Distributed adaptive attribute-based image retrieval

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Abstract
In this paper, we describe a prototype system, named DAIRS, for distributed image retrieval. DAIRS features adaptive query reformulation mechanism for improving the retrieval effectiveness. The query reformulation mechanism is based on the calculation of the functional dependency between each image attribute and the user's relevance feedback. The importance (or weight) of each attribute is modified in the reformulated query based on the degree of such functional dependency. Since image servers are dynamically evolving in a distributed environment, DAIRS has been designed to deal with image databases in various domains distributed in the Internet. The DAIRS communication protocol is designed to cooperate with http and ftp, so that the client can easily access the distributed image repositories. Experimental results show that the query reformulation mechanism significantly improves the retrieval effectiveness.

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