• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Lane Detection Based on Inverse Perspective Transformation and Kalman Filter

Vol. 12, No.2, February 28, 2018
10.3837/tiis.2018.02.006, Download Paper (Free):

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.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
Yingping Huang, Yangwei Li, Xing Hu and Wenyan Ci, "Lane Detection Based on Inverse Perspective Transformation and Kalman Filter," KSII Transactions on Internet and Information Systems, vol. 12, no. 2, pp. 643-661, 2018. DOI: 10.3837/tiis.2018.02.006

[ACM Style]
Huang, Y., Li, Y., Hu, X., and Ci, W. 2018. Lane Detection Based on Inverse Perspective Transformation and Kalman Filter. KSII Transactions on Internet and Information Systems, 12, 2, (2018), 643-661. DOI: 10.3837/tiis.2018.02.006