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All Journal International Journal of Electrical and Computer Engineering
Firas Husham Almukhtar
Imam Ja'afar Al-Sadiq University
Computer Science & IT Electrical & Electronics Engineering

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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
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp347-357

Abstract

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.
Co-Authors Batyrkhan Omarov Chengping Wang Md. Abdullah Al Noman Md. Faishal Rahaman Samrat Ray Shahajan Miah Zhai LI