Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2008-05-21
Computer Science
Computer Vision and Pattern Recognition
4 pages, ICIP 2006
Scientific paper
In this paper, we propose to combine formally noise and shape priors in region-based active contours. On the one hand, we use the general framework of exponential family as a prior model for noise. On the other hand, translation and scale invariant Legendre moments are considered to incorporate the shape prior (e.g. fidelity to a reference shape). The combination of the two prior terms in the active contour functional yields the final evolution equation whose evolution speed is rigorously derived using shape derivative tools. Experimental results on both synthetic images and real life cardiac echography data clearly demonstrate the robustness to initialization and noise, flexibility and large potential applicability of our segmentation algorithm.
Aubert Gilles
Fadili Jalal
Jehan-Besson Stéphanie
Lecellier François
Revenu Marinette
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