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Spatial relationships between objects are important features for designing a content-based image retrieval system. In this paper, we propose a new scheme, called 9D-SPA representation, for encoding the spatial relations in an image. With this representation, important functions of intelligent image database systems such as visualization, browsing, spatial reasoning, iconic indexing, and similarity retrieval can be easily achieved. The capability of discriminating images based on 9D-SPA representation is much more powerful than any spatial representation method based on Minimum Bounding Rectangles or centroids of objects. The similarity measures using 9D-SPA representation provide a wide range of fuzzy matching capability in similarity retrieval to meet different user's requirements. Experimental results showed that our system is very effective in terms of recall and precision. In addition, the 9D-SPA representation can be incorporated into a two-level index structure to help reduce the search space of each query processing. The experimental results also demonstrated that, on average, only 0.1254 percent \sim 1.6829 percent of symbolic pictures (depending on various degrees of similarity) were accessed per query in an image database containing 50,000 symbolic pictures.
Image database, spatial relations, similarity retrieval, 9D-SPA, visualization.

P. Huang and C. Lee, "Image Database Design Based on 9D-SPA Representation for Spatial Relations," in IEEE Transactions on Knowledge & Data Engineering, vol. 16, no. , pp. 1486-1496, 2004.
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