Robust Chinese character recognition by selection of binary-based and grayscale-based classifier

Yoshinobu Hotta*, Jun Sun, Yutaka Katsuyama, Satoshi Naoi

*この研究の対応する著者

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

As the spread of digital videos, digital cameras, and camera phones, lots of researches are reported about degraded character recognition. It is found that while the grayscale-based classifier is powerful for degraded character, the performance for clear character is not so good as binary-based classifier. In this paper, a dynamic classifier selection method is proposed to combine the two classifiers based on an estimation of the degradation level and the recognition reliability of the input character images. Experimental results show that the proposed method can achieve better recognition performance than the two individual ones.

本文言語English
ホスト出版物のタイトルDocument Analysis Systems VII - 7th International Workshop, DAS 2006, Proceedings
ページ553-563
ページ数11
DOI
出版ステータスPublished - 2006
外部発表はい
イベント7th International Workshop on Document Analysis Systems, DAS 2006 - Nelson, New Zealand
継続期間: 2006 2 132006 2 15

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
3872 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference7th International Workshop on Document Analysis Systems, DAS 2006
国/地域New Zealand
CityNelson
Period06/2/1306/2/15

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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