Published September 2011
| public
Book Section - Chapter
AdaBoost for Text Detection in Natural Scene
Chicago
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Abstract
Detecting text regions in natural scenes is an important part of computer vision. We propose a novel text detection algorithm that extracts six different classes features of text, and uses Modest AdaBoost with multi-scale sequential search. Experiments show that our algorithm can detect text regions with a f= 0.70, from the ICDAR 2003 datasets which include images with text of various fonts, sizes, colors, alphabets and scripts.
Additional Information
© 2011 IEEE. This research was supported by WCU(World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (R31-10008).Additional details
- Eprint ID
- 121177
- Resolver ID
- CaltechAUTHORS:20230426-654321000.10
- National Research Foundation of Korea
- R31-10008
- Created
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2023-05-01Created from EPrint's datestamp field
- Updated
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2023-05-01Created from EPrint's last_modified field
- Caltech groups
- Koch Laboratory (KLAB)