New fuzzy model for morphological colour image processing

Abstract

Mathematical morphology is a powerful tool for image processing and analysis of binary, greyscale and colour images. In the paper, an efficient new fuzzy model for morphological colour image processing is introduced. A new vector-ordering scheme that uses fuzzy if–then rules is proposed, and then the basic morphological operations of erosion and dilation are defined. The morphological operators presented, which are vector preserving, are less sensitive to image distortion and perform significantly better in noise removal problems than other reported morphological operators. Experimental results demonstrate these advantageous characteristics on real images. Additionally, illustrative examples that exhibit the applicability of the proposed framework to edge-detection problems are given.