Decision-theoretic image retrieval

Nuno Miguel Vasconcelos

doi:10.1117/12.473028

1 July 2002 Decision-theoretic image retrieval

Nuno Miguel Vasconcelos

Proceedings Volume 4862, Internet Multimedia Management Systems III; (2002) https://doi.org/10.1117/12.473028
Event: ITCom 2002: The Convergence of Information Technologies and Communications, 2002, Boston, MA, United States

Abstract

The design of an effective architecture for image retrieval requires careful consideration of the interplay between the three major components of a retrieval system: feature transformation, feature representation, and similarity function. We present a review of ongoing work on a decision theoretic formulation of the retrieval problem that enables the design of systems where all components are optimized with respect to the same end-to-end performance criteria: the minimization of the probability of retrieval error. In addition to some previously published results on the theoretical characterization of the impact of the feature transformation and representation in the probability of error, we present an efficient algorithm for optimal feature selection. Experimental results show that decision-theoretic retrieval performs well on color, texture, and generic image databases in terms of both retrieval accuracy and perceptual relevance of similarity judgments.

Citation Download Citation

Nuno Miguel Vasconcelos "Decision-theoretic image retrieval", Proc. SPIE 4862, Internet Multimedia Management Systems III, (1 July 2002); https://doi.org/10.1117/12.473028

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