Level set image segmentation based on EM algorithm
Yunyang Yan · Jisuanji gongcheng yu sheji · 2011
Aimed at the shortcomings of the classical level set methods such as the Chan-Vese model algorithm in the iteration process to re-initialize and easily affected by noise and ambiguous boundaries,an internal energy functional is added to achieve the purpose of without re-initialization,and prior knowledge of image is combined with Bayesian decision theory to propose an improved energy function to tackle this problem by continuously rectifying the deviation of the level set function according to the signed distance function.This is achieved using an expectation-maximisation algorithm.Experimental results shows the proposed algothim is better than the classical image segmentation on precision and accuracy.