Fuzzy stroke type identification for online Chinese character recognition
Jyh‐Yeong Chang, Min-Hwa Wan · 2002
Presents an online Chinese character stroke type recognition system based on fuzzy set theory. According to the writing stroke sequence, each character is described by a 1D stroke string model. The input written characters can have loose constraints, which are quite flexible on size and allow variations. The stroke segments of input strokes are extracted first 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.