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We propose to use hidden Markov models (HMMs) to classify images. Images are modeled by extracting symbols corresponding to 3×3 binary neighborhoods of interest points, and by ordering these symbols by decreasing saliency order , thus obtaining strings of symbols. HMMs are learned from sets of strings modeling classes of images. The method has been tested(More)
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