I. Introduction
Color naming within the computer vision context is mapping image pixels to linguistic color labels. We perceive colors and use color names in our day to day life without pretty much effort to describe the real-world scenario that surrounds us. We have the ability to name the colors reliably and distinguish even minute color changes. Color naming task has been under study of different fields such as anthropology, visual psychology and linguistics. The starting point that motivated for research community about this topic has been studied in the field of anthropology by Berlin and Kay [1]. They studied color naming across different languages and cultures to arrive at striking similarities in the use of color names. They stated the universality of color name categories and defined a set of 11 basic color categories that could be found in the the most evolved languages. These are red, green, blue, brown, yellow, pink, purple, orange, black, gray and white. Since then several others have studied, extended and confirmed their results in different fields [2] – [6], [8] – [10]. Color Naming finds its applications in computer vision tasks ranging from image search engines on the web, image retrieval, visual tracking, object recognition and texture recognition [11]. In other applications state-of-the-art results can be obtained by exploiting color description as a feature.