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http://dx.doi.org/10.3745/KIPSTB.2008.15-B.4.269

A New EDGE-BASED Stereo Correspondence Method for Snake-Based Object Segmentation  

Park, Min-Gyu (배재대학교 정보통신공학과)
Alattar, Ashraf (배재대학교 정보통신공학과)
Jang, Jong-Whan (배재대학교 정보통신공학과)
Abstract
In this paper, we propose a new stereo correspondence method for generating excellent external energy for snake-based object segmentation methods in stereo images. Our method first generates an edge-based disparity map by performing stereo correspondence between multi-level edge maps of the stereo image pair. Only edges of similar strength are considered for matching. To filter the disparity map for edges of the object of interest, the method estimates the object's disparity value by matching the pattern of edges of the region of interest in the left image against candidate patterns in the right image. The filtered edge map is then used to generate external energy for the snake. The proposed method has been tested on two snake models and results show a noticeable enhancement on performance of the snake when compared with other methods.
Keywords
Snake; segmentation; stereo; edge maps; disparity;
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1 Kass, M., A. Witkin and D. Terzopoulos. “Snake: Active Contour Models.” Int'l J. Computer Vision, Vol.1, No.4, pp.321-331, 1987   DOI
2 Waite, J. B. and W. J. Welsh. “Head boundary location using snakes,” Brit. Telecom Tech. J., Vol.8, No.3 pp.127-135, 1990
3 Couvignou, P. A., N. P. Papanikolopoulos and P. K. Khosla. “On the use of snakes for 3-D robotic visual tracking,” IEEE CVPR 1993, pp.750-751, June 1993   DOI
4 Malladi, R., J. A. Sethian and B. C. Vemuri. “Shape modeling with front propagation: A level set approach,” IEEE Trans. Pat. Anal. Mach. Intell., Vol.17, No.2, pp.158-175, June 1995   DOI   ScienceOn
5 Fok, Y. L., J. C. K. Chan and R. T. Chin. “Automated analysis of nerve-cell images using active contour models,” IEEE Trans. Med. Imag., Vol.15, No.3, pp.353-368, June 1996   DOI   ScienceOn
6 Xu, Chenyang and Jerry L. Prince. “Snakes, Shapes, and Gradient Vector Flow,” IEEE Transactions on Image Processing, Vol.7, No.3, pp.359-369, March 1998   DOI   ScienceOn
7 Kim, S. H., J. W. Jang and J. H. Choi. “Object Segmentation Algorithm Using Snakes in Stereo Images,” Optical Engineering, Vol.45, No.3, pp.037005, Mar. 2006   DOI   ScienceOn
8 Kim, S. H., A. M. Alattar and J. W. Jang. “Snake-Based Object Tracking in Stereo Sequences with the Optimization of the Number of Snake Points,” ICIP 2006, pp.193-196, Oct. 2006   DOI
9 Lam, K. M. and H. Yan. “Fast algorithm for locating head boundaries,” J. Elec. Imag., Vol.3, No.4, pp.351-359, Oct. 1994   DOI
10 McInernery, T. and D. Terzopolous. “Deformable models in medical image analysis: A survey,” Med. Imag. Anal., Vol.1, No.2, pp.91-108, 1996   DOI   ScienceOn