Copyright © 2006 The Institute of Electronics, Information and Communication Engineers
Special Section on Machine Vision Applications -- Papers -- Stereo and Multiple View Analysis |
A New Efficient Stereo Line Segment Matching Algorithm Based on More Effective Usage of the Photometric, Geometric and Structural Information
The authors are with Electrical Engineering Department, Amirkabir University of Technology, Tehran, Iran. E-mail: karimiankh{at}aut.ac.ir
In this paper, a new stereo line segment matching algorithm is presented. The main purpose of this algorithm is to increase efficiency, i.e. increasing the number of correctly matched lines while avoiding the increase of mismatches. In this regard, the reasons for the elimination of correct matches as well as the existence of the erroneous ones in some existing algorithms have been investigated. An attempt was also made to make efficient uses of the photometric, geometric and structural information through the introduction of new constraints, criteria, and procedures. Hence, in the candidate determination stage of the designed algorithm two new constraints, in addition to the reliable epipolar, maximum and minimum disparity and orientation similarity constraints were employed. In the process of disambiguation and final matches selection, being the main problem of the matching issue, regarding the employed constraints, criterion function and its optimization, it is a completely new development. The algorithm was applied to the images of several indoor scenes and its high efficiency illustrated by correct matching of 96% of the line segments with no mismatches.
Key Words: stereo vision, line segment, matching
Manuscript received November 1, 2005. Manuscript revised January 18, 2006.
References
[1] A. ghasemi and A. Raei, "Mobile robot navigation by stereo vision," ICEE 2004, 12th Iranian conference on electrical engineering, 2004.
[2] G. Karimian, Mobile robot localization by stereo vision, Amirkabir University, Ph.D. Thesis Report, 2005.
[3] E. Trucco and A. Verri, Introductory Techniques for 3-D Computer Vision, Prentice Hall, 1998.
[4] G. Medioni and R. Nevatia, "Segment-based stereo matching," Comput. Vis. Graph. Image Process., vol.31, no.3, pp.218, 1985.
[5] J.H. McIntosh and K.M. Mutch, "Matching straight lines," Comput. Vis. Graph. Image Process., vol.43, pp.386408, 1988.
[6] R.K.K. Yip and W.P. Ho, "Multi-level based stereo line matching with structural information using dynamic programming," ICIP'96, vol.2, pp.341344, 1996.
[7] S.D. Sharghi and F.A. Kamangar, "Geometric feature-based matching in stereo images," Proc. IEEE Information, Decision and Control, pp.6570, 1999.
[8] G. Pajares, J.M. de la Cruz, and J.A. Lopez-Orozco, "Relaxation labeling in stereo image matching," Elsevier Pattern Recognition J., vol.33, pp.5368, 2000.
[9] W.P. Ho and R.K.K. Yip, "A dynamic programming approach for stereo line matching with structural information," Proc. 13th International Conference on Pattern Recognition, no.1, pp.791794, 1996.
[10] S. Se, D. Lowe, and J. Little, "Mobile robot localization and mapping with uncertainty using scale-invariant visual landmarks," Int. J. Robot. Res., vol.21, no.8, pp.735758, 2002.
[11] M.C. Shin, D.B. Goldgof, K.W. Bowyer, and S. Nikiforou, "Comparison of edge detection algorithms using a structure from motion task," IEEE Trans. Syst., Man Cybern. B, Cybern., vol.31, no.4, pp.589601, 2001.[Medline]
[12] www.videredesign.com
[13] www.activmedia.com
![]()
CiteULike
Connotea
Del.icio.us What's this?
| ||||||||||||||||||||||||||||||||||||||||||||||||||