Content-based indexing technique using relative geometry features
Tai-Yuan Hou, Arding Hsu, Peiya Liu, Ming‐Yee Chiu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
Content-based image indexing is becoming increasingly important in today''s imaging applications. Although several techniques have been developed, most have limited capabilities in dealing with relative spatial relations for multiple object images. We believe that multiple object image indexing is important for content-based indexing in many application domains. We propose a content-based indexing technique which is based on the theory of weighted center-of-mass. The index of an image is constructed by incorporating the center-of-mass of each individual object to calculate the center-of-mass of the overall image. This multiple object indexing scheme is further enhanced by incorporating existing indexing structure construction techniques, such as Jagadish''s multidimensional point representation, and Grosky''s feature index tree. An image with multiple objects can be retrieved by specifying the spatial relations among image objects, such as relative position, relative distance, and direction. The retrieval matching is based on a relative similarity measure. Furthermore, due to certain invariant properties of center-of-mass, different notions of image similarity with respect to scaling, translation, rotation, and mirrored image can be easily supported. The advantages of the proposed method are illustrated with an example of retrieving magnetic resonance images of patients'' chests within the medical image domain. The relationships to certain other indexing techniques are also addressed.