Indexing for efficient spatial similarity query processing in multimedia databases

In multimedia databases, one major class of user queries requires retrieving those database images that are spatially similar to a query image. To rank order the database images with respect to the query, the existing spatial similarity algorithms compute the similarity of every database image with the query. For large multimedia databases, this task is computationally expensive and renders interactive query processing difficult. In this paper, we propose an indexing scheme which will eliminate non-relevant images to a query before the actual similarity computation. In other words, the indexing scheme serves as a filter and spatial similarity computation is done only on those images that pass through the filter. Some non-relevant images may pass through the filter (i.e., false positives) but the proposed indexing scheme guarantees that no relevant images are eliminated (i.e., no false negatives). The indexing scheme is robust in the sense that it recognizes translation, scaling, and rotation variant images of the query image as relevant to the query.