Title :
A color edge detector based on Dempster-Shafer theory
Author_Institution :
ENSEA-ETIS, Cergy, France
Abstract :
Segmentation based on contour detection is a relevant stage before image interpretation or pattern recognition. This paper is concerned with color image filtering and color edge detection. These two techniques utilize the Dempster-Shafer 91968. 1976) theory. After the description of color image filtering which generalizes Nagao´s (1979) filter, a method for computing the orientation and magnitude of a gradient on color images is presented. Both filtering and edge detection use a 5×5 window. Some choices in the algorithms permit one to reduce the computing complexity of evidential theory. Finally, a method which extracts the local maxima of gradient is described.
Keywords :
computational complexity; edge detection; filtering theory; image colour analysis; image segmentation; inference mechanisms; Dempster-Shafer theory; color edge detector; color image filtering; computing complexity reduction; contour detection; evidential theory; generalized Nagao´s filter; gradient local maxima extraction; image interpretation; image segmentation; pattern recognition; Color; Data mining; Detectors; Filtering; Filters; Image edge detection; Image segmentation; Merging; Pattern recognition; Pixel;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC, Canada
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.899833