A fast handwritten word recognition system for real time applications is presented. Preprocessing, segmentation and feature extraction are implemented using chain code representation. Dynamic matching between each character of a lexicon entry and segment(s) of input word image is used for ranking words in the lexicon. Speed of the entire recognition process is about 200 msec on a single SPARC-10 platform for lexicon size of 10. A top choice performance of 96% is achieved on a database of postal words captured at 212 dpi.


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    Titel :

    Handwritten word recognition for real-time applications


    Beteiligte:
    Gyeonghwan Kim (Autor:in) / Govindaraju, V. (Autor:in)


    Erscheinungsdatum :

    01.01.1995


    Format / Umfang :

    384590 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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