DocumentCode
1865068
Title
Fast and effective text detection
Author
Li, Xiaojun ; Wang, Weiqiang ; Jiang, Shuqiang ; Huang, Qingming ; Gao, Wen
Author_Institution
Grad. Univ. of Chinese Acad. of Sci., Beijing
fYear
2008
fDate
12-15 Oct. 2008
Firstpage
969
Lastpage
972
Abstract
Text in images and videos is a significant cue for visual content understanding and retrieval. In this paper, we present a fast and effective approach to locate text lines even under complex background. First, our algorithm uses the stroke filter to calculate the stroke maps in horizontal, vertical, left-diagonal, right-diagonal directions. Then a 24- dimensional feature is extracted for each sliding window and a SVM is used to obtain rough text regions. The rough text regions are further refined through a group of rules. And candidate text lines were localized more accurately through projection profile of the refined text regions. Finally another SVM classifier based on a 6-dimensional feature is used to verify the candidate text lines. The experimental results on challenging databases show that this approach can fast and effectively detect and localize text lines.
Keywords
feature extraction; filtering theory; image classification; support vector machines; text analysis; video signal processing; 24-dimensional feature extraction; SVM classifier; horizontal map; left-diagonal map; projection profile; right-diagonal map; rough text region; sliding window; stroke filter; stroke maps; support vector machine; text line detection; text line location; vertical map; visual content retrieval; visual content understanding; Detectors; Feature extraction; Filters; Flowcharts; Image retrieval; Learning systems; Machine learning algorithms; Support vector machine classification; Support vector machines; Videos; SVM; Stroke Filter; Text Detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location
San Diego, CA
ISSN
1522-4880
Print_ISBN
978-1-4244-1765-0
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2008.4711918
Filename
4711918
Link To Document