A fast segmentation algorithm for images with intensity in-homogeneity
Yufang Zhang · Journal of Chongqing University. English Edition · 2013
A novel fast method based on local region active contour model is proposed to overcome the difficult and ineffective segmentation of in-homogenous images.A new energy function is defined by combining kernel function and cut metric.On one hand,kernel function is favor of computing the in-homogenous distribution of local regions effectively;on the other hand,better approximation of the curve length by cut metric can help contours to quickly evolve into the object's boundary.In addition,in the evolving process of contours,a max-flow method is adopted,instead of traditional computational level set method.Experimental results of synthetic and real images show that the proposed method can effectively segment objects with weak boundary in in-homogenous images,as well as the complex structure objects with multi-gray levels.At the same time,it is robust to noise and the initial contours.