Ask the pixel average of each image block, obtain the pixel average matrix P that size is m × n.W in this process, h, m, n, b are constant.
Image is carried out piecemeal by the present invention, and be then that unit carries out follow-up judgement with image block, compared with prior art, the present invention can improve the speed of coupling, meets the requirement of real-time, can improve the accuracy of coupling simultaneously.
Matrix P of the present invention is retrieved as: using the pixel average of the image block of the first row first row asked for as matrix P position (1,1) value on, using the pixel average of the image block of the first row secondary series asked for as matrix P position (1,2) value on, using the pixel value mean value of the image block of the second row first row asked for as matrix P position (2,1) value on, and the like.
Step 104, be W × H by size, form is that the image to be checked of RGB24 converts 8 constant gray level images of size to; Again image to be checked is divided into M × N number of image block, each block size is b × b, i.e. M=W/b, N=H/b; Ask the pixel average of each image block, obtain the pixel average matrix Q that size is M × N.W in this process, H, N, M are constant.
The present invention, in order to be that unit carries out images match with image block, therefore needs image to be checked also to carry out the conversion the same with template image.
Matrix Q of the present invention is retrieved as: using the pixel average of the image block of the first row first row asked for as matrix Q position (1,1) value on, using the pixel average of the image block of the first row secondary series asked for as matrix Q position (1,2) value on, using the pixel value mean value of the image block of the second row first row asked for as matrix Q position (2,1) value on, and the like.
Step 105, initial time two matrixes initial point overlap, then order matrix P is in the enterprising line slip of matrix Q, often slides once, calculates the degree of correlation between two matrixes
when the degree of correlation calculated is less than setting threshold value, stops sliding, judge that the solder joint of this image to be checked meets the demands, otherwise continue to slide, when all relative position situations of sliding, the degree of correlation of two matrixes is still not less than setting threshold value, then judge that the solder joint of image to be checked does not meet the demands.
Under normal circumstances, if when element to be checked is less, the image to be checked now gathered is greater than template image usually, and therefore the present invention makes image to be checked motionless, makes template image slide on image to be checked, asks for the degree of correlation between two images, as shown in Figure 2.Template image slides with vertical direction in the horizontal direction, and the distance of each image block that slides, exists multiple relative position situation like this on two width images.Then compare the threshold value of the degree of correlation of often sliding once and setting, wherein threshold value draws according to a large amount of tests.The present invention can preferably make template image according to from left to right, and order from top to bottom moves, and finds in two width images the situation that whether there is the degree of correlation and be less than setting threshold value.
The present invention when element under test too large, when all details of element under test cannot be represented in the piece image that CCD gathers, need to gather multiple image by mobile CCD, and multiple image is spliced, obtain image to be checked, the acquisition process of this image to be checked is:
In whole splicing, CCD is according to the image of acquisition order element under test from top to bottom, from left to right; Can ensure to there is correlativity between the two adjacent width images that CCD gathers in this order.
Step 201, using CCD gather the first width (i.e. the image in the element under test lower left corner) as splice benchmark image, gather the image of the next position with seasonal CCD, and enter step 202.
Step 202, judge that whether image that CCD gathers is the image of element under test left column, if so, then enter step 203, otherwise enter step 204.
When the element that element under test is a strip, namely its upper edge and lower edge can be included in piece image, the image of the second width image that such CCD gathers and non-element under test left column, therefore be there is the region overlapped in the left side of the right side of piece image and the second width image, now enter step 204 and carry out image mosaic.When the length of element under test is suitable with width, namely its upper edge and lower edge cannot be included in piece image, and the second width image that such CCD gathers is the image of element under test left column, now needs to enter step 203 and carries out image mosaic.
Step 203, the image gathered with current C CD is for template image, with its lower images for target image, on selected template image, a pixel overlaps with a pixel on target image, respectively to upper right, bottom right, upper left, lower-left movable platen image, the often mobile degree of correlation once calculating two picture registration positions, judge whether S the mobile Minimum relevance weight obtained is less than setting threshold value, if, then the position relationship of two images during Minimum relevance weight is defined as the best stitching position of two width images, two width images are spliced by best stitching position, otherwise again obtain a width ccd image and calculate the degree of correlation again, until two width images splice with best stitching position.
