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Multimedia Tools and Applications

, Volume 76, Issue 15, pp 16625–16655 | Cite as

Arbitrarily-oriented multi-lingual text detection in video

  • Vijeta Khare
  • Palaiahnakote Shivakumara
  • Raveendran Paramesran
  • Michael Blumenstein
Article

Abstract

Text detection in arbitrarily-oriented multi-lingual video is an emerging area of research because it plays a vital role for developing real-time indexing and retrieval systems. In this paper, we propose to explore moments for identifying text candidates. We introduce a novel idea for determining automatic windows to extract moments for tackling multi-font and multi-sized text in video based on stroke width information. The temporal information is explored to find deviations between moving and non-moving pixels in successive frames iteratively, which results in static clusters containing caption text and dynamic clusters containing scene text, as well as background pixels. The gradient directions of pixels in static and dynamic clusters are analyzed to identify the potential text candidates. Furthermore, boundary growing is proposed that expands the boundary of potential text candidates until it finds neighbor components based on the nearest neighbor criterion. This process outputs text lines appearing in the video. Experimental results on standard video data, namely, ICDAR 2013, ICDAR 2015, YVT videos and on our own English and Multi-lingual videos demonstrate that the proposed method outperforms the state-of-the-art methods.

Keywords

Higher order moments Stroke width distance, dynamic window Caption text Region growing Arbitrarily-oriented text detection Multi-lingual text detection 

Notes

Acknowledgments

The work is also partly supported by the University of Malaya HIR under Grant No: UM.C/625/1/HIR/MOHE/ENG/42. The authors would like to thank the anonymous reviewers for their constructive comments and suggestions, which helped us to improve the quality and to clarify the paper significantly.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Vijeta Khare
    • 1
  • Palaiahnakote Shivakumara
    • 2
    • 3
  • Raveendran Paramesran
    • 1
  • Michael Blumenstein
    • 4
  1. 1.Faculty of EngineeringUniversity of MalayaKuala LumpurMalaysia
  2. 2.Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala LumpurMalaysia
  3. 3.Computer Systems and Information TechnologyUniversity of MalayaMalaysiaMalaysia
  4. 4.School of SoftwareUniversity of Technology SydneySydneyAustralia

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