A Level Set Method for Image Segmentation with Energy Function Based on Mixture of Gaussian distribution

In this paper, we present a novel level set method for image segmentation by utilizing the Bayesian rule and Mixture of Gaussian distribution as a conductor which its parameters are obtained from EM-algorithm. We use an Adaptive direction function to make the curve evolution robust against the curve’s initial position and a nonlinear adaptive velocity to speed up the process of curve evolution and also a probability-weighted edge and region indicator function to implement a robust segmentation for objects with weak boundaries. The proposed method has the following features:1) By using the Bayesian rule that contains the regional features of image, it automatically determines the curve to shrink or expand; 2) To avoid the leakage at weak boundaries it accompanies the curve evolution an appropriate speed.

کلیدواژه ها:

Active contour ، image segmentation ، level set ، Gaussian Mixture distribution ، EM- algorithm