Research of laser pointing location algorithm based on neighborhood characteristics feature

WANG Bo; LIU Xiaodong; LI Junhao; CHEN Taiyu; LIU Ronglin

doi:10.7510/jgjs.issn.1001-3806.2019.05.001

LASER TECHNOLOGY > 2019 > 43(5): 591-596. > DOI: 10.7510/jgjs.issn.1001-3806.2019.05.001

WANG Bo, LIU Xiaodong, LI Junhao, CHEN Taiyu, LIU Ronglin. Research of laser pointing location algorithm based on neighborhood characteristics feature[J]. LASER TECHNOLOGY, 2019, 43(5): 591-596. DOI: 10.7510/jgjs.issn.1001-3806.2019.05.001

Citation:

PDF (1815 KB)

Research of laser pointing location algorithm based on neighborhood characteristics feature

National Engineering Research Center for Laser Processing, Huazhong University of Science and Technology, Wuhan 430074, China

More Information

Received Date: January 13, 2019
Revised Date: January 27, 2019
Published Date: September 24, 2019

Graphical Abstract

Abstract

Abstract

In order to solve the difficult problem of locating large size multi-blind holes in laser processing, local pictures were taken by industrial cameras. According to the structure and distribution characteristics of blind holes in meshes, blind holes in local images were detected by least square fitting circle method. Neighborhood feature was used to find feature points in a network. By using feature point matching to realize local localization as a whole, the precise and efficient positioning of the workpiece was realized. The results show that, neighborhood feature method has a positioning accuracy of 0.02mm for blind holes in meshes. Effective positioning of blind holes is realized. It solves the problem of difficult positioning of dot processing parts. This study provides a basis for further research on laser processing in blind holes.
- laser technique,
- point location,
- least square method,
- neighborhood characteristics feature

FullText(HTML)

References (21)

References

[1]	MA X D. Software design of intelligent laser flying processing based on OpenCV visual measurement[D]. Wuhan: Huazhong University of Science and Technology, 2016: 1-5(in Chinese).
[2]	LI Q. Some research on laser micromachining applied in electronic industry[D]. Hangzhou: Zhejiang University, 2010: 1-23(in Chinese).
[3]	SUN Sh F, LIAO H P, WU X H, et al. Experimental study about micro hole processing by picosecond laser[J]. Laser Technology, 2018, 42(2):234-238(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jgjs201802018
[4]	WEN H, WANG M J, TANG P Sh. An algorithm on graphic joining[J]. Computer Applications and Software, 2000, 17(2):26-29(in Chinese).
[5]	GUO J. The research of binarization method based on non-uniform illumination images[D]. Wuhan: Wuhan University of Science and Technology, 2013: 5-43(in Chinese).
[6]	YANG K, ZENG L B, WANG D Ch. A fast arithmetic for the erosion and dilation operations of mathematical morphology[J]. Computer Engineering and Applications, 2005, 41(34):54-56(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjgcyyy200534018
[7]	SHEN X P, PENG G, YUAN Zh Q. Insulator location method based on Hough transformation and RANSAC algorithm[J]. Electronic Measurement Technology, 2017, 40(6):138-143(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dzcljs201706030
[8]	LIU G Ch, DENG G W. Measurement of geometric characteristics of the electronic component based on OpenCV[J]. Information Technology, 2015(7):165-169(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=xxjs201507043
[9]	LIU F L, QIAO G F, ZOU B. Precise measurement of circles in industrial computed tomographic images[J]. Optics and Precision Engineering, 2009, 17(11):2842-2848(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gxjmgc200911032
[10]	MAO Q Zh, PAN Zh M, GAO W W. Using iterative hough round transform and connected areato count steel bars reliabley[J]. Geomatic and Information Science of Wuhan University, 2014, 39(3):373-378(in Chinese). http://en.cnki.com.cn/Article_en/CJFDTotal-WHCH201403025.htm
[11]	XU L. Randomized Hough transform (RHT); basic mechanisms, algorithms, and computational complexities[J]. Cvgip Image Understanding, 1993, 57(2):131-154. DOI: 10.1006/ciun.1993.1009
[12]	PHILIP K P, DOVE E L, McPHERSON D D, et al. The fuzzy Hough transform-feature extraction in medical images[J]. IEEE Transactions on Medical Imaging, 1994, 13(2):235-240. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=1cb3dd3f76057de0f37d11df47dec360
[13]	LIN J L, SHI Q Y. Circle recognition through a point hough transformation[J]. Computer Engineering, 2003, 29(11):17-18(in Ch-inese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjgc200311007
[14]	AN P Y. Researsh on detection technology of multi-circle workpiece based on machine vision[D]. Hangzhou: Zhejiang Sci-Tech University, 2018: 35-42(in Chinese).
[15]	YU P, JIANG L X, WANG A Ch, et al. Center of circle detection of the edge missing circle[J]. Geomatics Spatial Information Technology, 2018, 41(7):207-211(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dbch201807058
[16]	ZHANG X Q, WANG J J, JIANG L Y. Circle recognition algorithm based on freeman chain code[J]. Computer Engineering, 2007, 33(15):196-198(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjgc200715069
[17]	CHU G L. Study on the key technologies of automatic identification for cooperative target on spacecraft[D]. Changchun: Changchun Institute of Optics, Fine Mehcanics and Physics, Chinese Academy of Sciences, 2015: 13-30(in Chinese).
[18]	TANG L L, ZHANG Q C, HU S. An improved algorithm for Canny edge detection with adaptive threshold[J]. Opto-Electronic Engineering, 2011, 38(5):127-132(in Chinese).
[19]	SUZUKI S, BE K. Topological structural analysis of digitized binary images by border following[J]. Computer Vision Graphics and Image Processing, 1985, 30(1):32-46. DOI: 10.1016/0734-189X(85)90016-7
[20]	ZHAO L L, GENG G H, LI K, et al. Images matching algorithm based on SURF and fast approximate nearest neighbor search[J]. Application Research of Computers, 2013, 30(3):921-923(in Ch-inese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=jsjyyyj201303072
[21]	GAO J, WU Y F, WU K, et al. Image matching method based on corner detection[J]. Chinese Journal of Scientific Instrument, 2013, 34(8):1717-1725(in Chinese). http://d.old.wanfangdata.com.cn/Periodical/yqyb201308006

