Name
Abstract | ||
|---|---|---|
We propose a level set based variational approach that incorporates shape priors into Chan-Veseýs model [3] for the shape prior segmentation problem. In our model, besides the level set function for segmentation, as in Cremersý work [5], 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 [7] and similar to the one proposed in [19], for minimizingChan-Veseýs segmentation model without length term. We extend the principle to the minimization of our prescribed functionals. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/CVPR.2005.212 | CVPR (2) |
Keywords | Field | DocType |
variational approach,labelling level set function,prior shape,fast solution principle,shape prior segmentation problem,level set,shape prior,length term,segmentation model,prescribed functionals,level set function,image segmentation,image processing,shape,convergence,labeling,mathematics,object recognition,solid modeling,mathematical model,minimisation,edge detection | Convergence (routing),Active shape model,Computer vision,Scale-space segmentation,Pattern recognition,Edge detection,Computer science,Segmentation,Level set,Image segmentation,Artificial intelligence,Prior probability | Conference |
ISSN | ISBN | Citations |
1063-6919 | 0-7695-2372-2 | 79 |
PageRank | References | Authors |
3.30 | 10 | 2 |