Statistical model based on level set method for image segmentation

Abstract

Level set method requires the definition of a speed function that governs model deformation. Classical method only used image gradient, edge strength, and region intensity to define the speed function. In this paper, a new speed function for level set framework is proposed. This method combines the region intensity and gradient information instead of spatial image gradient information. The new method is robust to noise and poor edges. We illustrate the performance of the new algorithm on various images. The experimental results show that incorporating region intensity information and gradient information into the level set framework, an accurate and robust segmentation can be achieved.