[1]	LIAO Houzhang, KONG Yong, ZHANG He, WU Huihui, TONG Xiaofan, ZHAO Li. Two-step phase unwrapping based on swin-UNet-denoise and least square method[J]. LASER TECHNOLOGY, 2024, 48(5): 752-758. DOI: 10.7510/jgjs.issn.1001-3806.2024.05.021
[2]	YUAN Longxiang, WANG Huaping, WANG Yang, LIU Jingzhi, QU Quanlei. Isolation switch on state of non-contact automatic detection method[J]. LASER TECHNOLOGY, 2024, 48(5): 734-738. DOI: 10.7510/jgjs.issn.1001-3806.2024.05.018
[3]	WU Teng, SHI Wenqing, XIE Linyi, GONG Meimei, HUANG Jiang, XIE Yuping, HE Kuanfang. Forming quality control method of laser cladding Fe-based TiC composite coating[J]. LASER TECHNOLOGY, 2022, 46(3): 344-354. DOI: 10.7510/jgjs.issn.1001-3806.2022.03.008
[4]	QI Yongfeng, MA Zhongyu. Hyperspectral image classification method based on neighborhood spectra and probability cooperative representation[J]. LASER TECHNOLOGY, 2019, 43(4): 448-452. DOI: 10.7510/jgjs.issn.1001-3806.2019.04.003
[5]	ZHANG Jing, WU Youyu. Locating algorithm of optical fiber spot center based on FPGA[J]. LASER TECHNOLOGY, 2017, 41(5): 769-774. DOI: 10.7510/jgjs.issn.1001-3806.2017.05.030
[6]	MA Cuihong, CUI Jinlong. Quantitative analysis of composition in molten steel by LIBS based on improved partial least squares[J]. LASER TECHNOLOGY, 2016, 40(6): 876-881. DOI: 10.7510/jgjs.issn.1001-3806.2016.06.021
[7]	BAO Hong, ZENG Haitao, BAI Yulei, HU Zhong, XIANG Zhicong, ZHOU Yanzhou, SHEN Zuochun. Blade trailing edge contour based on probability density least-square fitting[J]. LASER TECHNOLOGY, 2016, 40(4): 555-559. DOI: 10.7510/jgjs.issn.1001-3806.2016.04.021
[8]	CANG Guihua, YUE Jianping. Plane fitting of point clouds based on weighted total least square[J]. LASER TECHNOLOGY, 2014, 38(3): 307-310. DOI: 10.7510/jgjs.issn.1001-3806.2014.03.005
[9]	HAN Wan-peng, MENG Wen, LI Yun-xia, LI Da-wei. Correction model mixed with least-square and grid method for dual galvanometric scanning[J]. LASER TECHNOLOGY, 2012, 36(2): 179-182,187. DOI: 10.3969/j.issn.1001-3806.2012.02.008
[10]	Wang Haixian. A laser warning device using neighborhood related processing technique[J]. LASER TECHNOLOGY, 1998, 22(5): 303-308.

Cited By

Cited by

Periodical cited type(2)

1.	沈志飞，刘晓东，费锡磊，康恺. 基于点集贝塞尔曲线优化的激光振镜加工算法. 激光技术. 2021(05): 548-553 . 本站查看
2.	李霄，刘明. 一种钢包内壁温度场激光定位测量系统及其实验分析. 电子测量技术. 2020(05): 39-42 .

Other cited types(0)

Get Citation

PDF

XML

Article views (6) PDF downloads (12) Cited by(2)

Turn off MathJax

Article Contents

Abstract

References

Research of laser pointing location algorithm based on neighborhood characteristics feature

Abstract

References

Related Articles

Cited by

Periodical cited type(2)

Other cited types(0)

Catalog

Links：

Research of laser pointing location algorithm based on neighborhood characteristics feature

Abstract

References

Related Articles

Cited by

Periodical cited type(2)

Other cited types(0)

Catalog

Links：

Export File

Citation

Format

Content