Vision measurement method based on Bayesian model and digital image correlation

XIE Junyu; XU Yangjian; WANG Xiaogui

doi:10.7510/jgjs.issn.1001-3806.2016.06.019

In order to operate 3-D measurement efficiently and accurately, a vision measurement method correlation was proposed based on Bayesian model and digital image. Digital image correlation was used to match the rectified images, which had the ability to improve the accuracy of traditional stereo matching method. The iterative initial disparity of digital image correlation was determined by Bayesian model to overcome the disadvantages of coarse-fine search. Based on the projecting relationship between the rectified image and the raw image, 3-D coordinates of the matched point were then calculated by the least square method. The results show that the proposed vision measurement method based on Bayesian model and digital image correlation has high accuracy and efficiency of 3-D vision measurement.

Vision measurement method based on Bayesian model and digital image correlation

Corresponding author: WANG Xiaogui, hpcwxg@zjut.edu.cn

1. College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310014, China

Received Date: 2015-11-05

Accepted Date: 2016-01-04

Available Online: 2016-11-25

Abstract: In order to operate 3-D measurement efficiently and accurately, a vision measurement method correlation was proposed based on Bayesian model and digital image. Digital image correlation was used to match the rectified images, which had the ability to improve the accuracy of traditional stereo matching method. The iterative initial disparity of digital image correlation was determined by Bayesian model to overcome the disadvantages of coarse-fine search. Based on the projecting relationship between the rectified image and the raw image, 3-D coordinates of the matched point were then calculated by the least square method. The results show that the proposed vision measurement method based on Bayesian model and digital image correlation has high accuracy and efficiency of 3-D vision measurement.

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Reference (14)

[1]	HAN Y H. Research on 3-D model reconstruction method based on binocular stereo vision[D]. Taiyuan:North University of China, 2014:8-20(in Chinese).
[2]	ROY S, COX I J. A maximum-flow formulation of the n-camera stereo correspondence problem[C]//Sixth International Conference on Computer Vision, 1998.New York,USA:IEEE, 1998:492.
[3]	SUN, H Y S J, ZHENG N N. Stereo matching using belief propagation[J]. IEEE Transactions on Pattern Analysis Machine Intelligence, 2003, 25(7):787-800.
[4]	SUTTON M A, MCNEIL S R, HELM J D, et al. Advances in two-dimensional and three-dimensional computer vision[J]. Photomechanics, 2000, 77(1):323-372.
[5]	YU Q F, LU H W, LIU X L. Precisely measurement and motion based on image[M].Beijing:Beijing Science Press, 2002:153-154(in Chinese).
[6]	GAO Y. Research on key technologies and applications of three-dimensional digital image correlation[D]. Hefei:University of Science and Technology of China, 2014:27-37(in Chinese).
[7]	GEIGER A, ROSER M, URTASUN R. Efficient large-scale stereo matching[C]//TenthAsian Conference on Computer Vision-volume Part Ⅰ, 2010.Berlin,Germany:Springer-Verlag, 2010:25-38.
[8]	LI M J, SU X Y. Stereo matching by means of digital speckle[J]. Laser Technology, 2004, 28(5):550-553(in Chinese).
[9]	ZHANG Z. A flexible new technique for camera calibration[J]. IEEE Transactions on Pattern Analysis Machine Intelligence, 2000, 22(11):1330-1334.
[10]	HEIKKILA J, SILVEN O. A four-step camera calibration procedure with implicit image correction[C]//IEEE Computer Society Conferenceon Computer Vision and Pattern Recognition, 1997.New York,USA:IEEE, 1997:1106-1112.
[11]	BRADSKI G R, KAEHLER A. Learning opencv-computer vision with the opencvlibrary[M].Sebastopol,CA,USA:O'Reilly Media,Inc,2008:467-476.
[12]	DEVERNAY F, FAUGERAS O. Computing differential properties of 3-D shapes from stereoscopic images without 3-D models[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition,1994.New York,USA:IEEE,1994:208-213.
[13]	VENDROUX G, KNAUSS W G. Submicron deformation field measurements:part 2. Improved digital image correlation[J]. Experimental Mechanics, 1998, 38(2):86-92.
[14]	GARCIA D, ORTEU J J, PRNAZZI L. A combined temporal tracking and stereo-correlation technique for accurate measurement of 3-D displacements:application to sheet metal forming[J]. Journal of Materials Processing Technology, 2002, 125(2):736-742.

Vision measurement method based on Bayesian model and digital image correlation

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