A Markov random fields model for hybrid edge and region based colour image segmentation

TitleA Markov random fields model for hybrid edge and region based colour image segmentation
Publication TypeConference Paper
Year of Publication2002
AuthorsWesolkowski, S., and P. Fieguth
Conference Name15th Canadian Conference on Electrical and Computer Engineering
Keywordscolor hue, color theory, dichromatic reflection model, edge detection, highlight components removal, hybrid edge-based color image segmentation, image colour analysis, image segmentation, line process, Markov processes, Markov random fields model, random processes, region segmentation, region-based color image segmentation, RGB space, shading effects removal, vector-angle component
Abstract

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.

DOI10.1109/CCECE.2002.1013070