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Model-based On-line Handwritten Digit Recognition


Xiaolin Li, Réjean Plamondon and Marc Parizeau


Abstract - This paper presents a hidden Markov model (HMM) based approach to online handwritten digit recognition using stroke sequences. In this approach, a character instance is represented by a sequence of symbolic strokes, and the representation is obtained by component segmentation and stroke classification. The component segmentation is based on the delta lognormal model of handwriting generation. The symbolic strokes are used for HMM multiple observation training or recognition. A training and recognition experiment has been conducted using the above techniques.

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Bibtex:

@inproceedings{Li53,
    author    = { Xiaolin Li and Réjean Plamondon and Marc Parizeau },
    title     = { Model-based On-line Handwritten Digit Recognition },
    booktitle = { Proc. of the 14th International Conference on Pattern Recognition },
    pages     = { 1134-1136 },
    year      = { 1998 },
    month     = { August },
    location  = { Brisbane (Australie) }
}

Last modification: 2002/06/14 by parizeau

     
   
   

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