Affinity relation discovery in image database clustering and content-based retrieval

Authors:
Mei-Ling Shyu;Shu-Ching Chen;Min Chen;Chengcui Zhang
Affiliations:
University of Miami, Coral Gables, FL;Florida International University, Miami, FL;Florida International University, Miami, FL;University of Alabama at Birmingham, Birmingham, AL
Venue:
Proceedings of the 12th annual ACM international conference on Multimedia
Year:
2004

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Abstract

In this paper, we propose a unified framework, called Markov Model Mediator (MMM), to facilitate image database clustering and to improve the query performance. The structure of the MMM framework consists of two hierarchical levels: local MMMs and integrated MMMs, which model the affinity relations among the images within a single image database and within a set of image databases, respectively, via an effective data mining process. The effectiveness and efficiency of the MMM framework for database clustering and image retrieval are demonstrated over a set of image databases which contain various numbers of images with different dimensions and concept categories.