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Efficient and Robust Lane Detection Using Three-Stage Feature Extraction with Line Fitting

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Advances in Multimedia Information Processing – PCM 2017 (PCM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10735))

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Abstract

Lane detection plays an important role in advanced driver assistance system. The objective of lane detection is to separate lane markings from background and to locate their positions. Challenges of lane detection mainly lie in large appearance variations. These variations mainly include shadows, occlusion, variable lighting conditions, and different weather conditions, e.g., sunny or rainy days. In this paper, we propose a method named Lane Detection with Three-stage Feature Extraction to detect lane proposals. The three-stage features include contrast feature, line structure feature, and convex signal feature. Three feature extraction methods are devised for each of the three-stage respectively. After getting lane proposals through the processing of the three methods, we use straight line model to fit these proposals based on RANSAC method. Extensive experiments demonstrate that our method is stable and can find lane proposals exactly given the lane in the scene.

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Acknowledgments

This work was supported by the NSFC (under Grant U1509206, 61472276).

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Authors and Affiliations

  1. School of Computer Science and Technology, Tianjin University, Tianjin, China

    Aming Wu & Yahong Han

Authors
  1. Aming Wu
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  2. Yahong Han
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Corresponding author

Correspondence to Yahong Han .

Editor information

Editors and Affiliations

  1. University of Electronic Science and Technology of China, Chengdu, China

    Bing Zeng

  2. University of Chinese Academy of Sciences, Beijing, China

    Qingming Huang

  3. University of Ottawa, Ottawa, Ontario, Canada

    Abdulmotaleb El Saddik

  4. University of Electronic Science and Technology of China, Chengdu, China

    Hongliang Li

  5. Chinese Academy of Sciences, Beijing, China

    Shuqiang Jiang

  6. Harbin Institute of Technology, Harbin, China

    Xiaopeng Fan

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Wu, A., Han, Y. (2018). Efficient and Robust Lane Detection Using Three-Stage Feature Extraction with Line Fitting. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10735. Springer, Cham. https://doi.org/10.1007/978-3-319-77380-3_44

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  • DOI: https://doi.org/10.1007/978-3-319-77380-3_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77379-7

  • Online ISBN: 978-3-319-77380-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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