CN108571928A - A kind of intermediate plate anchorage dimensional defects detection method based on machine vision - Google Patents

A kind of intermediate plate anchorage dimensional defects detection method based on machine vision Download PDF

Info

Publication number
CN108571928A
CN108571928A CN201810330740.XA CN201810330740A CN108571928A CN 108571928 A CN108571928 A CN 108571928A CN 201810330740 A CN201810330740 A CN 201810330740A CN 108571928 A CN108571928 A CN 108571928A
Authority
CN
China
Prior art keywords
intermediate plate
image
plate anchorage
anchorage
size
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201810330740.XA
Other languages
Chinese (zh)
Inventor
王健
唐滔
曾庆宁
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Guilin University of Electronic Technology
Original Assignee
Guilin University of Electronic Technology
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Guilin University of Electronic Technology filed Critical Guilin University of Electronic Technology
Priority to CN201810330740.XA priority Critical patent/CN108571928A/en
Publication of CN108571928A publication Critical patent/CN108571928A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/0006—Industrial image inspection using a design-rule based approach
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/13—Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/155—Segmentation; Edge detection involving morphological operators
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/187—Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G06T2207/20164—Salient point detection; Corner detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Image Analysis (AREA)

Abstract

The intermediate plate anchorage dimensional defects detection method based on machine vision that the invention discloses a kind of belonging to intermediate plate anchorage automatic measurement technique field, includes the following steps：Camera calibration；Image Acquisition；Image preprocessing；The extraction of ROI image；Corner Detection；Dimensional measurement；Qualification determination.The present invention can accurately detect the actual physical size of intermediate plate anchorage, improve intermediate plate anchorage automatic detection level, efficiently solve the problems, such as that current artificial detection speed is slow, efficiency is low, of high cost, to realize that intelligence production, intelligence manufacture are laid a good foundation.

