Abstract : This paper proposes a feature extraction method for
online handwritten characters for a penmanship learning support system.
This system has a database of model characters. It evaluates the
characters a learner writes by comparing them with the model characters.
However, if we prepare feature information for every character,
information must be input every time a model character is added.
Therefore, we propose a method of automatically extracting features from
handwritten characters. In this paper, we examine whether it correctly
identifies the turns in strokes as features. The resulting extraction
rate is 80% and in the remaining 20% of cases, it extracted an area near
a turn.
https://hal.inria.fr/hal-01055589
Contributeur : Hal Ifip
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Soumis le : mercredi 13 août 2014 - 15:07:09
Dernière modification le : mercredi 16 août 2017 - 17:33:15
Document(s) archivé(s) le : mercredi 26 novembre 2014 - 23:51:58
