Laser & Optoelectronics Progress, Volume. 57, Issue 16, 161502(2020)

Lane Marker Line Identification Method in Variable Light Environment

Pingshu Ge1,3, Lie Guo2、*, Guodong Qi2, and Jing Chang2
Author Affiliations
  • 1College of Mechanical and Electronic Engineering, Dalian Minzu University, Dalian, Liaoning 116600, China
  • 2School of Automotive Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
  • 3School of Control Science and Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
  • show less

    To realize the lane marker line identification in complex variable light environment and ensure all-weather lane departure warning, a new lane marker line identification algorithm is proposed. The adaptive image segmentation technology based on OTSU algorithm is used for the lane marker line division for different lighting conditions, and then the adaptive threshold is obtained the weighting process for global and partial thresholds. Sobel operators with gradient directions of 45°and 135° are adopted to extract the lane edge information. Finally, improved Hough transform method is used to finish the lane marker line identification. The road images under different lighting conditions are compared, and the results show that the identification accuracy of the proposed method is improved by 5.7% on average compared with that of the traditional Hough transform method, and the average detection time of a single image is 57.79 ms. The proposed algorithm has good anti-interference performance, can adapt to various lighting conditions, and can meet the real-time requirements of the system.

    Tools

    Get Citation

    Copy Citation Text

    Pingshu Ge, Lie Guo, Guodong Qi, Jing Chang. Lane Marker Line Identification Method in Variable Light Environment[J]. Laser & Optoelectronics Progress, 2020, 57(16): 161502

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Machine Vision

    Received: Dec. 2, 2019

    Accepted: Jan. 7, 2020

    Published Online: Aug. 5, 2020

    The Author Email: Guo Lie (guolie@163.com)

    DOI:10.3788/LOP57.161502

    Topics