[1] Zhang Weizhong, Zhang Liyan, Wang Xiaoping, et al. Non-iterative image feature matching algorithmbased on reference point correspondences [J]. Journal of Southeast University (English Edition), 2007, 23 (2): 190-195. [doi:10.3969/j.issn.1003-7985.2007.02.008]

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Non-iterative image feature matching algorithmbased on reference point correspondences()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

23

Issue:

2007 2

Page:

190-195

Research Field:

Computer Science and Engineering

Publishing date:

2007-06-30

Info

Title:

Non-iterative image feature matching algorithmbased on reference point correspondences

Author(s):

Zhang Weizhong¹;  2;  Zhang Liyan²;  Wang Xiaoping²;  Ding Zhian²;  Zhou Ling²

¹College of Information Engineering, Qingdao University, Qingdao 266071, China
²Research Center of CAD/CAM Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Keywords:

reference points detection;  coded and non-coded target;  subpixel;  gray scale centroid;  point correspondence

PACS:

TP391

DOI:

10.3969/j.issn.1003-7985.2007.02.008

Abstract:

Based on the coded and non-coded targets, the targets are extracted from the images according to their size, shape and intensity etc., and thus an improved method to identify the unique identity(ID)of every coded target is put forward and the non-coded and coded targets are classified.Moreover, the gray scale centroid algorithm is applied to obtain the subpixel location of both uncoded and coded targets.The initial matching of the uncoded target correspondences between an image pair is established according to similarity and compatibility, which are based on the ID correspondences of the coded targets.The outliers in the initial matching of the uncoded target are eliminated according to three rules to finally obtain the uncoded target correspondences.Practical examples show that the algorithm is rapid, robust and is of high precision and matching ratio.

References:

[1] Kanade T, Okutomi M.A stereo matching algorithm with an adaptive window: theory and experiment[J].IEEE Trans on Pattern and Machine Intelligence, 1994, 16(9):920-932.
[2] Stefano L D, Marchionni M, Mattoccia S.A fast area-based stereo matching algorithm[J].Image and Vision Computing, 2004, 22(12):983-1005.
[3] Mount D M, Netanyahu N S, Moigne J L.Efficient algorithms for robust feature matching[J].Pattern Recognition, 1999, 8(6):17-38.
[4] Carcassoni M, Hancock E R.Correspondence matching with modal clusters[J].IEEE Trans on Pattern Analysis and Machine Intelligence, 2003, 25(12):1609-1615.
[5] Zhang Z, Deriche R, Faugeras O, et al.A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry. Rapport de Recherche n.2273 [R].Shophia-Antipoles:Unité de Recherce INRIA, 1994.
[6] Galo M, Tozzi C L.Feature-point based matching:a sequential approach based on relaxation labeling and relative orientation[J].Journal of WSCG, 2004, 12(1):1-8.
[7] Keith F, Anthon V, Ndimi B.An Inexpensive, automatic and accurate camera calibration method[C]//Proceedings of the Thirteenth Annual Symposium of the Pattern Recognition Association of South Africa.Cape Town, 2002:1205-1211.
[8] Xu J, Fang Z P, Malcolm A A, et al.A robust close-range photogrammetric system for industrial metrology[C]//Proc of the 7th International Conference on Control, Automation, Robotics and Vision.Singapore, 2002:114-119.
[9] Zhou Ling. Research on key technology of 3-D reconstruction based on multiple images by using one hand-held digital camera[D].Nanjing:Research Center of CAD/CAM Engineering of Nanjing University of Aeronautics and Astronautics, 2006.(in Chinese)

Memo

Memo:

Biography: Zhang Weizhong(1963—), male, professor, zhangwz_-01@163.com.

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