A computer vision-based lane detection technique using gradient threshold and hue-lightness-saturation value for an autonomous vehicle
Al Noman M.A. Li Z. Almukhtar F.H. Rahaman M.F. Omarov B. Ray S. Miah S. Wang C.
February 2023Institute of Advanced Engineering and Science
International Journal of Electrical and Computer Engineering
2023#13Issue 1347 - 357 pp.
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.
Autonomous vehicles , Computer vision , Lane detection , Perspective transformation , Sliding window searching , Thresholding
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National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China
School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China
Department of Computer Technical Engineering, Imam Jaafar Al-Sadiq University, Kirkuk, Iraq
Department of Information Systems, Al-Farabi Kazakh National University, Almaty, Kazakhstan
Department of Economics, Sunstone Calcutta Institute of Engineering and Management, Kolkata, India
Department of Electrical & Electronic Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh
National Engineering Laboratory for Electric Vehicles, Beijing institute of Technology, Haidian District, Beijing, China
National Engineering Laboratory for Electric Vehicles
School of Mechanical Engineering
Department of Computer Technical Engineering
Department of Information Systems
Department of Economics
Department of Electrical & Electronic Engineering
National Engineering Laboratory for Electric Vehicles
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