Global minimization of adaptive local image fitting energy for image segmentation
Guoqi Liu, Zhiheng Zhou, Shengli Xie · Journal of Systems Engineering and Electronics · 2014
The active contour model based on local image fitting (LIF) energy is an effective method to deal with intensity inhomo-geneities, but it always conflicts with the local minimum problem because LIF has a nonconvex energy function form. At the same time, the parameters of LIF are hard to be chosen for better performance. A global minimization of the adaptive LIF energy model is proposed. The regularized length term which constrains the zero level set is introduced to improve the accuracy of the boundaries, and a global minimization of the active contour model is presented. In addition, based on the statistical information of the intensity histogram, the standard deviation σ with respect to the truncated Gaussian window is automatically computed according to images. Consequently, the proposed method improves the performance and adaptivity to deal with the intensity inhomo-geneities. Experimental results for synthetic and real images show desirable performance and efficiency of the proposed method.