Geometry-based image retrieval in binary image databases

In this paper, a geometry-based image retrieval system is developed for multiobject images. We model both shape and topology of image objects using a structured representation called curvature tree (CT). The hierarchy of the CT reflects the inclusion relationships between the image objects. To facilitate shape-based matching, triangle-area representation (TAR) of each object is stored at the corresponding node in the CT. The similarity between two multiobject images is measured based on the maximum similarity subtree isomorphism (MSSI) between their CTs. For this purpose, we adopt a recursive algorithm to solve the MSSI problem and a very effective dynamic programming algorithm to measure the similarity between the attributed nodes. Our matching scheme agrees with many recent findings in psychology about the human perception of multiobject images. Experiments on a database of 13,500 real and synthesized medical images and the MPEG-7 CE-1 database of 1,400 shape images have shown the effectiveness of the proposed method.