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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    Title :

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


    Contributors:
    Cheriet, M. (author) / Thibault, R. (author) / Sabourin, R. (author)


    Publication date :

    1994-01-01


    Size :

    414192 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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