CN107122783A - A kind of assembling connecting piece method for quickly identifying based on Corner Detection - Google Patents

A kind of assembling connecting piece method for quickly identifying based on Corner Detection Download PDF

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CN107122783A
CN107122783A CN201710256335.3A CN201710256335A CN107122783A CN 107122783 A CN107122783 A CN 107122783A CN 201710256335 A CN201710256335 A CN 201710256335A CN 107122783 A CN107122783 A CN 107122783A
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msubsup
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munderover
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CN107122783B (en
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刘桂雄
黄坚
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South China University of Technology SCUT
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00Arrangements for image or video recognition or understanding
    • G06V10/40Extraction of image or video features
    • G06V10/44Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/241Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2411Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00Indexing scheme relating to image or video recognition or understanding
    • G06V2201/06Recognition of objects for industrial automation

Abstract

The invention discloses a kind of assembling connecting piece method for quickly identifying based on Corner Detection, including sample angle point study statistics:Harris angle points, Shi Tomasi angle points, FAST angle points including gathering and detecting sample, and count the average value and standard deviation of various angle point quantity in the sample;High robust Corner Detection is quickly recognized:Including setting reliability requirement, the calculation formula of connector possible position numerical lower limits is set up automatically;Select the maximum Corner Detection Algorithm of the number average Corner Detection Algorithm minimum with standard deviation in angle point learns statistics, the method for meeting condition is set to detect image angle point to be checked, if image local area angle point quantity is higher than threshold requirement, it is probably greatly connector then to think to have, and extracts image and inputs to the detection of grader kind;Full Corner Detection is quickly recognized:Including the use of Harris angle points, Shi Tomasi angle points, three kinds of angular-point detection methods of FAST angle points, for the position with angle point, that is, think to be likely to be connector, extract image and input to the detection of grader kind.

