Framework for image mining and retrieval

Rokia Missaoui; Madenda Sarifuddin; Youssef Hamouda; Jean Vaillancourt; Hayet Laggoune

doi:10.1117/12.503300

23 June 2003 Framework for image mining and retrieval

Rokia Missaoui, Madenda Sarifuddin, Youssef Hamouda, Jean Vaillancourt, Hayet Laggoune

Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003) https://doi.org/10.1117/12.503300
Event: Visual Communications and Image Processing 2003, 2003, Lugano, Switzerland

Abstract

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.

Citation Download Citation

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); https://doi.org/10.1117/12.503300

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