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Local binary pattern-based features for text identification of web images

  • Insook Jung*
  • , Il Seok Oh
  • *Corresponding author for this work
  • Jeonbuk National University

Research output: Contribution to conferenceConference paperpeer-review

Abstract

We present a method of robustly identifying a text block in complex web images. The method is a MLP (Multilayer perceptron) classifier trained on LBP (Local binary patterns), wavelet and shape feature spaces. Especially, we propose adaptive masks of LBP which responses flexibly to various character sizes. Most of previous works use fixed mask size or multi level scales by pyramid schemes, which may have weakness in dealing with diverse size of text. Experiments carried out on 100 web images show promising results.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4320-4323
Number of pages4
ISBN (Print)9780769541099
DOIs
StatePublished - 2010

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Keywords

  • Adaptive mask
  • Component
  • LBP
  • Text identification
  • Web image

Quacquarelli Symonds(QS) Subject Topics

  • Computer Science & Information Systems
  • Data Science

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