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D-LSD: A Distorted Line Segment Detector for Calibrated Images

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Computer Analysis of Images and Patterns (CAIP 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 13053))

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Abstract

In this paper, we present an algorithm for the detection of line segments directly on the original, distorted images captured by calibrated wide-angle, fisheye and omnidirectional cameras. Distorted line segments are detected as convex polygonal chains of connected straight lines and then validated as the projection of 3D lines. This last validation step is our main contribution, which is formulated in a generic way in order to allow the detection of line segments from calibrated central projection vision systems and without requiring the rectification of the whole image. We evaluate our method with real images from a publicly available dataset and compare it with state-of-the-art alternatives, achieving comparable line detection performance without requiring image rectification. Additionally, we provide an open source reference implementation.

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Notes

  1. 1.

    The reference implementation of D-LSD as well as the others’ used for evaluation are publicly available at: https://github.com/dzunigan/line_detection.

  2. 2.

    https://github.com/tum-vision/mono_dataset_code.

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Acknowledgements

This research was funded by the Government of Spain and the European Regional Development’s funds (FEDER) under the projects ARPEGGIO (PID2020-117057) and WISER (DPI2017-84827-R).

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Authors and Affiliations

  1. Machine Perception and Intelligent Robotics Group (MAPIR), Department of System Engineering and Automation, University of Malaga, Malaga, Spain

    David Zuñiga-Noël, Francisco-Angel Moreno & Javier Gonzalez-Jimenez

Authors
  1. David Zuñiga-Noël
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  2. Francisco-Angel Moreno
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  3. Javier Gonzalez-Jimenez
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Corresponding author

Correspondence to Francisco-Angel Moreno .

Editor information

Editors and Affiliations

  1. Cyprus University of Technology, Limassol, Cyprus

    Nicolas Tsapatsoulis

  2. University of Cyprus, Nicosia, Cyprus

    Andreas Panayides

  3. University of Cyprus, Nicosia, Cyprus

    Theo Theocharides

  4. Cyprus University of Technology, Limassol, Cyprus

    Andreas Lanitis

  5. University of Cyprus, Nicosia, Cyprus

    Constantinos Pattichis

  6. University of Salerno, Salerno, Italy

    Mario Vento

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Zuñiga-Noël, D., Moreno, FA., Gonzalez-Jimenez, J. (2021). D-LSD: A Distorted Line Segment Detector for Calibrated Images. In: Tsapatsoulis, N., Panayides, A., Theocharides, T., Lanitis, A., Pattichis, C., Vento, M. (eds) Computer Analysis of Images and Patterns. CAIP 2021. Lecture Notes in Computer Science(), vol 13053. Springer, Cham. https://doi.org/10.1007/978-3-030-89131-2_39

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  • DOI: https://doi.org/10.1007/978-3-030-89131-2_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89130-5

  • Online ISBN: 978-3-030-89131-2

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