Model-based online handwritten digit recognition
نویسندگان
چکیده
This paper presents a hidden Markov model (HMM) based approach to on-line 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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