A Markov Random Fields model for hybrid edge- and region-based color image segmentation

In this paper, a framework based on a Markov Random Field approach for color image segmentation enhanced by edge detection is presented, We use a previously developed methodology to transform the image into an R'G'B' space to remove any highlight components preserving the vector-angle component, representing color hue but not intensity, to remove shading effects. To improve the segmentation process we describe the idea of a line process. This allows for the integration of region segmentation with edge detection in a Markov Random Field framework. We discuss the advantages of this new model with respect to the previously developed image segmentation model.