I. Introduction
Clustering aims at grouping unlabeled data elements with high similarity into clusters based on any measure obtained solely from the data. These methods have been widely used in different investigative areas such as face detection [10], bioinformatics [9], [1], [14], market analysis [2] etc. Clustering has been extensively used to detect faces using skin extraction [5] while bioinformatics researchers utilized cluster analysis to build gene groups with related patterns and develop homologous sequences of genes [14]. Furthermore, market researchers took advantage of clustering techniques to segment multivariate survey data to better understand the relationships between different groups of consumers [2].