<title>Geometric histogram: a distribution of geometric configurations of color subsets</title>

Abstract

Spatial distribution of color is very important for refining color histograms use din indexing and retrieving color images. Existing histogram refinement techniques are based on the spatial distribution of a single color or color pair. In this paper, the concept of spatial distribution of a subset of colors, which is defined as the occurrence of different geometric configurations of the color set, is used to provide new clues for refining traditional color histogram. The concept is a unification of some existing techniques such as color density maps, color correlogram and color tuples. Experimental results demonstrate that triangular geometric histogram, on e of the simplest special cases of geometric histograms, which is defined as the occurrence of a list of isosceles right triangles of different side lengths of color triples, is more desirable than existing techniques for content-based image retrieval, especially when the database in question consists of on-line color images which are extremely heterogenous in terms of the content of images, camera types, lighting conditions and so on.