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This paper presents a novel approach to visual objects classification basedon generating simple fuzzy classifiers using local image features todistinguish between one known class and other classes. Boosting meta learningis used to find the most representative local features. The proposed approachis tested on a state-of-the-art image dataset and compared with thebag-of-features image representation model combined with the Support VectorMachine classification. The novel method gives better classification accuracyand the time of learning and testing process is more than 30% shorter.

Fast Image Classification by Boosting Fuzzy Classifiers