Penmanship Learning Support System: Feature Extraction for Online Handwritten CharactersReport as inadecuate




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1 Kansai University Graduate School 2 Kansai University

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.

Keywords : Penmanship Evaluation of characters Features Turns





Author: Tatsuya Yamaguchi - Noriaki Muranaka - Masataka Tokumaru -

Source: https://hal.archives-ouvertes.fr/



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