Description

A kind of intermediate plate anchorage dimensional defects detection method based on machine vision
Technical field
The present invention relates to intermediate plate anchorage automatic measurement technique field more particularly to a kind of intermediate plate anchorages based on machine vision Dimensional defects detection method.
Background technology
With the development of prestressed anchor technology, intermediate plate anchorage (abbreviation intermediate plate) proportion in prestressed anchor engineering It is increasing, it is widely used in the construction of different types of rridges road construction, intermediate plate anchorage is the important base of prestress anchorage system One of plinth part, the quality of size directly affect the safety of prestressing force structures, and city is flowed into if there is the workpiece of dimensional defects , it may cause building that safety accident occurs when serious, greatly destroy social safety and people's property, it is same to give production enterprise Industry brings great economic loss and liability exposure.
Therefore, link is very important to the detection of intermediate plate anchorage dimensional defects.The detection used on production line at present Method is artificial detection, and deficiency is：Detection speed is slow, it is less efficient, of high cost, be easy to cause human error detection.
Invention content
In view of the deficiencies of the prior art, problem solved by the invention is how to solve that artificial detection speed is slow, is easy to make The problem of at human error.
In order to solve the above technical problems, the technical solution adopted by the present invention is a kind of intermediate plate anchorage ruler based on machine vision Very little defect inspection method, includes the following steps：
(1) camera calibration measures the practical ruler of horizontal direction using the intermediate plate anchorage object of benchmark as calibrated reference Very little DxWith corresponding pixel number NxBetween ratio Kx, measure the actual size D of vertical directionyWith corresponding pixel Number NyBetween ratio Ky, the correspondence of world coordinates and pixel coordinate is：
Wherein (i, j) is pixel coordinate, and (x, y) is the corresponding world coordinates of pixel coordinate；
(2) Image Acquisition acquires intermediate plate anchorage image under red bowl lamp source；
(3) image preprocessing, collected intermediate plate anchorage image carry out gradation conversion, filtering removal noise, enhancing image Contrast；
(4) extraction of ROI image, to intermediate plate anchorage image binaryzation, Connected area disposal$ and closed operation obtain bianry image, ROI region extraction is carried out to bianry image again；
(5) Corner Detection is as follows with Harris Corner Detection ROI region images：
A) gradient of image pixel in the x and y direction, and the product of the two are calculated, matrix M is obtained：
Wherein I (x, y) gray value, IxFor the gradient in the directions x of image I；IyFor the gradient in the directions y；
B) gaussian filtering is carried out to image, obtains new matrix M：
Wherein G is Gaussian template；
C) value for the angle point receptance function CRF that each pixel is corresponded on original image is calculated：
CRF (x, y)=det (M)-K (trace (M))2
Wherein, the determinant of det (M) representing matrixes M, the mark of trace (M) representing matrix, K are generally taken as 0.04；
D) Local Extremum is chosen；
E) given threshold chooses angle point, obtains angle point collection：corner(x,y)；
(6) dimensional measurement, diagonal point set corner (x, y) carry out camera calibration, and the angle point of object will be detected in ROI image The vertical range of air line distance or angle point to another two angle points line between position coordinates is converted into corresponding true geometric size, Full-size(d) calculation formula is as follows between two angle points：
Wherein A (m1,n1) and B (m2,n2) be image in arbitrary two angle point pixel coordinate, Δx=Kx(m2-m1)、Δy= Ky(n2-n1)、ΔABActual distance respectively between the horizontal component, vertical component and AB of actual distance；
(7) qualification determination, the differentiation of qualified products is carried out using the method for the upper lower deviation of setting, and discrimination formula is as follows：
Wherein, i={ 1,2,3,4,5 } respectively represents the basic parameter type of intermediate plate anchorage size, ftiIt is test intermediate plate anchor The a certain size parameter values of tool, fsiFor corresponding standard parameter optimal value, TiIt is to differentiate that the upper lower deviation allowed, the value decide To the containing degree of intermediate plate anchorage size, g (fti) be feature decision result function, when functional value be equal to 1 when, differentiate intermediate plate anchor It is qualification to have the dimensional parameters, otherwise sentences that its is unqualified, is all qualification and if only if all dimensional parameters of intermediate plate anchorage, just sentences Its other size qualification.
There is technical scheme of the present invention higher Detection accuracy and robustness, the accuracy rate of defects detection can reach 96%；Intermediate plate anchorage dimensional defects detection method based on machine vision, intermediate plate anchorage is introduced by machine vision metrology technology Dimensional measurement, testing process do not influenced by factors such as the experience of operating personnel, survey tool, fatigue strengths, ensure that survey The precision of amount, detection speed is fast, speed can reach 0.2 second every, be effectively improved intermediate plate anchorage work piece production automation The quality of degree and product.
Description of the drawings
Fig. 1 is the principle of the present invention flow chart.
Specific implementation mode
The specific implementation mode of the present invention is further described with reference to the accompanying drawings and examples, but is not to this hair Bright restriction.
Fig. 1 shows a kind of intermediate plate anchorage dimensional defects detection method based on machine vision, includes the following steps：
(1) camera calibration need to carry out camera calibration, the picture of intermediate plate anchorage image after the completion of image capturing system debugging Plain size conversion is mm size；Camera calibration in this method is demarcated using Pixel Dimensions；
Using the intermediate plate anchorage object of benchmark as calibrated reference, the actual size D of horizontal direction is measuredxWith it is corresponding Pixel number NxBetween ratio Kx, measure the actual size D of vertical directionyWith corresponding pixel number NyBetween ratio Example Ky, the correspondence of world coordinates and pixel coordinate is：
Wherein (i, j) is pixel coordinate, and (x, y) is the corresponding world coordinates of pixel coordinate；
(2) Image Acquisition, CCD industrial cameras acquire intermediate plate anchorage image under red bowl lamp source；
(3) image preprocessing, collected intermediate plate anchorage image carry out gradation conversion, filtering removal noise, enhancing image Contrast；
(4) extraction of ROI image, to intermediate plate anchorage image binaryzation, Connected area disposal$ and closed operation obtain bianry image, ROI region extraction is carried out to bianry image again；
(5) Corner Detection is as follows with Harris Corner Detection ROI region images：
A) gradient of image pixel in the x and y direction, and the product of the two are calculated, matrix M is obtained：
Wherein I (x, y) gray value, IxFor the gradient in the directions x of image I；IyFor the gradient in the directions y；
B) gaussian filtering is carried out to image, obtains new matrix M：
Wherein G is Gaussian template；
C) value for the angle point receptance function CRF that each pixel is corresponded on original image is calculated：
CRF (x, y)=det (M)-K (trace (M))2
Wherein, the determinant of det (M) representing matrixes M, the mark of trace (M) representing matrix, K are generally taken as 0.04；
D) Local Extremum is chosen；
E) given threshold chooses angle point, obtains angle point collection：corner(x,y)；
(6) dimensional measurement, diagonal point set corner (x, y) carry out camera calibration, and the angle point of object will be detected in ROI image The vertical range of air line distance or angle point to another two angle points line between position coordinates is converted into corresponding true geometric size, Full-size(d) calculation formula is as follows between two angle points：
Wherein A (m1,n1) and B (m2,n2) be image in arbitrary two angle point pixel coordinate, Δx=Kx(m2-m1)、Δy= Ky(n2-n1)、ΔABActual distance respectively between the horizontal component, vertical component and AB of actual distance；
(7) qualification determination, the differentiation of qualified products is carried out using the method for the upper lower deviation of setting, and discrimination formula is as follows：
Wherein, i={ 1,2,3,4,5 } respectively represents the basic parameter type of intermediate plate anchorage size, ftiIt is test intermediate plate anchor The a certain size parameter values of tool, fsiFor corresponding standard parameter optimal value, TiIt is to differentiate that the upper lower deviation allowed, the value decide To the containing degree of intermediate plate anchorage size, g (fti) be feature decision result function, when functional value be equal to 1 when, differentiate intermediate plate anchor It is qualification to have the dimensional parameters, otherwise sentences that its is unqualified, is all qualification and if only if all dimensional parameters of intermediate plate anchorage, just sentences Its other size qualification.Detailed description is made that embodiments of the present invention above in association with attached drawing, but the present invention is not limited to institute The embodiment of description.To those skilled in the art, without departing from the principles and spirit of the present invention, to this A little embodiments carry out various change, modification, replacement and modification and still fall in protection scope of the present invention.

