Unsupervised Robust Clustering for Image Database Categorization
Date:
Talk at ICPR’02 conference, located in Québec city, in Canada.
Abstract: Content-based image retrieval can be dramatically improved by providing a good initial database overview to the user. To address this issue, we present in this paper the Adaptive Robust Competition. This algorithm relies on a non-supervised database categorization, coupled with a selection of prototypes in each resulting category. In our approach, each image is represented by a high-dimensional signature in the feature space, and a principal component analysis is performed for every feature to reduce dimensionality. Image database overview is computed in challenging conditions since clusters are overlapping with outliers an
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