Colour Image Segmentation using A-IFSs

The problem of segmentation is an important research field and often a critical and decisive preprocessing step for many image processing applications. During the past years, the use of colour images instead of gray images is growing fast in many research areas. Moreover, the use of segmentation over colour images is advised when additional colour information conveyed is necessary to further discriminate the image regions. Recently, fuzzy logic theory, and Atanassov’s intuitionistic fuzzy sets (A-IFSs), have been successfully applied to image segmentation and, in this paper we propose a general methodology for RGB colour image segmentation based on A-IFSs. The proposed methodology is based on a multilevel colour thresholding framework that uses Atanassov’s intuitionistic index values for representing the uncertainty present in the assigning of the pixels to the different regions. This framework is to be applied to each RGB component separately to finally aggregate the results of the three components. The number of thresholds is auto established by the methodology based on the image entropy. Experimental results are presented. Keywords— Atanassov’s Intuitionistic Fuzzy Sets, Color Image Segmentation, Fuzzy Logic, Multi-Thresholding.