An improvement to the content-based image retrieval (CBIR) system for kaou images which has been developed by the authors group is introduced. Kaous are handwritten monograms found on old Japanese documents in a Chinese character-like shapes with artistic decorations. Kaous play an important role in the research of historical documents, which involve browsing and comparison of numerous samples. In this work, a novel method of kaou image modeling for CBIR is introduced, which incorporates the shade information of a closed kaou region in addition to the conventionally used contour characteristics. Dissimilarity of query and dictionary images were calculated as a weighted sum of elementary differences in the positions, contour shapes and colors of the component regions. These elementary differences were evaluated using relaxation matching and empirically defined distance functions. In the experiments, a set of 2455 kaou images were used. It was found that apparently similar kaou images could be retrieved by the proposed method, improving the retrieval quality. .
