Accuracy improvement of viewpoint-free scene character recognition by rotation angle estimation

Kanta Kuramoto, Wataru Oyama, Tetsushi Wakabayashi, Fumitaka Kimura

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

2 被引用数 (Scopus)

抄録

This paper addresses the problem of detecting characters in natural scene image. How to correctly discriminate character/non-character is also a very challenging problem. In this paper, we propose new character/non-character discrimination technique using the rotation angle of characters to improve character detection accuracy in natural scene image. In particular, we individually recognize characters and estimate the rotation angle of those characters by our previously reported method and use the rotation angle for character/non-character discrimination. As the result of the character recognition experiment evaluating 50 alphanumeric natural scene images, we have confirmed the accuracy improvement of precision and -measure by 9.37 % and 4.73 % respectively when compared to the performance with previously reported paper.

本文言語英語
ホスト出版物のタイトルCamera-Based Document Analysis and Recognition - 5th International Workshop, CBDAR 2013, Revised Selected Papers
出版社Springer Verlag
ページ60-70
ページ数11
ISBN(印刷版)9783319051666
DOI
出版ステータス出版済み - 1月 1 2014
イベント5th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2013 - Washington, DC, 米国
継続期間: 8月 23 20138月 23 2013

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)
8357 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他5th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2013
国/地域米国
CityWashington, DC
Period8/23/138/23/13

!!!All Science Journal Classification (ASJC) codes

  • 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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