Fast and accurate text detection in natural scene images with user-intention

Liuan Wang, Wei Fan, Yuan He, Jun Sun, Yutaka Katsuyama, Yoshinobu Hotta

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

Text detection in natural scene images plays an important role in content-based image retrieval, especially user-guided text detection for human-computer interaction. In this paper, we propose a fast and accurate text detection method with user-intention in terms of tap gesture. Firstly, a user-intention slice descriptor is designed based on the estimated text property, which contains all the user interested texts, and fast heuristic features and accurate texture feature of decomposed connected components (CCs) are fed into cascade of Gentle Adaboost classifiers to eliminate non-text candidates, finally candidate texts, sharing the same property consistent with the seed CCs, are accumulated to a user-intention text line according to local and global permutation constraint. Experimental results demonstrate the effectiveness and robustness of the proposed method in comparison with the state-of-art methods.

本文言語English
ホスト出版物のタイトルProceedings - International Conference on Pattern Recognition
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2920-2925
ページ数6
ISBN(電子版)9781479952083
DOI
出版ステータスPublished - 2014 12 4
外部発表はい
イベント22nd International Conference on Pattern Recognition, ICPR 2014 - Stockholm, Sweden
継続期間: 2014 8 242014 8 28

出版物シリーズ

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

Conference

Conference22nd International Conference on Pattern Recognition, ICPR 2014
国/地域Sweden
CityStockholm
Period14/8/2414/8/28

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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