FAST IMAGE RETRIEVAL USING COLOR-SPATIAL INFORMATION

In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate the retrieva l process. The basic unit used in our technique is a single-colored cl uster, which bounds a homogeneous region of that color in an image. Tw o clusters from two images are similar if they are of the same color a nd overlap in the image space. The number of clusters that can be extr acted from an image can be very large, and it affects the accuracy of retrieval. We study the effect of the number of clusters on retrieval effectiveness to determine an appropriate value for ''optimal'' perfor mance. To facilitate efficient retrieval, we also propose a multi-tier indexing mechanism called the Sequenced Multi-Attribute Tree (SMAT). We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors, while the second layer di scriminates clusters of different spatial locality. We conducted an ex perimental study on an image database consisting of 12,000 images. Our results show the effectiveness of the proposed color-spatial approach , and the efficiency of the proposed indexing mechanism.