|Title||A Markov random fields model for hybrid edge and region based colour image segmentation|
|Publication Type||Conference Paper|
|Year of Publication||2002|
|Authors||Wesolkowski, S., and P. Fieguth|
|Conference Name||15th Canadian Conference on Electrical and Computer Engineering|
|Keywords||color 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|
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.