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23 June 2003 Framework for image mining and retrieval
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Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003)
Event: Visual Communications and Image Processing 2003, 2003, Lugano, Switzerland
In this paper, we describe a three-step content-based approach to image retrieval and mining. At a first step, visual features such as color and shape are generated from images by improving a few existing feature extraction techniques. Then, both visual features and descriptive data (i.e., metadata) are considered for a coarse-grain similarity analysis using a conceptual clustering approach called formal concept analysis (concept lattice theory). This approach is designed and implemented so that exploratory mechanisms such as browsing, zooming/shrinking and visualization allow the user to discover and refine the cluster which is the most appropriate to his/her target image. At this second stage, issues such as dimension reduction, cluster construction and association rule generation are handled. The last step consists to conduct a fine-grain similarity analysis on some selected cluster(s) identified at the second stage by using two newly proposed similarity measures.
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Rokia Missaoui, Madenda Sarifuddin, Youssef Hamouda, Jean Vaillancourt, and Hayet Laggoune "Framework for image mining and retrieval", Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003);

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