Lane Line Detection and Recognition by Polarisation Imaging

The detection of lane lines in an adverse environments is a complex and popular topic in both assisted safe driving and intelligent vehicle research. An optical polarization theory was introduced into traditional lane detection technology, aimed at external adverse road environments. In addition, a lane-line detection method was proposed based on imaging polarization by analysing the basic features of the lane line image. Firstly, a three-angle special environment road polarization-image was collected to obtain a polarization degree image. Secondly, the polarization degree images were converted by binarization, divided first into regions of interest, and then according to the straight-line feature of the lane edge before the edge detection of road images were conducted; hence, the actual lane line edge could be obtained. Finally, the improved Hough algorithm proposed through the Hough transform principle could detect the lane marking; and the vehicle driving deflection angle was calculated. The simulation and experimental results demonstrate this method can accurately detect and identify the lane line in an adverse environment with an error of less than 0.3° between the detected and actual declination angle of the lane line.