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Penmanship Learning Support System: Feature Extraction for Online Handwritten Characters
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
Contributor : Hal Ifip <>
Submitted on : Wednesday, August 13, 2014 - 3:07:09 PM
Last modification on : Wednesday, August 16, 2017 - 5:33:15 PM
Long-term archiving on: : Wednesday, November 26, 2014 - 11:51:58 PM
Contributor : Hal Ifip <>
Submitted on : Wednesday, August 13, 2014 - 3:07:09 PM
Last modification on : Wednesday, August 16, 2017 - 5:33:15 PM
Long-term archiving on: : Wednesday, November 26, 2014 - 11:51:58 PM
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