| Summary: | 碩士 === 國立交通大學 === 資訊工程研究所 === 83 === This thesis presents an application of neural networks on off-
line similar handwritten Chinese character recognition. The
proposed method consists of three components:(1)confusing
character sets construction,(2)feature selection,(3)modular
neural network recognition. In order to evaluate the proposed
recognition system, we choose 5401 frequently used Chinese
characters as our trainning and testing domain. The database of
each testing and trainning sample character was created by the
Computer and Communication Laboratory of Industrial Technology
Research Institute. Because the samples in this database were
collected by more than 2600 people, our recognition system
could reach a high generality and user-independence.
Experimental results show that, the method improves recognition
rate from 86.01% to 90.12%.
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