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Enhanced Characterness for Text Detection in the Wild

  • Aarushi Agrawal
  • Prerana Mukherjee
  • Siddharth Srivastava
  • Brejesh Lall
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 703)

Abstract

Text spotting is an interesting research problem as text may appear at any random place and may occur in various forms. Moreover, ability to detect text opens the horizons for improving many advanced computer vision problems. In this paper, we propose a novel language agnostic text detection method utilizing edge-enhanced maximally stable extremal regions (MSERs) in natural scenes by defining strong characterness measures. We show that a simple combination of characterness cues helps in rejecting the non-text regions. These regions are further fine-tuned for rejecting the non-textual neighbor regions. Comprehensive evaluation of the proposed scheme shows that it provides comparative to better generalization performance to the traditional methods for this task.

Keywords

Text detection HOG Enhanced MSER Stroke width 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Aarushi Agrawal
    • 1
  • Prerana Mukherjee
    • 2
  • Siddharth Srivastava
    • 2
  • Brejesh Lall
    • 2
  1. 1.Department of Electrical EngineeringIndian Institute of Technology KharagpurKharagpurIndia
  2. 2.Department of Electrical EngineeringIndian Institute of Technology DelhiDelhiIndia

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