Claims (4)

1. a kind of intermediate plate anchorage dimensional defects detection method based on machine vision, it is characterised in that：Include the following steps：
(1) camera calibration measures the actual size D of horizontal direction using the intermediate plate anchorage object of benchmark as calibrated referencex With corresponding pixel number NxBetween ratio Kx, measure the actual size D of vertical directionyWith corresponding pixel number Ny Between ratio Ky, the correspondence of world coordinates and pixel coordinate is：
Wherein (i, j) is pixel coordinate, and (x, y) is the corresponding world coordinates of pixel coordinate；
(2) Image Acquisition acquires intermediate plate anchorage image under red bowl lamp source；
(3) image preprocessing, collected intermediate plate anchorage image carry out gradation conversion, filtering removal noise, enhancing image comparison Degree；
(4) extraction of ROI image obtains bianry image, right again to intermediate plate anchorage image binaryzation, Connected area disposal$ and closed operation Bianry image carries out ROI region extraction；
(5) Corner Detection, with Harris Corner Detection ROI region images；
(6) dimensional measurement, diagonal point set corner (x, y) carry out camera calibration, and the corner location of object will be detected in ROI image The vertical range of air line distance or angle point to another two angle points line between coordinate is converted into corresponding true geometric size；
(7) qualification determination carries out the differentiation of qualified products using the method for the upper lower deviation of setting.
2. the intermediate plate anchorage dimensional defects detection method according to claim 1 based on machine vision, it is characterised in that：Step Suddenly in (5), the Harris Corner Detections are as follows：
A) gradient of image pixel in the x and y direction, and the product of the two are calculated, matrix M is obtained：
Wherein I (x, y) gray value, IxFor the gradient in the directions x of image I；IyFor the gradient in the directions y；
B) gaussian filtering is carried out to image, obtains new matrix M：
Wherein G is Gaussian template；
C) value for the angle point receptance function CRF that each pixel is corresponded on original image is calculated：
CRF (x, y)=det (M)-K (trace (M))2
Wherein, the determinant of det (M) representing matrixes M, the mark of trace (M) representing matrix, K are generally taken as 0.04；
D) Local Extremum is chosen；
E) given threshold chooses angle point, obtains angle point collection：corner(x,y).
3. the intermediate plate anchorage dimensional defects detection method according to claim 1 or 2 based on machine vision, feature exist In：In step (6), full-size(d) between two angle points, calculation formula is as follows：
Wherein A (m1,n1) and B (m2,n2) be image in arbitrary two angle point pixel coordinate, Δx=Kx(m2-m1)、Δy=Ky(n2- n1)、ΔABActual distance respectively between the horizontal component, vertical component and AB of actual distance.
4. the intermediate plate anchorage dimensional defects detection method according to claim 1 or 2 based on machine vision, feature exist In：In step (7), discrimination formula is as follows：
Wherein, i={ 1,2,3,4,5 } respectively represents the basic parameter type of intermediate plate anchorage size, ftiIt is test intermediate plate anchorage A certain size parameter values, fsiFor corresponding standard parameter optimal value, TiIt is to differentiate the upper lower deviation allowed, which decides to folder The containing degree of piece anchorage size, g (fti) be feature decision result function, when functional value be equal to 1 when, differentiate intermediate plate anchorage should Dimensional parameters are qualification, otherwise sentence that its is unqualified, are all qualification and if only if all dimensional parameters of intermediate plate anchorage, just differentiate it Size qualification.
CN201810330740.XA 2018-04-13 2018-04-13 A kind of intermediate plate anchorage dimensional defects detection method based on machine vision Pending CN108571928A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810330740.XA CN108571928A (en) 2018-04-13 2018-04-13 A kind of intermediate plate anchorage dimensional defects detection method based on machine vision

