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Simultaneous variational image segmentation and object recognition via shape sparse representation

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3 Author(s)
Fei Chen ; Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China ; Huimin Yu ; Roland Hu

In this paper, we propose a novel model for simultaneous image segmentation and object recognition. Our model is different from previous prior-based level set variatioinal image segmentation in two aspects. The first is the use of the shape sparse representation, which is able to integrate shape priors by linear combination into variational image segmentation. The second is that segmentation and recognition procedures are carried out automatically. The sparsest solution will determine the identity of the target. In addition, our model can handle more general shape priors. Numerical experiments show promising results on synthetic and real images.

Published in:

2010 IEEE International Conference on Image Processing

Date of Conference:

26-29 Sept. 2010