Abstract
A new automatic translation system between simplified and complex Chinese characters based on OCR approaches is proposed in this paper. This system can demonstrate an efficient feature extraction algorithm for recognizing either complex or simplified printed Chinese characters. In addition, a new post-processing model proposed in the authors' system not only translates texts between complex and simplified characters, but also corrects character recognition errors. Experimental results show that the average recognition rates are about 99.2% and 95.3% for single font and multi-font recognition respectively. In testing on real documents of simplified characters, it achieves a recognition rate of 96.2% without contextual post-processing. Using the proposed language model for post-processing, one can improve the final accuracy rate to 97.8% including the text translation process and the recognition error correction.
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