Color image retrieval using hybrid graph representation

In this paper, a robust color image retrieval algorithm is proposed based on the hybrid graph representation, i.e., a dual graph which consists of the Modified Color Adjacency Graph (MCAG) and Spatial Variance Graph (SVG). The MCAG, which is similar to the Color Adjacency Graph (CAG) [6], is proposed to enhance the indexing ability 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 process, we expand the histogram intersection [2] 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 on the Swain's test images and the Virage images, demonstrating that the proposed algorithm yields high retrieval performance with tolerable computational complexity. It is also shown that the proposed algorithm works well, even if the query image is corrupted. e.g., a large part of pixels is missing. (C) 1999 Elsevier Science B.V. All rights reserved.