AdaBoost for text detection in natural scene

Jung Jin Lee, Pyoung Hean Lee, Seong Whan Lee, Alan Yuille, Christof Koch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

140 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011
Pages429-434
Number of pages6
DOIs
Publication statusPublished - 2011
Event11th International Conference on Document Analysis and Recognition, ICDAR 2011 - Beijing, China
Duration: 2011 Sep 182011 Sep 21

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN (Print)1520-5363

Other

Other11th International Conference on Document Analysis and Recognition, ICDAR 2011
CountryChina
CityBeijing
Period11/9/1811/9/21

Keywords

  • AdaBoost
  • text detection
  • text location

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Lee, J. J., Lee, P. H., Lee, S. W., Yuille, A., & Koch, C. (2011). AdaBoost for text detection in natural scene. In Proceedings - 11th International Conference on Document Analysis and Recognition, ICDAR 2011 (pp. 429-434). [6065348] (Proceedings of the International Conference on Document Analysis and Recognition, ICDAR). https://doi.org/10.1109/ICDAR.2011.93