Comparative study of part-based handwritten character recognition methods

Wang Song, Seiichi Uchida, Marcus Liwicki

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

19 被引用数 (Scopus)

抄録

The purpose of this paper is to introduce three part-based methods for handwritten character recognition and then compare their performances experimentally. All of those methods decompose handwritten characters into "parts". Then some recognition processes are done in a part-wise manner and, finally, the recognition results at all the parts are combined via voting to have the recognition result of the entire character. Since part-based methods do not rely on the global structure of the character, we can expect their robustness against various deformations. Three voting methods have been investigated for the combination: single voting, multiple voting, and class distance. All of them use different strategies for voting. Experimental results on the MNIST database showed the relative superiority of the class distance method and the robustness of the multiple voting method against the reduction of training set.

本文言語英語
ホスト出版物のタイトルProceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011
ページ814-818
ページ数5
DOI
出版ステータス出版済み - 2011
イベント11th International Conference on Document Analysis and Recognition, ICDAR 2011 - Beijing, 中国
継続期間: 9 18 20119 21 2011

出版物シリーズ

名前Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN(印刷版)1520-5363

その他

その他11th International Conference on Document Analysis and Recognition, ICDAR 2011
国/地域中国
CityBeijing
Period9/18/119/21/11

All Science Journal Classification (ASJC) codes

  • コンピュータ ビジョンおよびパターン認識

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