Active contours driven by local image fitting energy

Authors:
Kaihua Zhang;Huihui Song;Lei Zhang
Affiliations:
Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China;Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, People's Republic of China;Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China
Venue:
Pattern Recognition
Year:
2010

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Abstract

A new region-based active contour model that embeds the image local information is proposed in this paper. By introducing the local image fitting (LIF) energy to extract the local image information, our model is able to segment images with intensity inhomogeneities. Moreover, a novel method based on Gaussian filtering for variational level set is proposed to regularize the level set function. It can not only ensure the smoothness of the level set function, but also eliminate the requirement of re-initialization, which is very computationally expensive. Experiments show that the proposed method achieves similar results to the LBF (local binary fitting) energy model but it is much more computationally efficient. In addition, our approach maintains the sub-pixel accuracy and boundary regularization properties.