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An Effective and Fast Lane Detection Algorithm

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Advances in Visual Computing (ISVC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5359))

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Abstract

Lane detection is crucial for autonomous driving. In this paper, we present an effective and fast lane detection algorithm. The proposed algorithm includes three novelties. First, we set a region of interest (ROI) appropriate to reduce nonessential cost of computation. Second, we determine a real midpoint between two road lines for each frame. The midpoint can be used to classify the candidates of lane marking points to right and left effectively. Finally, we use a temporal trajectory strategy to avoid the failure of lane detection, which is generally caused by shadows of bridges or neighboring vehicles. Experimental results show that the proposed algorithm can label the location of lane marking accurately and fast. It processes a frame only 16 ms and can solve the problems caused by lighting change, shadows, and vehicle occlusions.

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References

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Author information

Authors and Affiliations

  1. Department of Applied Electronics Technology, National Taiwan Normal University, Taipei, 10612, Taiwan, R.O.C.

    Chung-Yen Su & Gen-Hau Fan

Authors
  1. Chung-Yen Su
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  2. Gen-Hau Fan
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Mitsubishi Electric Research Laboratories, P.O. Box 02139, Cambridge, MA, USA

    Fatih Porikli

  7. Computer and Information Science and Engineering, University of Florida, P.O. Box, FL 32611-6120, Gainsville, USA

    Jörg Peters

  8. IBM T.J. Watson Research Center, 19 Skyline Drive, NY 10532, Hawthorne, USA

    James Klosowski

  9. 128 Memorial Mall, Stewart B001, IN 47907, West Lafayette, USA

    Laura Arns

  10. Denver Museum of Nature and Space, 2001 Colorade Blvd. Denver,, CO 80205, USA

    Yu Ka Chun

  11. Departmen of Computer Science,, NC State University, Campus Box 8206, NC 27695-8206, Raleigh, USA

    Theresa-Marie Rhyne

  12. Los Alamos National Labs, P.O. Box 1663, NM 87545, Los Alamos, USA

    Laura Monroe

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© 2008 Springer-Verlag Berlin Heidelberg

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Su, CY., Fan, GH. (2008). An Effective and Fast Lane Detection Algorithm. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_94

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  • DOI: https://doi.org/10.1007/978-3-540-89646-3_94

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89645-6

  • Online ISBN: 978-3-540-89646-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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