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Text Particles Multi-band Fusion for Robust Text Detection

  • Pengfei Xu
  • Rongrong Ji
  • Hongxun Yao
  • Xiaoshuai Sun
  • Tianqiang Liu
  • Xianming Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5112)

Abstract

Texts in images and videos usually carry important information for visual content understanding and retrieval. Two main restrictions exist in the state-of-the-art text detection algorithms: weak contrast and text-background variance. This paper presents a robust text detection method based on text particles (TP) multi-band fusion to solve there problems. Firstly, text particles are generated by their local binary pattern of pyramid Haar wavelet coefficients in YUV color space. It preserves and uniforms text-background contrasts while extracting multi-band information. Secondly, the candidate text regions are generated via density-based text particle multi-band fusion, and the LHBP histogram analysis is utilized to remove non-text regions. Our TP-based detection framework can robustly locate text regions regardless of diversity sizes, colors, rotations, illuminations and text-background contrasts. Experiment results on ICDAR 03 over the existing methods demonstrate the robustness and effectiveness of the proposed method.

Keywords

text detection text particle multi-band fusion local binary pattern LHBP 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Pengfei Xu
    • 1
  • Rongrong Ji
    • 1
  • Hongxun Yao
    • 1
  • Xiaoshuai Sun
    • 1
  • Tianqiang Liu
    • 1
  • Xianming Liu
    • 1
  1. 1.School of Computer Science and EngineeringHarbin Institute of TechnologyHarbinChina

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