We present a new method to segment visual handwritten data in gray-scale images. In handwriting recognition, visual shapes are very important in improving the system's performance. We introduce a robust method for extracting visual shapes of handwritten data from a noisy background. We adopted a multi-resolution Marr-Hildreth (1980) based approach to correctly segment visual data in variable contrasted images. Encouraging results have been obtained on real data, from the CEDAR database.<>


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    Titel :

    A multi-resolution based approach for handwriting segmentation in gray-scale images


    Beteiligte:
    Cheriet, M. (Autor:in) / Thibault, R. (Autor:in) / Sabourin, R. (Autor:in)


    Erscheinungsdatum :

    01.01.1994


    Format / Umfang :

    414192 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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