CaltechAUTHORS
Published September 2011 | Version public
Book Section - Chapter Metadata-only

AdaBoost for Text Detection in Natural Scene

Creators

  • 1. ROR icon Korea University
  • 2. ROR icon University of California, Los Angeles
  • 3. ROR icon California Institute of Technology

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

Identifiers

Eprint ID
121177
Resolver ID
CaltechAUTHORS:20230426-654321000.10

Related works

Describes
10.1109/ICDAR.2011.93 (DOI)

Funding

National Research Foundation of Korea
R31-10008

Dates

Created
2023-05-01
Created from EPrint's datestamp field
Updated
2023-05-01
Created from EPrint's last_modified field

Caltech Custom Metadata

Caltech groups
Koch Laboratory (KLAB)