A fuzzy rule-based colour image segmentation algorithm

Most fuzzy rule-based image segmentation techniques to date have been primarily developed for gray level images. In this paper, a new algorithm called fuzzy rule-based colour image segmentation (FRCIS) is proposed by extending the generic fuzzy rule-based image segmentation (GFRIS) algorithm [2] and integrating a novel algorithm for averaging hue angles. Qualitative and quantitative analysis of the performance of FRCIS is examined and contrasted with the popular fuzzy c-means (FCM) and possibilistic c-means (PCM) algorithms for both, the Hue-Saturation-Value (HSV) and RGB colour models. Overall, FRCIS provides considerable improvement for many different image types.