A method for color content matching of images

Abstract

Color features are among the most important features used in image database retrieval. Due to its compact representation and low complexity, direct histogram comparison is the most commonly used technique in measuring color similarity of images. However, it has many serious drawbacks, including a high degree of dependency on color codebook design, sensitivity to quantization boundaries, and inefficiency in representing images with few dominant colors. In this paper we present a new algorithm for color matching. We describe a new method for color codebook design in the Lab space. We introduce a statistical technique to extract perceptually relevant colors. We propose a new color distance measure that guaranties optimality in matching different color components of two images. Experiments comparing the new algorithm to some existing techniques show that these novel elements lead to better match to human perception in judging image color similarity.