Journal
COMPUTER VISION AND IMAGE UNDERSTANDING
Volume 107, Issue 3, Pages 210-224Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.cviu.2006.11.004
Keywords
object segmentation; active contours; snakes; graph cut
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In this paper we present a graph cuts based active contours (GCBAC) approach to object segmentation. GCBAC approach is a combination of the iterative deformation idea of active contours and the optimization toot of graph cuts. It differs from traditional active contours in that it uses graph cuts to iteratively deform the contour and its cost function is defined as the summation of edge weights on the cut. The resulting contour at each iteration is the global optimum within a contour neighborhood (CN) of the previous result. Since this iterative algorithm is shown to converge, the final contour is the global optimum within its own CN. The use of contour neighborhood alleviates the well-known bias of the minimum cut in favor of a shorter boundary. GCBAC approach easily extends to the segmentation of three and higher dimensional objects, and is suitable for interactive correction. Experimental results on selected data sets and performance analysis are provided. (c) 2006 Elsevier Inc. All rights reserved.
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