The Graphical Specification of Similarity Queries

Abstract Image databases will require a completely new organization due to the unstructured and ‘perceptual’ structure of the data they contain. We argue that similarity measures, rather than matching, will be the organizing principle of image databases. Similarity is a very elusive and complex judgment, and typical databases will have to rely on a number of different metrics to satisfy the different needs of their users. This poses the problem of how to combine different similarity measures in a coherent and intuitive way. In this paper we propose our solution, which is loosely based on ideas derived from fuzzy logic in that it uses the equivalent in the similarity domain of the and, or and not operations. The approach is much more general than that, however, and can be adapted to work with any operation that combines together similarity judgment. With this approach, a query can be described as a Directional Acyclic graph with certain properties. We analyse briefly the properties of this graph, and we present the interface we are developing to specify these queries.

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