DocumentCode
1493948
Title
Tensor Voting Based Text Localization in Natural Scene Images
Author
Nguyen, Toan Dinh ; Park, Jonghyun ; Lee, Gueesang
Author_Institution
Dept. of Electron. & Comput. Eng., Chonnam Nat. Univ., Gwangju, South Korea
Volume
17
Issue
7
fYear
2010
fDate
7/1/2010 12:00:00 AM
Firstpage
639
Lastpage
642
Abstract
A new and efficient text localization method by tensor voting is proposed. Tensor voting is used to extract the text line information based on the observation that the text characters are situated close together and arranged in a line or on a smooth curve. The text line information is useful to reduce the false positive rate in region-based text localization methods. The experimental results obtained for different types of natural text images show that the proposed method successfully detects the text regions with a low false-positive rate.
Keywords
data mining; image texture; natural scenes; tensors; text analysis; natural scene images; tensor voting; text line information; text localization; Natural scene image; tensor voting; text line information; text localization;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2010.2049595
Filename
5466222
Link To Document