Text detection in natural scene images with user-intention

Liuan Wang, Yutaka Katsuyama, Wei Fan, Yuan He, Jun Sun, Yoshinobu Hotta

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

1 Citation (Scopus)

Abstract

We propose an accurate and robust coarse-to-fine text detection scheme with user-intention which captures the intrinsic characteristics of natural scene texts. In the coarse detection stage, a double edge detector is designed to estimate the symmetry of stroke and the stroke width, which help segment the foreground. Then the initial user-intention region is extended to generate a coarse bounding box based on the estimated foreground. In the refinement stage, candidate connected components (CCs) from Niblack decomposition, are grouped together by location to form text lines after noise removal and layer selection. Experimental results demonstrate the effectiveness of the proposed method which yields higher performance compared with state-of-the-art methods.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
Pages2256-2259
Number of pages4
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia
Duration: 2013 Sep 152013 Sep 18

Publication series

Name2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Conference

Conference2013 20th IEEE International Conference on Image Processing, ICIP 2013
CountryAustralia
CityMelbourne, VIC
Period13/9/1513/9/18

Keywords

  • double edge symmetry
  • greedy CCs grouping
  • stroke width constraint
  • text detection

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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