Step 204, the image gathered with current C CD is for template image, with its left-side images for target image, on selected template image, a pixel overlaps with a pixel on target image, respectively to upper right, bottom right, upper left, lower-left movable platen image, the often mobile degree of correlation once calculating two picture registration positions, judge whether S the mobile Minimum relevance weight obtained is less than setting threshold value, if, then the position relationship of two images during Minimum relevance weight is defined as the best stitching position of two width images, two width images are spliced by best stitching position, otherwise again obtain a width ccd image and calculate the degree of correlation again, until two width images splice with best stitching position.
In step 203 and step 204, S is the integer of setting in advance, in theory, certainly there is the position of accurate match in the adjacent two width images that CCD gathers, when still not have for mobile S time, the match is successful, may be then gather for twice caused by the change of image-context because CCD is adjacent, the factor such as to block of such as light causes, and now CCD Resurvey piece image, till searching out best stitching position.
Step 205, judge that whether spliced image to be checked is complete, if imperfect, then CCD gathers the image of the next position, and returns step 202.
Complete if now splice, then now can enter step 103 and image to be checked and template image are processed, calculate the degree of correlation, and judge the quality of solder joint.
The method is applied to the Rough Inspection stage that spaceborne PCB quality of welding spot detects, can to Component Displacement, Short Item, wrong part, many tin, few tin, connect tin, set up a monument, breakage, the project such as upset detect, have higher real-time and reliability, the examining stage of carrying out for utilizing 3 D stereo microscope carries out basis.
In sum, these are only preferred embodiment of the present invention, be not intended to limit protection scope of the present invention.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (2)
1., for an optical imagery matching detection method for spaceborne expression type PCB quality of welding spot, it is characterized in that, concrete step is:
Step 101, to find from standard database according to the PCB information of element under test and be applicable to the template image of current element under test;
Step 102, CCD is made to be positioned at the dead ahead of element under test, and the spacing of adjustment CCD and element under test, on the image that CCD is gathered, the size of element under test is identical with the size of element under test on template image; CCD gathers element under test image, and is defined as image to be checked;
Step 103, be first w × h by size, form is that the template image of RGB24 converts 8 constant gray level images of size to; Template image is divided into m × n image block again, each block size is b × b, i.e. m=w/b, n=h/b; Ask the pixel average of each image block, obtain the pixel average matrix P that size is m × n;
Step 104, be W × H by size, form is that the image to be checked of RGB24 converts 8 constant gray level images of size to; Again image to be checked is divided into M × N number of image block, each block size is b × b, i.e. M=W/b, N=H/b; Ask the pixel average of each image block, obtain the pixel average matrix Q that size is M × N;
Step 105, initial time two matrixes initial point overlap, then order matrix P is in the enterprising line slip of matrix Q, often slides once, calculates the degree of correlation between two matrixes
when the degree of correlation calculated is less than setting threshold value, stops sliding, judge that the solder joint of this image to be checked meets the demands, otherwise continue to slide, when all relative position situations of sliding, the degree of correlation of two matrixes is still not less than setting threshold value, then judge that the solder joint of image to be checked does not meet the demands.
