This paper proposes a new hybrid handwritten signature verification system where the on-line reference data acquired through a digitizing tablet serves as the basis for the segmentation process of the corresponding scanned off-line data. Local foci of attention over the image are determined through a self-adjustable learning process in order to pinpoint the feature extraction process. Both local and global primitives are processed and the decision about the authenticity of the specimen is defined through similarity measurements. The global performance of the system is measured using two different classifiers.


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    Title :

    A hybrid on/off line handwritten signature verification system


    Contributors:
    Zimmer, A. (author) / Lee Luan Ling, (author)


    Publication date :

    2003-01-01


    Size :

    433785 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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