Color image segmentation using Dempster-Shafer's theory
P. Vannoorenberghe, Olivier Colot, Denis De Brucq · 2003
In this paper, we propose a color image segmentation method based on the Dempster-Shafer's theory. The tristimuli R, G and B are considered as three independent information sources which can be very limited or weak. The basic idea consists in modeling the color information in order to have the features of each region in the image. This model, obtained on training sets extracted from the intensity, allows to reduce the classification errors concerning each pixel of the image. The proposed segmentation algorithm has been applied to synthetic and biomedical images in order to illustrate the methodology.