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810330740.XA CN108571928A (en) 2018-04-13 2018-04-13 A kind of intermediate plate anchorage dimensional defects detection method based on machine vision

Publications (1)

Publication Number Publication Date
CN108571928A true CN108571928A (en) 2018-09-25

Family

ID=63574766

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810330740.XA Pending CN108571928A (en) 2018-04-13 2018-04-13 A kind of intermediate plate anchorage dimensional defects detection method based on machine vision

Country Status (1)

Country Link
CN (1) CN108571928A (en)

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109472773A (en) * 2018-09-29 2019-03-15 广东工业大学 A kind of defect inspection method for LED
CN109840891A (en) * 2019-01-07 2019-06-04 重庆工程学院 A kind of intelligence strand tapered anchorage and prestressed monitoring method and detection system, terminal
CN110500951A (en) * 2019-06-04 2019-11-26 湘潭大学 A kind of lamp lens shell sizes detection method based on machine vision
CN110533731A (en) * 2019-08-30 2019-12-03 无锡先导智能装备股份有限公司 The scaling method of camera resolution and the caliberating device of camera resolution
CN111175024A (en) * 2020-01-03 2020-05-19 昆山丘钛微电子科技有限公司 Test method of infrared laser
CN112233119A (en) * 2020-12-16 2021-01-15 常州微亿智造科技有限公司 Workpiece defect quality inspection method, device and system
CN113011719A (en) * 2021-03-03 2021-06-22 苏州盛弘森科技有限公司 Visual quality detection method and system for industrial production
CN114820612A (en) * 2022-06-29 2022-07-29 南通恒强轧辊有限公司 Roller surface defect detection method and system based on machine vision

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102426785A (en) * 2011-11-18 2012-04-25 东南大学 Traffic flow information perception method based on contour and local characteristic point and system thereof
CN103295003A (en) * 2013-06-07 2013-09-11 北京博思廷科技有限公司 Vehicle detection method based on multi-feature fusion
CN106174830A (en) * 2016-06-30 2016-12-07 西安工程大学 Garment dimension automatic measurement system based on machine vision and measuring method thereof
CN106643549A (en) * 2017-02-07 2017-05-10 泉州装备制造研究所 Machine vision-based tile size detection method
CN107490583A (en) * 2017-09-12 2017-12-19 桂林电子科技大学 A kind of intermediate plate defect inspection method based on machine vision
CN107506688A (en) * 2017-07-18 2017-12-22 西安电子科技大学 Harris Corner Detection image pyramid palmmprint ROI recognition methods

