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This paper investigates a part-based recognition method of handwritten digits. In the proposed method, the global structure of digit patterns is discarded by representing each pattern by just a set of local feature vectors. The method is then comprised of two steps. First, each of J local feature vectors of a target pattern is recognized into one of ten categories ("0"-"9") by the nearest neighbor discrimination with a large database of reference vectors. Second, the category of the targetdoi:10.1109/icpr.2010.479 dblp:conf/icpr/UchidaL10 fatcat:zjvbg6au6zeyfpxq2pqw6zlcjm