So far the bottleneck of Chinese recognition, especially handwritten recognition, still lies in the effectiveness of feature-extraction to cater for various distortions and position shifting. In the paper, a novel method is proposed by applying a set of Gabor spatial filters with different directions and spatial frequencies to character images, in an effort to reach the optimum trade-off between feature stability and feature localization. While a classic self-organizing map is used for unsupervised clustering feature codes, a multi-staged LVQ with a fuzzy judgement unit is applied for the final recognition on the feature mapping result.<>


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    Title :

    Handwritten Chinese character recognition using spatial Gabor filters and self-organizing feature maps


    Contributors:
    Da Deng (author) / Chan, K.P. (author) / Yinglin Yu (author)


    Publication date :

    1994-01-01


    Size :

    360439 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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