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102426785A (en) * 2011-11-18 2012-04-25 东南大学 Traffic flow information perception method based on contour and local characteristic point and system thereof
CN103295003A (en) * 2013-06-07 2013-09-11 北京博思廷科技有限公司 Vehicle detection method based on multi-feature fusion
CN106174830A (en) * 2016-06-30 2016-12-07 西安工程大学 Garment dimension automatic measurement system based on machine vision and measuring method thereof
CN106643549A (en) * 2017-02-07 2017-05-10 泉州装备制造研究所 Machine vision-based tile size detection method
CN107506688A (en) * 2017-07-18 2017-12-22 西安电子科技大学 Harris Corner Detection image pyramid palmmprint ROI recognition methods
CN107490583A (en) * 2017-09-12 2017-12-19 桂林电子科技大学 A kind of intermediate plate defect inspection method based on machine vision

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109472773A (en) * 2018-09-29 2019-03-15 广东工业大学 A kind of defect inspection method for LED
CN109840891A (en) * 2019-01-07 2019-06-04 重庆工程学院 A kind of intelligence strand tapered anchorage and prestressed monitoring method and detection system, terminal
CN110500951A (en) * 2019-06-04 2019-11-26 湘潭大学 A kind of lamp lens shell sizes detection method based on machine vision
CN110500951B (en) * 2019-06-04 2021-03-09 湘潭大学 Car light glass shell size detection method based on machine vision
CN110533731A (en) * 2019-08-30 2019-12-03 无锡先导智能装备股份有限公司 The scaling method of camera resolution and the caliberating device of camera resolution
CN111175024A (en) * 2020-01-03 2020-05-19 昆山丘钛微电子科技有限公司 Test method of infrared laser
CN112233119A (en) * 2020-12-16 2021-01-15 常州微亿智造科技有限公司 Workpiece defect quality inspection method, device and system
CN113011719A (en) * 2021-03-03 2021-06-22 苏州盛弘森科技有限公司 Visual quality detection method and system for industrial production
CN114820612A (en) * 2022-06-29 2022-07-29 南通恒强轧辊有限公司 Roller surface defect detection method and system based on machine vision
CN114820612B (en) * 2022-06-29 2022-09-02 南通恒强轧辊有限公司 Roller surface defect detection method and system based on machine vision

Similar Documents

Publication Publication Date Title
CN108571928A (en) A kind of intermediate plate anchorage dimensional defects detection method based on machine vision
CN109472822A (en) Dimension of object measurement method based on depth image processing
CN101526484B (en) Bearing defect detecting technique based on embedded-type machine vision
CN106770321B (en) A kind of plastic part defect inspection method based on multi-threshold section
CN109035232A (en) A kind of intermediate plate defect inspection method merged based on deep learning and machine vision
CN109001224A (en) Welding seam detection method and detection device
CN109752392A (en) A kind of pcb board defect type detection system and method
CN106643549A (en) Machine vision-based tile size detection method
CN108489394A (en) A kind of large-scale sheet metal works almost T-stable automatic detection device and method
CN109284718A (en) The recognition methods simultaneously of the more instrument in change visual angle towards crusing robot
EP1467176B1 (en) Inspection system and method
CN109785294A (en) A kind of pcb board defective locations detection system and method
CN111724358A (en) Concrete quality detection method and system based on image and convolutional neural network
CN109916922A (en) Mirror surface/class mirror article defect inspection method
Yang et al. An online detection system for aggregate sizes and shapes based on digital image processing
CN115597494A (en) Precision detection method and system for prefabricated part preformed hole based on point cloud
CN115656182A (en) Sheet material point cloud defect detection method based on tensor voting principal component analysis
Murao et al. Concrete crack detection using uav and deep learning
CN108416790A (en) A kind of detection method for workpiece breakage rate
CN204989067U (en) Image quality indicator
CN115615992B (en) Fireproof brick size measurement and defect detection method
CN110033444A (en) A kind of building structure surface crack automatic axial dimensioning method
CN113160145B (en) Detection method, detection device, detection apparatus, and computer-readable storage medium
CN113793321A (en) Casting surface defect dynamic detection method and device based on machine vision
CN108645865A (en) A kind of measurement method of the submerged-arc welding steel pipe weld seam amount of the being partially welded parameter based on CCD

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20180925