A level set based segmentation method for images with intensity inhomogeneity

Authors:
Xiao-Feng Wang;Hai Min
Affiliations:
Hefei Inst. of Int. Machines, Chinese Academy of Sci., Hefei, Anhui, China and Key Lab of Network and Int. Inf. Proc., Dept. of Comp. Sci. and Techn., Hefei Univ., Hefei, China and Dept. of Aut., ...;Intelligent Computing Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China and Department of Automation, University of Science and Technology of China, He ...
Venue:
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Year:
2009

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Abstract

In this paper, an efficient hybrid level set (HLS) model is proposed for segmenting the images with intensity inhomogeneity, which is a difficult problem for traditional region-based level set methods. The total energy functional for the proposed model consists of three terms, i.e., global term, local term and regularization term. By incorporating the local image information into the proposed model, the images with intensity inhomogeneity can be efficiently segmented. In addition, the time-consuming re-initialization step widely adopted in traditional level set methods can be avoided by introducing a penalizing energy. Finally, experiments on some synthetic and real images have demonstrated the efficiency and robustness of the proposed model.