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.
Recognition of handprinted Chinese characters using Gabor features
Proceedings of 3rd International Conference on Document Analysis and Recognition ; 2 ; 819-823 vol.2
01.01.1995
390247 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Recognition of Handprinted Chinese Characters Using Gabor Features
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