KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Lane Detection Based on Inverse Perspective Transformation and Kalman Filter

  • Huang, Yingping (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology) ;
  • Li, Yangwei (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology) ;
  • Hu, Xing (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology) ;
  • Ci, Wenyan (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology)
  • Received : 2017.04.13
  • Accepted : 2017.09.21
  • Published : 2018.02.28
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Abstract

This paper proposes a novel algorithm for lane detection based on inverse perspective transformation and Kalman filter. A simple inverse perspective transformation method is presented to remove perspective effects and generate a top-view image. This method does not need to obtain the internal and external parameters of the camera. The Gaussian kernel function is used to convolute the image to highlight the lane lines, and then an iterative threshold method is used to segment the image. A searching method is applied in the top-view image obtained from the inverse perspective transformation to determine the lane points and their positions. Combining with feature voting mechanism, the detected lane points are fitted as a straight line. Kalman filter is then applied to optimize and track the lane lines and improve the detection robustness. The experimental results show that the proposed method works well in various road conditions and meet the real-time requirements.

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References

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