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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    Title :

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


    Contributors:
    Nakamura, A. (author) / Kawajiri, H. (author)


    Publication date :

    2002-01-01


    Size :

    453551 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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