An approach to bigram-based linguistic processing for online handwriting text recognition is described. A probability of correctness for each recognition result is derived from a feature set which consists of bigram probabilities and recognition scores. Using the probability of correctness, the number of candidates accepted to the post-processing step and the weight value balancing recognition scores with bigram scores are adaptively controlled. The proposed method is evaluated in experiments using the HANDS-kuchibue online handwritten character database. Results show that the method is effective in reducing candidates, improving accuracy, and saving computational costs.


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    Titel :

    Bigram-based post-processing for online handwriting recognition using correctness evaluation


    Beteiligte:
    Nakamura, A. (Autor:in) / Kawajiri, H. (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    453551 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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