Description

A kind of assembling connecting piece method for quickly identifying based on Corner Detection
Technical field
The present invention relates to assembling connecting piece method for quickly identifying, more particularly to a kind of assembling connecting piece based on Corner Detection Method for quickly identifying.
Background technology
Assembling refers to by defined technical requirements, and part or part are connected, semifinished or finished goods are made Technical process.Assembling is the important procedure of product manufacture, and the quality of assembling, the quality to product plays a decisive role. Assembling quality is discussed, carried out in the case where all Assembly parts are certified products, install correct precondition, therefore in detection production Before product assembling quality, it is necessary to check for misloading and the part of neglected loading.Because Assembly part, connector are more, assembling detection pair As variation, accuracy, uniformity and real-time to detection technique propose higher requirement and challenge.Relative to whole dress With product, its connector size is smaller, often complete in the picture, therefore the geometric figure that standard connector can be closed is retouched State, and the geometric figure closed certainly exists angle point.
The general recognition methods having to the method that objects in images is identified based on classification with based on the identification side matched Method.It is computationally intensive using the method for classification, but precision it is high, with generalization ability, also have in the case of to provide sample compared with Good recognition accuracy, such as piston of automobile assembling quality visual detecting system (ZL201010543006.5) can be disposably automatic right Piston of automobile top surface character, piston ring is assembled, and the content such as graphite linings integrality carries out the vision-based detection based on digital picture;Vision Detection method (201610496560.X) allows the bowlder on the image for detecting product to be checked to improve the center of circle and radius is extracted The degree of accuracy and speed, and then improve extraction efficiency;Braking automobile master cylinder piston surface quality machine vision detection device (201210348279.3) quick detection for being automatically performed piston face mass defect can be realized, the detection knot of surface quality is provided Really.Recognition methods based on inherent feature is good to specific parts Detection results, if object variation, must be by professional vision Testing staff detects feature again, and flexibility is poor.Recognition methods flexibility based on matching is stronger, for not setting in advance Situation can not then detect, it is narrower using scope.Patent of the present invention for connector size it is smaller, be in the picture it is complete, It can be described with the geometric figure of closing, the characteristics of certainly existing angle point.Realize that assembling connecting piece is quickly known based on Corner Detection Not, the efficiency of the recognition methods based on classification can be effectively improved.
The content of the invention
In order to solve the above technical problems, it is an object of the invention to provide a kind of assembling connecting piece based on Corner Detection is quick Recognition methods.
The purpose of the present invention is realized by following technical scheme:
A kind of assembling connecting piece method for quickly identifying based on Corner Detection, comprises the following steps:
Step A samples angle point study statistics;Including gather and detect the Harris angle points of sample, Shi-Tomasi angle points, FAST angle points, and count the average value and standard deviation of various angle point quantity in the sample;
Step B high robust Corner Detections are quickly recognized;Including setting reliability requirement, connector possible position is set up automatically The calculation formula of numerical lower limits;Select the Corner Detection Algorithm and standard deviation of the number average maximum in angle point learns statistics most Small Corner Detection Algorithm, makes the method for meeting condition detect image angle point to be checked, if image local area angle point quantity is higher than Threshold requirement, then it is assumed that with being probably greatly connector, extracts image and inputs to the detection of grader kind;
Step C is complete, and Corner Detection is quickly recognized;Including the use of Harris angle points, Shi-Tomasi angle points, FAST angle points three Angular-point detection method is planted, for the position with angle point, that is, thinks to be likely to be connector, extracts image and input to grader kind Detection.
Compared with prior art, one or more embodiments of the invention can have the following advantages that:
Relative to whole assembling product, the size of connector is smaller, often complete in the picture, can be several with closing What figure description, certainly exists angle point, and invention is based on this hypothesis, it is possible to achieve the various connectors of assembly process are quickly known Not, for do not have sample set detection means, it is probably connector image that can quickly filter out, so as to improve Test equipment detection efficiency and real-time.
Brief description of the drawings
Fig. 1 is the assembling connecting piece method for quickly identifying flow chart based on Corner Detection;
Fig. 2 is assembling connecting piece model top view;
Fig. 3 is the quick recognition effect figure of assembling connecting piece based on Corner Detection.
Embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with embodiment and accompanying drawing to this hair It is bright to be described in further detail.
As shown in figure 1, being the assembling connecting piece method for quickly identifying flow based on Corner Detection, comprise the following steps:
Step 1 sample angle point study statistics:Including gather and detect the Harris angle points of sample, Shi-Tomasi angle points, FAST angle points, and count the average value and standard deviation of various angle point quantity in the sample;
Step 2 high robust Corner Detection is quickly recognized:Including setting reliability requirement, connector possible position is set up automatically The calculation formula of numerical lower limits;Select the Corner Detection Algorithm and standard deviation of the number average maximum in angle point learns statistics most Small Corner Detection Algorithm, makes the method for meeting condition detect image angle point to be checked, if image local area angle point quantity is higher than Threshold requirement, then it is assumed that with being probably greatly connector, extracts image and inputs to the detection of grader kind;
The full Corner Detection of step 3 is quickly recognized:Including the use of Harris angle points, Shi-Tomasi angle points, FAST angle points three Angular-point detection method is planted, for the position with angle point, that is, thinks to be likely to be connector, extracts image and input to grader kind Detection.
The sample collection stage of above-mentioned steps 1 specifically includes:
If sample set is { R1,R2…Ri…RI, if with RX、RYImage R is represented respectivelyiHorizontal stroke, ordinate scope, for Arbitrary sample image Ri, point p (x, y) set can be expressed as;
Ri=p (x, y) | x ∈ RX∧y∈RY}
If along direction w on image midpoint p (x, y)u,vGrey scale change value be Ex,yFor:
And the detection method such as Harris angle points, Shi-Tomasi angle points, FAST angle points is then to select different to point P (x, y) Wu,v, according to different Ex,yJudge P (x, y) whether as angle point;
Use Harris angle points, Shi-Tomasi angle points, 3 kinds of method detection sample set { R of FAST angle points1,R2…Ri…RI} It is respectively N to detect angle point quantity vectorH、NST、NF
N is calculated respectivelyHDesired value and variance E (NH)、D(NH);NSTDesired value and variance E (NST)、D(NST);NF's Desired value and variance E (NF)、D(NF)。
The high robust Corner Detection of above-mentioned steps 2 is quickly in identification, and setting confidence level requirement sets up connector possible automatically The calculation formula of number of positions lower limit;
The confidence level can divide multiple stage (c1,c2...) choose, then under different confidence levels, Harris angle point quantity Lower limit nTHCalculation formula is:
Shi-Tomasi angle point numerical lower limits nTSCalculation formula is:
FAST angle point numerical lower limits nTFCalculation formula is:
The full Corner Detection of above-mentioned steps 3 directly sets angle point numerical lower limits n in quickly recognizingT=1, use Harris angles Point, Shi-Tomasi angle points, 3 kinds of angular-point detection methods of FAST angle points, for the position with angle point, that is, think the company of being likely to be Fitting, extracts image and inputs to the detection of grader kind.
Fig. 2 is assembling connecting piece model top view;Fig. 3 is the quick recognition effect of assembling connecting piece based on Corner Detection Figure.
Although disclosed herein embodiment as above, described content is only to facilitate understanding the present invention and adopting Embodiment, is not limited to the present invention.Any those skilled in the art to which this invention pertains, are not departing from this On the premise of the disclosed spirit and scope of invention, any modification and change can be made in the implementing form and in details, But the scope of patent protection of the present invention, still should be subject to the scope of the claims as defined in the appended claims.

