Combining Region and Edge Cues for Image Segmentation in a Probabilistic Gaussian Mixture Framework

Omer Rotem, Hayit Greenspan, Jacob Goldberger

Abstract: In this paper we propose a new segmentation algorithm which combines patch-based information with edge cues under a probabilistic framework. We use a mixture of multiple Gaussians for building the statistical model with color and spatial features, and we incorporate edge information based on texture, color and brightness differences into the EM algorithm. We evaluate our results qualitatively and quantitatively on a large data-set of natural images and compare our results to other state-of-the-art methods.