Color Based Retrieval

Abstract

In content based retrieval, color indexing is one of the most prevalent retrieval methods. The key problems in color indexing are: (1) the choice of color space, (2) color features, and (3) finding the best distance metric. In our color experiments we examine two applications from computer vision which involve distortions derived from changes in viewpoint and the process of printing and scanning. In the first experiments we use the Corel stock photo database and a color histogram method to find copies of images which were printed and subsequently scanned in. The second application deals with object based retrieval. The goal is to find all images of an object in a database where the images depicting the object were taken from different viewpoints. Both the ground truth and the algorithm come from the work by Gevers and Smeulders [Gevers and Smeulders, 1999]. Furthermore, for both applications, we implement the quadratic perceptual similarity measure proposed by Hafner et al. [Hafner et al., 1995] and the correlogram introduced by Huang et al. [Huang et al., 1997] as benchmarks.