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

Md. Abdullah Al Noman, Zhai LI, Firas Husham Almukhtar, Md. Faishal Rahaman, Batyrkhan Omarov, Samrat Ray, Shahajan Miah, Chengping Wang


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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DOI: http://doi.org/10.11591/ijece.v13i1.pp347-357

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).