Clustering Using Perceptual Positions

Abstract

We introduce the concept of perceptual position to cluster a set of feature points (FPs) in the same way as that performed by human subjects. The perceptual position is based on a physical position of a FP. It is a fuzzy set whose domain of membership, being greater than 0, is determined by the FPs within a hypershpere centering around that FP with radius is L. A clustering algorithm for the perceptual positions is presented using fuzzy c means (FCM). As the results of experiments, clustering using this new algorithm is closer to that performed by human subjects than is that using the conventional FCM algorithm when we choose suitable L.