On Similarity Measures for Multimedia Database Applications

Abstract

A multimedia database query consists of a set of fuzzy and boolean (or crisp) predicates, constants, variables, and conjunction, disjunction, and negation operators. The fuzzy predicates are evaluated based on different media criteria, such as color, shape, layout, keyword. Since media-based evaluation yields similarity values, results to such a query is defined as an ordered set. Since many multimedia applications require partial matches, query results also include tuples which do not satisfy all predicates. Hence, any fuzzy semantics which extends the boolean semantics of conjunction in a straight forward manner may not be desirable for multimedia databases. In this paper, we focus on the problem of ‘given a multimedia query which consists of multiple fuzzy and crisp predicates, how to provide the user with a meaningful overall ranking.’ More specifically, we study the problem of merging similarity values in queries with multiple fuzzy predicates. We describe the essential multimedia retrieval semantics, compare these with the known approaches, and propose a semantics which captures the retrieval requirements in multimedia databases.