Historical hand-written string recognition by non-linear discriminant analysis using kernel feature selection

Ryo Inoue, Hidehisa Nakayama, Nei Kato

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In this paper, we propose a method to compose a classifier by non-linear discriminant analysis using kernel method combined with kernel feature selection for holistic recognition of historical hand-written string. Through experiments using historical hand-written string database HCD2, we show that our approach can obtain high recognition accuracy comparable to that of individual character recognition.

本文言語English
ホスト出版物のタイトルProceedings - 18th International Conference on Pattern Recognition, ICPR 2006
ページ1094-1097
ページ数4
DOI
出版ステータスPublished - 2006 12 1
イベント18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China
継続期間: 2006 8 202006 8 24

出版物シリーズ

名前Proceedings - International Conference on Pattern Recognition
2
ISSN(印刷版)1051-4651

Other

Other18th International Conference on Pattern Recognition, ICPR 2006
国/地域China
CityHong Kong
Period06/8/2006/8/24

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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