A computer vision-based lane detection technique using gradient threshold and hue-lightness-saturation value for an autonomous vehicle

Md. Abdullah Al Noman (Beijing Institute of Technology)
Zhai LI (Beijing Institute of Technology)
Firas Husham Almukhtar (Imam Ja'afar Al-Sadiq University)
Md. Faishal Rahaman (Beijing Institute of Technology)
Batyrkhan Omarov (Al-Farabi Kazakh National University)
Samrat Ray (Sunstone Calcutta Institute of Engineering and Management)
Shahajan Miah (Bangladesh University of Business and Technology)
Chengping Wang (Beijing Institute of Technology)

International Journal of Electrical and Computer Engineering
Vol 13, No 1: February 2023

Automatic lane detection for driver assistance is a significant component in developing advanced driver assistance systems and high-level application frameworks since it contributes to driver and pedestrian safety on roads and highways. However, due to several limitations that lane detection systems must rectify, such as the uncertainties of lane patterns, perspective consequences, limited visibility of lane lines, dark spots, complex background, illuminance, and light reflections, it remains a challenging task. The proposed method employs vision-based technologies to determine the lane boundary lines. We devised a system for correctly identifying lane lines on a homogeneous road surface. Lane line detection relies heavily on the gradient and hue lightness saturation (HLS) thresholding which detects the lane line in binary images. The lanes are shown, and a sliding window searching method is used to estimate the color lane. The proposed system achieved 96% accuracy in detecting lane lines on the different roads, and its performance was assessed using data from several road image databases under various illumination circumstances.