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.


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    Title :

    Recognition of handprinted Chinese characters using Gabor features


    Contributors:
    Hamamoto, Y. (author) / Uchimura, S. (author) / Masamizu, K. (author) / Tomita, S. (author)


    Publication date :

    1995-01-01


    Size :

    390247 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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