A Spatially Varying Mean and Variance Active Contour Model

Abstract

This paper presents a spatially varying mean and variance (SVMV) active contour model. Assuming the distribution of intensity belonging to each region as a Gaussian distribution with spatially varying mean and variance, we define an energy function, and integrate the entire image domain. This energy is then incorporated into a variational level set formulation, from which a curve evolution equation is derived for energy minimization. The proposed model can effectively deal with the images with intensity in homogeneity because of considering the image local mean and variance. Experimental results on synthetic and real images demonstrate that the proposed model can effectively segment the image with intensity in homogeneity.