A A-IFSs Based Image Segmentation Methodology for Gait Analysis

In this work, image segmentation is addressed as the starting point within a motion analysis methodology intended for biomechanics behavior characterization. First, we propose a general segmentation framework that uses Atanassov's intuitionistic fuzzy sets (A-IFSs) to determine the optimal image threshold value. Atanassov's intuitionistic fuzzy index values are used for representing the unknowledge/ignorance of an expert on determining whether a pixel belongs to the background or the object of the image. Then, we introduce an extension of this methodology that uses a heuristic based multi-threshold approach to determine the optimal threshold. Experimental results are presented.