Analysis of Local Features for Handwritten Character Recognition

Seiichi Uchida, Marcus Liwicki
2010 2010 20th International Conference on Pattern Recognition  
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 target
more » ... of the target pattern is determined by the majority voting on the J local recognition results. Despite a pessimistic expectation, we have reached recognition rates much higher than 90% for the task of digit recognition.
doi:10.1109/icpr.2010.479 dblp:conf/icpr/UchidaL10 fatcat:zjvbg6au6zeyfpxq2pqw6zlcjm