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Recognition of handprinted Chinese characters using Gabor features
Description
A method for handprinted Chinese character recognition based on Gabor filters is proposed. The Gabor approach to character recognition is intuitively appealing because it is inspired by a multi-channel filtering theory for processing visual information in the early stages of the human visual system. The performance of a character recognition system using Gabor features is demonstrated on the ETL-8 character set. Mental results show that the Gabor features yielded an error rate of 2.4% versus the error rate of 4.4% obtained by using a popular feature extraction method.
Journal
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- Proceedings of 3rd International Conference on Document Analysis and Recognition
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Proceedings of 3rd International Conference on Document Analysis and Recognition 2 819-823, 2002-11-19
IEEE Comput. Soc. Press