Split Bregman method for minimization of improved active contour model combining local and global information dynamically

JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS

卷:389

Article

Yang, Yunyun¹  Wu, Boying¹ 

[1] Harbin Inst Technol, Dept Math, Harbin 150001, Peoples R China

关键词: Active contour model;    Image segmentation;    Intensity inhomogeneity;    Level set method;    Variational method;    Split Bregman method;   

DOI  :  10.1016/j.jmaa.2011.11.073

来源: Elsevier

【 摘 要 】

This paper presents an improved active contour model by combining the Chan-Vese model, the region-scalable fitting energy model, the globally convex segmentation method and the split Bregman method. A weight function that varies with the location of a given image is used to control the influence of the local and global information dynamically. We first present our model in a 2-phase level set formulation and then extend it to a multi-phase formulation. By taking the local and global information into consideration together, our model can segment more general images, especially images with intensity inhomogeneity. Our model has been applied to synthetic and real images with promising results. Numerical results show the advantages of our model compared with other models. The accuracy and efficiency are demonstrated by the numerical results. Besides, our model is robust in the presence of noise. (C) 2011 Elsevier Inc. All rights reserved.

【 授权许可】

Free