A novel penta-valued descriptor for color clustering

Abstract

This paper proposes a new color representation. This representation belongs to the penta-valued category and it has three chromatic components (red, blue and green) and two achromatic components (black and white). The proposed penta-valued representation is obtained by constructing a fuzzy partition in the RGB color space. In the structure of the penta-valued representation, it is defined the well known negation operator and supplementary, two new unary operators: the dual and the complement. Also, using the Bhattacharyya formula, it is defined a new inter-color similarity. Next, the obtained inter-color similarity is used in the framework of k-means clustering algorithm. On this way, it results a new color image clustering method. Some examples are presented in order to prove the effectiveness of the proposed multi-valued color descriptor. © 2014 Springer International Publishing.