Models and algorithms for efficient color image indexing

A robust color image retrieval algorithm is proposed, based on the hybrid graph representation, i.e. a dual graph which consists of a modified color adjacency graph (MCAG) and a spatial variance graph (SVG). The MCAG is proposed to enhance the indexing performance and the database capacity by increasing the feature dimension. In addition, the SVG is introduced in order to utilize the geometric statistics of the chromatic segment in the spatial domain. In the matching, we expand the histogram intersection into the graph intersection, in which graph matching is performed using simple matrix operations. Intensive discussions and experimental results are provided to evaluate the performance of the proposed algorithm. Experiments are carried out with M.J. Swain´s et al.´s (1991) test images and the VIRAGE images. It is shown that the proposed algorithm provides high retrieval performance with tolerable computational complexity