Level set based shape prior segmentation

We propose a level set based variational approach that incorporates shape priors into Chan-Vese's model for the shape prior segmentation problem. In our model, besides the level set function for segmentation, as in Cremers' work, we introduce another labelling level set function to indicat...

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Bibliographic Details
Published in2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 2; pp. 1164 - 1170 vol. 2
Main Authors Chan, T., Wei Zhu
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Active contours
Convergence
Image processing
Image segmentation
Labeling
Level set
Mathematical model
Mathematics
Shape
Solid modeling
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Summary:We propose a level set based variational approach that incorporates shape priors into Chan-Vese's model for the shape prior segmentation problem. In our model, besides the level set function for segmentation, as in Cremers' work, we introduce another labelling level set function to indicate the regions on which the prior shape should be compared. Our model can segment an object, whose shape is similar to the given prior shape, from a background where there are several objects. Moreover, we provide a proof for a fast solution principle, which was mentioned by F. Gibou et al., and similar to the one proposed in [B. Song et al., (2002)], for minimizing Chan-Vese's segmentation model without length term. We extend the principle to the minimization of our prescribed functionals.
ISBN:0769523722
9780769523729
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2005.212