Fuzzy stroke type identification for on-line Chinese character recognition

Abstract

This paper presents an on-line Chinese character stroke type recognition system based on fuzzy set theory. According to the writing strobe sequence, each character is described by an 1-D stroke string model. The input written characters can be loosely constraints, which are quite flexible on size and allow various variations. The stroke segments of input strokes are extracted firstly and the strokes of input character are then identified as a sequence of primitive stroke types by a fuzzy methodology. A character recognition system, based on this stroke type identification scheme and Modified Dynamic Programming Forward (MDPF) matching, Modified Dynamic Programming Backward (MPDB) matching, and A* matching algorithms, has been built and tested to be very successful.