A novel edge detector for color images based on MCDM with evidential reasoning

Edge detection is one of the most important tasks in image processing and pattern recognition. Edge detector with multiple color channels can provide more edge information. However, the uncertainty occurring with the edge detection in each single channel and the discordance existing in the fusion of multiple channels edge detectors make the detection difficult. In this paper, we propose a new edge detection method in color images based on information fusion. We show that obtaining final edge through fusing the edge information in each channel is a challenging problem to make decision in the framework of Multi-Criteria decision making (MCDM). In this work, we propose to detect edges in color images using Cautious OWA with evidential reasoning (COWA-ER) and Fuzzy-Cautious OWA with evidential reasoning (FCOWA-ER) to handle the uncertainty and discordance. Experimental results show that the proposed approaches achieve better edge detection performance compared with the original edge detector.