Myeong Jun Yu , Shin Hyoung Kim , Jong Whan Jang

The KIPS Transactions:PartB , Vol. 11, No. 7, pp. 769-778, Dec. 2004
10.3745/KIPSTB.2004.11.7.769,   PDF Download:

Abstract

Object segmentation is a challenging problem when the background is cluttered and the objects are overlapped one another. Recent development using snake algorithms proposed to segment objects from a 2-D image persents a higher possibility for getting better contours. However, the performance of those snake algorithms degrades rapidly when the background is clutterd and objects are overlapped one another. Moreover, the initial snake point placement is another difficulty to be resolved. Here, we propose a novel snake algorithm for object segmentation using disparity information taken from a set of stereo images. By applying our newly designed energy function defined in the disparity space, our algorithmeffectively circumvents the limitations found in the previous methods. The performance of the proposed algorithm has been verified by computer simulation using various stereo image sets. The experiment results have exhibited a better performance over the well-known snake algorithm in terms of segmentation accuracy.

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