A preclassification method for handwritten Chinese character recognition via Fuzzy rules and senar neural net

摘要

In this paper, a method of character preclassification for handwritten Chinese char- acter recognition is proposed. Since the number of Chinese characters is very large (at least 540ls for daily use), we employ two stages to reduce the candidates of an input character. In stage I, we extract the first set of primitive features from handwritten Chi- nese characters and use fuzzy rules to create four preclassification groups. The purpose in stage I is to reduce the candidates roughly.