2. the optical imagery matching detection method of quality of welding spot according to claim 1, it is characterized in that, when element under test is too large, when all details of element under test cannot be represented in the piece image that CCD gathers, need to gather multiple image by mobile CCD, and multiple image is spliced, obtain image to be checked, the acquisition process of this image to be checked is:
In whole splicing, CCD is according to the image of acquisition order element under test from top to bottom, from left to right;
Step 201, using CCD gather the first width as splicing benchmark image, gather the image of the next position with seasonal CCD, and enter step 202;
Step 202, judge that whether image that CCD gathers is the image of element under test left column, if so, then enter step 203, otherwise enter step 204;
Step 203, the image gathered with current C CD is for template image, with its lower images for target image, on selected template image, a pixel overlaps with a pixel on target image, respectively to upper right, bottom right, upper left, lower-left movable platen image, the often mobile degree of correlation once calculating two picture registration positions, judge whether S the mobile Minimum relevance weight obtained is less than setting threshold value, if, then the position relationship of two images during Minimum relevance weight is defined as the best stitching position of two width images, two width images are spliced by best stitching position, otherwise again obtain a width ccd image and calculate the degree of correlation again, until two width images splice with best stitching position,
Step 204, the image gathered with current C CD is for template image, with its left-side images for target image, on selected template image, a pixel overlaps with a pixel on target image, respectively to upper right, bottom right, upper left, lower-left movable platen image, the often mobile degree of correlation once calculating two picture registration positions, judge whether S the mobile Minimum relevance weight obtained is less than setting threshold value, if, then the position relationship of two images during Minimum relevance weight is defined as the best stitching position of two width images, two width images are spliced by best stitching position, otherwise again obtain a width ccd image and calculate the degree of correlation again, until two width images splice with best stitching position,
Step 205, judge that whether spliced image to be checked is complete, if imperfect, then CCD gathers the image of the next position, and returns step 202.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210332167.9A CN102914549B (en) | 2012-09-10 | 2012-09-10 | Optical image matching detection method aiming at satellite-borne surface exposed printed circuit board (PCB) soldering joint quality |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210332167.9A CN102914549B (en) | 2012-09-10 | 2012-09-10 | Optical image matching detection method aiming at satellite-borne surface exposed printed circuit board (PCB) soldering joint quality |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102914549A CN102914549A (en) | 2013-02-06 |
| CN102914549B true CN102914549B (en) | 2015-03-25 |
Family
ID=47613011
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210332167.9A Active CN102914549B (en) | 2012-09-10 | 2012-09-10 | Optical image matching detection method aiming at satellite-borne surface exposed printed circuit board (PCB) soldering joint quality |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102914549B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104535587A (en) * | 2014-12-23 | 2015-04-22 | 安徽科鸣三维科技有限公司 | PCBA solder joint inspection method based on machine vision |
| CN105184793B (en) * | 2015-09-02 | 2018-01-16 | 广东电网有限责任公司汕尾供电局 | A kind of electric energy meter sample appearance and pcb board element testing method |
| CN105389818B (en) * | 2015-11-12 | 2018-11-27 | 广州视源电子科技股份有限公司 | The localization method and system of element |
| CN105588840B (en) * | 2015-12-04 | 2019-01-25 | 广州视源电子科技股份有限公司 | A kind of electronic units fix method and device |
| CN106651802B (en) * | 2016-12-24 | 2019-10-18 | 大连日佳电子有限公司 | Machine vision scolding tin position finding and detection method |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6771807B2 (en) * | 2000-01-18 | 2004-08-03 | Solvision Inc. | Method and system for detecting defects on a printed circuit board |
| CN101136015A (en) * | 2006-09-01 | 2008-03-05 | 北大方正集团有限公司 | Method for calculating similarity between images |
| CN101334266A (en) * | 2008-07-18 | 2008-12-31 | 北京优纳科技有限公司 | Circuit board defect off-line checking method based on large-capacity image storage technology |
| CN101895693A (en) * | 2010-06-07 | 2010-11-24 | 北京高森明晨信息科技有限公司 | Method and device for generating panoramic image |
