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Precise and Robust Line Detection for Highly Distorted and Noisy Images

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Pattern Recognition (GCPR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9796))

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Abstract

This article presents a method to detect lines in fisheye and distorted perspective images. The detection is performed with subpixel accuracy. By detecting lines in the original images without warping the image with a reverse distortion, the detection accuracy can be noticeably improved. The combination of the edge detection and the line detection to a single step provides a more robust and more reliable detection of larger line segments.

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Authors and Affiliations

  1. Department of Computer Science, Kiel University, Kiel, Germany

    Dominik Wolters & Reinhard Koch

Authors
  1. Dominik Wolters
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  2. Reinhard Koch
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Corresponding author

Correspondence to Dominik Wolters .

Editor information

Editors and Affiliations

  1. University of Hannover, Hannover, Germany

    Bodo Rosenhahn

  2. Max Planck Institute for Informatics, Saarbrücken, Germany

    Bjoern Andres

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Wolters, D., Koch, R. (2016). Precise and Robust Line Detection for Highly Distorted and Noisy Images. In: Rosenhahn, B., Andres, B. (eds) Pattern Recognition. GCPR 2016. Lecture Notes in Computer Science(), vol 9796. Springer, Cham. https://doi.org/10.1007/978-3-319-45886-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-45886-1_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45885-4

  • Online ISBN: 978-3-319-45886-1

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