On-Line Character Recognition System Using Fuzzy Stroke Type

• Main Authors: Wan, Ming-Hwa, 萬明華
• Other Authors: Chang, Jyh-Yeong
• Format: Others
• Language: zh-TW
• Published: 1995
• Online Access: http://ndltd.ncl.edu.tw/handle/20697434543773937164

碩士 === 國立交通大學 === 控制工程研究所 === 83 === 　　This thesis presents an on-line Chinese character recognition system based on fuzzy stroke type identification and model-based stroke string matching. According to the writing stroke sequence, each character is described by a 1-D stroke string model. The written characters can be loosely constraints, which are quite flexible on size and allow various variations. The proposed recognition system consists of two phases: primitive stroke type identification and character recognition by stroke-string matching. In the former phase, the stroke segments of imput strokes are extracted firstly and the strokes of input character are then identified as a sequence of primitive stroke types by our fuzzy approach. In the latter phase, the character is recognized by the stroke string matching. The recognition results are tested based upon the 605 handwritten characters about 6 variations for each one. The obtained recognition rate is 92.1%, and the cumulative classification rate of choosing the second most similar characters is up to 96.7%.