Data Resource Selection in Distributed Visual Information Systems

With the advances in multimedia databases and the popularization of the Internet, it is now possible to access large image and video repositories distributed throughout the world. One of the challenging problems in such access is how the information in the respective databases can be summarized to enable an intelligent selection of relevant database sites based on visual queries. This paper presents an approach to solve this problem based on image content-based indexing of a metadatabase at a query distribution server. The metadatabase records a summary of the visual content of the images in each database through image templates and statistical features characterizing the similarity distributions of the images. The selection of the databases is done by searching the metadatabase using a ranking algorithm that uses the query's similarity to a template and the features of the databases associated with the template. Two selection approaches, termed mean-based and histogram-based approaches, are presented. The database selection mechanisms have been implemented in a metaserver, and extensive experiments have been performed to demonstrate the effectiveness of the database selection approaches.

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