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 IfipConnect in order to contact the contributor Submitted on : Wednesday, August 13, 2014 - 3:07:09 PM Last modification on : Saturday, January 8, 2022 - 6:30:02 PM Long-term archiving on: : Wednesday, November 26, 2014 - 11:51:58 PM
Tatsuya Yamaguchi, Noriaki Muranaka, Masataka Tokumaru. Penmanship Learning Support System: Feature
Extraction for Online Handwritten Characters. 9th International Conference on Entertainment Computing (ICEC), Sep 2010, Seoul, South Korea. pp.496-498, ⟨10.1007/978-3-642-15399-0_71⟩. ⟨hal-01055589⟩