Claims (4)

1. a kind of assembling connecting piece method for quickly identifying based on Corner Detection, it is characterised in that methods described includes following step Suddenly:
Step A samples angle point study statistics:Harris angle points, Shi-Tomasi angle points, FAST including gathering and detecting sample Angle point, and count the average value and standard deviation of various angle point quantity in the sample;
Step B high robust Corner Detections are quickly recognized:Including setting reliability requirement, connector possible position quantity is set up automatically The calculation formula of lower limit;The selection maximum Corner Detection Algorithm of number average and standard deviation minimum in angle point learns statistics Corner Detection Algorithm, makes the method for meeting condition detect image angle point to be checked, if image local area angle point quantity is higher than threshold value It is required that, then it is assumed that with being probably greatly connector, extract image and input to the detection of grader kind;
Step C is complete, and Corner Detection is quickly recognized:Including the use of Harris angle points, Shi-Tomasi angle points, three kinds of angles of FAST angle points Point detecting method, for the position with angle point, that is, thinks to be likely to be connector, extracts image and inputs to the inspection of grader kind Survey.
2. the assembling connecting piece method for quickly identifying as claimed in claim 1 based on Corner Detection, it is characterised in that the step Sample collection is specifically included in rapid A:
If sample set is { R1,R2…Ri…RI, if with RX、RYImage R is represented respectivelyiHorizontal stroke, ordinate scope, for any Sample image Ri, point p (x, y) set can be expressed as;
Ri=p (x, y) | x ∈ RX∧y∈RY}
If along direction w on image midpoint p (x, y)u,vGrey scale change value be Ex,yFor:
<mrow> <msub> <mi>E</mi> <mrow> <mi>x</mi> <mo>,</mo> <mi>y</mi> </mrow> </msub> <mo>=</mo> <munder> <mo>&amp;Sigma;</mo> <mrow> <mi>u</mi> <mo>,</mo> <mi>v</mi> </mrow> </munder> <msub> <mi>w</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>v</mi> </mrow> </msub> <msup> <mrow> <mo>|</mo> <mrow> <msub> <mi>I</mi> <mrow> <mi>x</mi> <mo>+</mo> <mi>u</mi> <mo>,</mo> <mi>y</mi> <mo>+</mo> <mi>v</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>I</mi> <mrow> <mi>u</mi> <mo>,</mo> <mi>v</mi> </mrow> </msub> </mrow> <mo>|</mo> </mrow> <mn>2</mn> </msup> </mrow>
And the detection method such as Harris angle points, Shi-Tomasi angle points, FAST angle points is then to select different to point P (x, y) wu,v, according to different Ex,yJudge P (x, y) whether as angle point;
Use Harris angle points, Shi-Tomasi angle points, three kinds of method detection sample set { R of FAST angle points1,R2…Ri…RIDetection Angle point quantity vector is respectively NH、NS、NF
<mrow> <msub> <mi>N</mi> <mi>H</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <msubsup> <mi>n</mi> <mi>H</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>n</mi> <mi>H</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <mo>...</mo> <msubsup> <mi>n</mi> <mi>H</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>...</mo> <msubsup> <mi>n</mi> <mi>H</mi> <mrow> <mo>(</mo> <mi>I</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> </mrow>
<mrow> <msub> <mi>N</mi> <mi>S</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <msubsup> <mi>n</mi> <mi>S</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>n</mi> <mi>S</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <mo>...</mo> <msubsup> <mi>n</mi> <mi>S</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>...</mo> <msubsup> <mi>n</mi> <mi>S</mi> <mrow> <mo>(</mo> <mi>I</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> </mrow>
<mrow> <msub> <mi>N</mi> <mi>F</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <msubsup> <mi>n</mi> <mi>F</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>n</mi> <mi>F</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <mo>...</mo> <msubsup> <mi>n</mi> <mi>F</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>...</mo> <msubsup> <mi>n</mi> <mi>F</mi> <mrow> <mo>(</mo> <mi>I</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> </mrow>
N is calculated respectivelyHDesired value and variance E (NH)、D(NH);NSTDesired value and variance E (NS)、D(NS);NFDesired value With variance E (NF)、D(NF)。
3. the assembling connecting piece method for quickly identifying as claimed in claim 1 based on Corner Detection, it is characterised in that the step Rapid B high robusts Corner Detection is quickly in identification, and connector possible position numerical lower limits are set up in setting confidence level requirement automatically Calculation formula includes:
The confidence level can divide multiple stage (c1,c2...) choose, then under different confidence levels, Harris angle point numerical lower limits nTHCalculation formula is:
<mrow> <msub> <mi>n</mi> <mrow> <mi>T</mi> <mi>H</mi> </mrow> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msubsup> <mi>n</mi> <mi>H</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>-</mo> <mi>&amp;lambda;</mi> <mrow> <mo>(</mo> <mi>c</mi> <mo>)</mo> </mrow> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msup> <mrow> <mo>(</mo> <msubsup> <mi>n</mi> <mi>H</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <mrow> <mo>(</mo> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msubsup> <mi>n</mi> <mi>H</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> </mrow> </mtd> <mtd> <mrow> <mi>c</mi> <mo>&lt;</mo> <mn>100</mn> <mi>%</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mn>1</mn> </mtd> <mtd> <mrow> <mi>c</mi> <mo>=</mo> <mn>100</mn> <mi>%</mi> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
Shi-Tomasi angle point numerical lower limits nTSCalculation formula is:
<mrow> <msub> <mi>n</mi> <mrow> <mi>T</mi> <mi>S</mi> </mrow> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msubsup> <mi>n</mi> <mi>S</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>-</mo> <mi>&amp;lambda;</mi> <mrow> <mo>(</mo> <mi>c</mi> <mo>)</mo> </mrow> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msup> <mrow> <mo>(</mo> <msubsup> <mi>n</mi> <mi>S</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <mrow> <mo>(</mo> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msubsup> <mi>n</mi> <mi>S</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> </mrow> </mtd> <mtd> <mrow> <mi>c</mi> <mo>&lt;</mo> <mn>100</mn> <mi>%</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mn>1</mn> </mtd> <mtd> <mrow> <mi>c</mi> <mo>=</mo> <mn>100</mn> <mi>%</mi> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
FAST angle point numerical lower limits nTFCalculation formula is:
<mrow> <msub> <mi>n</mi> <mrow> <mi>T</mi> <mi>F</mi> </mrow> </msub> <mo>=</mo> <mrow> <mo>{</mo> <mrow> <mtable> <mtr> <mtd> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msubsup> <mi>n</mi> <mi>F</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>-</mo> <mi>&amp;lambda;</mi> <mrow> <mo>(</mo> <mi>c</mi> <mo>)</mo> </mrow> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msup> <mrow> <mo>(</mo> <msubsup> <mi>n</mi> <mi>F</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>-</mo> <msup> <mrow> <mo>(</mo> <munderover> <mo>&amp;Sigma;</mo> <mn>1</mn> <mi>I</mi> </munderover> <msubsup> <mi>n</mi> <mi>F</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> </mrow> </mtd> <mtd> <mrow> <mi>c</mi> <mo>&lt;</mo> <mn>100</mn> <mi>%</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mn>1</mn> </mtd> <mtd> <mrow> <mi>c</mi> <mo>=</mo> <mn>100</mn> <mi>%</mi> </mrow> </mtd> </mtr> </mtable> <mo>.</mo> </mrow> </mrow> </mrow>
4. the assembling connecting piece method for quickly identifying as claimed in claim 1 based on Corner Detection, it is characterised in that the step The full Corner Detections of rapid C quickly in identification, directly set angle point numerical lower limits nT=1, use Harris angle points, Shi-Tomasi angles Point, three kinds of angular-point detection methods of FAST angle points.
CN201710256335.3A 2017-04-19 2017-04-19 Method for quickly identifying assembly connector based on angular point detection Active CN107122783B (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108280430A (en) * 2018-01-24 2018-07-13 陕西科技大学 A kind of flow image-recognizing method
CN112884784A (en) * 2021-03-11 2021-06-01 南通大学 Image-based lens detection and front-back judgment method

