| Summary: | 碩士 === 國立交通大學 === 資訊工程學系 === 84 === This thesis presents an application of statistics theory on
off-line adaptivemodule for handwritten Chinese characters
recognition. The proposed methodconsists of three
components:(1).prior information,(2).feature selection,(3).
adaptive module recognition. In order to evaluate the proposed
recognition system,we choose 5401 fre-quently used Chinese
characters as our domain. The database of each testingand
training sample character for the original 5401 classifier was
created bythe Computer and Communication Laboratory of
Industrial Technology ResearchInstitute. And we select the most
300 frequently used Chinese characterswhich were written by five
members of our lab for ten times as the testingand training for
the adaptive module. Because the samples for the adaptivemodule
were not sepcified,our recognition system could reach a high
generalityand user-independence. Experimental results show that,
the method improvesrecognition rate from 44.09% to 90.03%.
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