| Summary: | 碩士 === 國立高雄應用科技大學 === 資訊工程系 === 98 === Recognition of off-line handwritten Chinese character had been an important problem. Because of the variation and vagueness derived from different users’ handwritings. It was hard to recognize handwriting characters via statistical features obtained from database. In recent years, such studies as word segmentation, part-of-speech and parsing were developed and presented. These methods would be used to increase the accuracy of off-line handwritten Chinese character recognition. The purpose of this study is to use lexical, syntactical and corpus rules for increasing the accuracy mentioned above.
Our methods could be divided into three phases. First, we used lexical rule “multi-syllable words priority” to predict some characters of a sentence from candidate characters. Second, neighbor several candidate characters in which particular grammar patterns appear will be treated as the characters of the sentence. Finally, two adjacent candidate characters will be regarded as a string. The strings which occur in a corpus frequently will be used to be the characters of the sentence. To contrast approach “highest frequency priority”, experimental results shown that the accurate rate of Chinese handwriting character recognition could be effectively increased from 0.45 to 0.85.
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