FReBIR: An image retrieval system based on fuzzy region matching |
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Affiliation: | 1. The University College in Aljamoum, Umm Al-Qura University, Makkah, Saudi Arabia;2. Automated Scheduling Optimization and Planning Group (ASAP), University of Nottingham, NG8 1BB, UK;3. HEC Management School, University of Liege, 4000 Liege, Belgium;4. Center for Computational Intelligence, School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK |
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Abstract: | In this paper, we present a method of image indexing and retrieval which takes into account the relative positions of the regions within the image. Indexing is based on a segmentation of the image into fuzzy regions; we propose an algorithm which produces a fuzzy segmentation. The image retrieval is based on inexact graph matching, taking into account both the similarity between regions and the spatial relation between them. We propose, on one hand a solution to reduce the combinatorial complexity of the graph matching, and on the other hand, a measure of similarity between graphs allowing the result images ranking. A relevance feedback process based on region classifiers allows then a good generalization to a large variety of the regions. The method is adapted to partial queries, aiming for example at retrieving images containing a specific type of object. Applications may be of two types, firstly an on-line search from a partial query, with a relevance feedback aiming at interactively leading the search, and secondly an off-line learning of categories from a set of examples of the object. The name of the system is FReBIR for Fuzzy Region-Based Image Retrieval. |
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