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Research on Lane Detection Based on Machine Vision

  • Conference paper
Proceedings of the 2011 International Conference on Informatics, Cybernetics, and Computer Engineering (ICCE2011) November 19-20, 2011, Melbourne, Australia

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 110))

Abstract

In order to enhance the real-time and stability of lane detection based on machine vision, a method for line detection based on combined road model is proposed. After image classification according to illumination, the image is processed by different algorithms during image pretreatment. For straight line and curve line in the vicinity, improved Hough Transform (HT) is adopted for line detection and tracking. Both of the road boundaries are fitted using Catmull-Rom Splines based on control points search algorithm for curve line in the distance. For various kinds of lanes on most structural road, experiment results indicate that the method has good robustness and stability.

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Author information

Authors and Affiliations

  1. Intelligent Measure & Control Laboratory, Beijing University of Technology, Beijing, China

    Xining Yang, Dezhi Gao, Jianmin Duan & Lei Yang

Authors
  1. Xining Yang
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  2. Dezhi Gao
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  3. Jianmin Duan
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  4. Lei Yang
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Editor information

Editors and Affiliations

  1. South China Normal University, Yifeng Dasha Building C 1707, Huang Pu Da Dao Zhong, Cui Yuan Jie 8, Tian He Qu, 510000, Guangzhou, China

    Liangzhong Jiang

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© 2011 Springer-Verlag Berlin Heidelberg

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Yang, X., Gao, D., Duan, J., Yang, L. (2011). Research on Lane Detection Based on Machine Vision. In: Jiang, L. (eds) Proceedings of the 2011 International Conference on Informatics, Cybernetics, and Computer Engineering (ICCE2011) November 19-20, 2011, Melbourne, Australia. Advances in Intelligent and Soft Computing, vol 110. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25185-6_69

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  • DOI: https://doi.org/10.1007/978-3-642-25185-6_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25184-9

  • Online ISBN: 978-3-642-25185-6

  • eBook Packages: EngineeringEngineering (R0)

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