| CN101901481A (en) * | 2010-08-11 | 2010-12-01 | 深圳市蓝韵实业有限公司 | Image mosaic method |
| CN201886521U (en) * | 2010-04-16 | 2011-06-29 | 广东工业大学 | Fast image splicing system |
| CN101477066B (en) * | 2009-01-09 | 2012-02-01 | 华南理工大学 | Circuit board element mounting/welding quality detection method and system based on super-resolution image reconstruction |
| CN102486831A (en) * | 2010-12-03 | 2012-06-06 | 江南大学 | Gray level image correlation matching algorithm for digital signal processor |
| CN102486829A (en) * | 2010-12-01 | 2012-06-06 | 鸿富锦精密工业（深圳）有限公司 | Image analysis system and method |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5191054B2 (en) * | 2009-01-09 | 2013-04-24 | 日本プラスト株式会社 | Cover body of airbag device and airbag device |
| JP5300670B2 (en) * | 2009-09-14 | 2013-09-25 | 株式会社東芝 | Pattern inspection apparatus and manufacturing method of structure having pattern |
-
2012
- 2012-09-10 CN CN201210332167.9A patent/CN102914549B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6771807B2 (en) * | 2000-01-18 | 2004-08-03 | Solvision Inc. | Method and system for detecting defects on a printed circuit board |
| CN101136015A (en) * | 2006-09-01 | 2008-03-05 | 北大方正集团有限公司 | Method for calculating similarity between images |
| CN101334266A (en) * | 2008-07-18 | 2008-12-31 | 北京优纳科技有限公司 | Circuit board defect off-line checking method based on large-capacity image storage technology |
| CN101477066B (en) * | 2009-01-09 | 2012-02-01 | 华南理工大学 | Circuit board element mounting/welding quality detection method and system based on super-resolution image reconstruction |
| CN201886521U (en) * | 2010-04-16 | 2011-06-29 | 广东工业大学 | Fast image splicing system |
| CN101895693A (en) * | 2010-06-07 | 2010-11-24 | 北京高森明晨信息科技有限公司 | Method and device for generating panoramic image |
| CN101901481A (en) * | 2010-08-11 | 2010-12-01 | 深圳市蓝韵实业有限公司 | Image mosaic method |
| CN102486829A (en) * | 2010-12-01 | 2012-06-06 | 鸿富锦精密工业（深圳）有限公司 | Image analysis system and method |
| CN102486831A (en) * | 2010-12-03 | 2012-06-06 | 江南大学 | Gray level image correlation matching algorithm for digital signal processor |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102914549A (en) | 2013-02-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102914549B (en) | Optical image matching detection method aiming at satellite-borne surface exposed printed circuit board (PCB) soldering joint quality | |
| CN105571502B (en) | The measurement method of weld gap in Friction Stir Welding | |
| CN105538345B (en) | A kind of puma manipulator and positioning assembly method based on many camera lenses | |
| CN106485275B (en) | A method of realizing that cover-plate glass is bonded with liquid crystal display positioning | |
| US20180357788A1 (en) | UAV Inspection Method for Power Line Based on Human Visual System | |
| CN100547351C (en) | A kind of machine vision localization method | |
| CN105674910B (en) | A kind of ultra-large type plate shearing machine plate cutting boundary curve detecting system and method | |
| CN104256882B (en) | Based on reconstituted tobacco ratio measuring method in the pipe tobacco of computer vision | |
| CN102589516B (en) | Dynamic distance measuring system based on binocular line scan cameras | |
| CN104483331A (en) | Three-dimensional detection method, three-dimensional detection device and three-dimensional detection system for connector contact pin | |
| CN108469437B (en) | Method and device for detecting defects of float glass | |
| CN104198324A (en) | Computer vision-based method for measuring proportion of cut leaves in cut tobacco | |
| CN106501272A (en) | Machine vision scolding tin position detecting system | |
| CN109813728A (en) | A kind of circuit board solder joint detection method and system | |
| CN114798360A (en) | Real-time detection method for PCB dispensing and related device | |
| CN104677782A (en) | Machine vision online detection system and method for electric connector shell | |
| DE102019124810A1 (en) | Image processing device and image processing method | |
| CN102074031A (en) | Standard establishment method for observational check machine of printed circuit board | |
| CN105023018A (en) | Jet code detection method and system | |
| CN104019752B (en) | The thickness evenness detection method of display screen, Apparatus and system | |
| TW419634B (en) | Automatic detection system and method using bar code positioning | |
| CN206470205U (en) | Machine vision scolding tin assisted detection system | |
| JP6960252B2 (en) | Maintenance management method for image analyzers and railway equipment parts | |
| CN105424708B (en) | Plate glass insurance fiber tube fusable links mass defect detection method | |
| CN107977953A (en) | Workpiece conductive features inspection method and workpiece conductive features check system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |