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IJCV
2002

Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional

8 years 11 months ago
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
We present a modification of the Mumford-Shah functional and its cartoon limit which facilitates the incorporation of a statistical prior on the shape of the segmenting contour. By minimizing a single energy functional, we obtain a segmentation process which maximizes both the grey value homogeneity in the separated regions and the similarity of the contour with respect to a set of training shapes. We propose a closed-form, parameter-free solution for incorporating invariance with respect to similarity transformations in the variational framework. We show segmentation results on artificial and real-world images with and without prior shape information. In the cases of noise, occlusion or strongly cluttered background the shape prior significantly improves segmentation. Finally we compare our results to those obtained by a level set implementation of geodesic active contours.
Daniel Cremers, Florian Tischhäuser, Joachim
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where IJCV
Authors Daniel Cremers, Florian Tischhäuser, Joachim Weickert, Christoph Schnörr
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