A new snake-based algorithm is presented to segment objects from a pair of stereo images. The proposed algorithm is built upon a new energy function defined in the disparity space in such a way to successfully locate the boundary of an object found in a stereo image pair. The distinction of our algorithm comes from its superb segmentation capability even when the objects in the image are occluded and the background behind them is cluttered. The computer simulation shows out-performing results over the well-known conventional snake algorithm in terms of segmentation accuracy.
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