A perturbation model for generating synthetic text lines from existing cursively handwritten lines of text produced by human writers is presented. Our purpose is to improve the performance of an HMM-based off-line cursive handwriting recognition system by providing it with additional synthetic training data. Two kinds of perturbations are applied, geometrical transformations and thinning/thickening operations. The proposed perturbation model is evaluated under different experimental conditions.


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    Titel :

    Generation of synthetic training data for an HMM-based handwriting recognition system


    Beteiligte:
    Varga, T. (Autor:in) / Bunke, H. (Autor:in)


    Erscheinungsdatum :

    01.01.2003


    Format / Umfang :

    449723 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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