This paper proposes active handwriting models, in which kernel principal component analysis is applied to capture nonlinear handwriting variations. In the recognition phase, the chamfer distance transform and a dynamic tunneling algorithm (DTA) are employed to search for the optimal shape parameters. The proposed methodology is successfully applied to a novel radical decomposition approach to the challenging problem of handwritten Chinese character recognition.


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    Title :

    Nonlinear active handwriting models and their applications to handwritten Chinese radical recognition


    Contributors:
    Ng, G.S. (author) / Shi, D. (author) / Gunn, S.R. (author) / Damper, R.I. (author)


    Publication date :

    2003-01-01


    Size :

    260863 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Nonlinear Active Handwriting Models and their Applications to Handwritten Chinese Radical Recognition

    Shi, D. / Ng, G. / Gunn, S. et al. | British Library Conference Proceedings | 2003



    A Radical Approach to Handwritten Chinese Character Recognition Using Active Handwriting Models

    Shi, D. / Gunn, S. R. / Damper, R. I. et al. | British Library Conference Proceedings | 2001