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This paper develops a theoretically simple, efficient yet robust approach to supervised texture segmentation based on local radial difference features and a Bag-of-Words (BoW) model. We make the following contributions: (1) we propose an approach to optimally learn new compact single BoW histogram models from the entire training set, with the single histogram providing benefits of efficiency in both...
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