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Publication number Priority date Publication date Assignee Title
WO2009068718A1 (en) * 2007-11-29 2009-06-04 Escribano Gonzalez Jesus Environmentally-friendly device for collecting plastic sheets from cultivated soil
CN102072910A (en) * 2010-11-13 2011-05-25 上海交通大学 Visual inspection system for automobile piston assembly quality
CN106338521A (en) * 2016-09-22 2017-01-18 华中科技大学 Additive manufacturing surface defect, internal defect and shape composite detection method and device

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009068718A1 (en) * 2007-11-29 2009-06-04 Escribano Gonzalez Jesus Environmentally-friendly device for collecting plastic sheets from cultivated soil
CN102072910A (en) * 2010-11-13 2011-05-25 上海交通大学 Visual inspection system for automobile piston assembly quality
CN106338521A (en) * 2016-09-22 2017-01-18 华中科技大学 Additive manufacturing surface defect, internal defect and shape composite detection method and device

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108280430A (en) * 2018-01-24 2018-07-13 陕西科技大学 A kind of flow image-recognizing method
CN108280430B (en) * 2018-01-24 2021-07-06 陕西科技大学 Flow image identification method
CN112884784A (en) * 2021-03-11 2021-06-01 南通大学 Image-based lens detection and front-back judgment method

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