Advances in lane marking detection algorithms for all-weather conditions
Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advance...
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Institute of Advanced Engineering and Science
2021
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Online Access: | http://eprints.utem.edu.my/id/eprint/25810/2/ADVANCES%20IN%20LANE%20MARKING%20DETECTION%20ALGORITHMS%20FOR%20ALL-WEATHER.PDF http://eprints.utem.edu.my/id/eprint/25810/ http://ijece.iaescore.com/index.php/IJECE/article/view/23491/14954 |
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my.utem.eprints.258102022-04-11T11:58:15Z http://eprints.utem.edu.my/id/eprint/25810/ Advances in lane marking detection algorithms for all-weather conditions Ab. Ghani, Hadhrami Besar, Rosli Md. Sani, Zamani Kamaruddin, Mohd Nazeri Syahali, Syabeela Mohamed Daud, Atiqullah Martin, Aerun Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advanced driving assistance systems (ADAS). Therefore, this paper conducts a thorough review on vision-based lane marking detection algorithms developed for all-weather conditions. The review methodology consists of two major areas, which are a review on the general system models employed in the lane marking detection algorithms and a review on the types of weather conditions considered for the algorithms. Throughout the review process, it is observed that the lane marking detection algorithms in literature have mostly considered weather conditions such as fog, rain, haze and snow. A new contour-angle method has also been proposed for lane marker detection. Most of the research work focus on lane detection, but the classification of the types of lane markers remains a significant research gap that is worth to be addressed for ADAS and intelligent transport systems. Institute of Advanced Engineering and Science 2021-08 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25810/2/ADVANCES%20IN%20LANE%20MARKING%20DETECTION%20ALGORITHMS%20FOR%20ALL-WEATHER.PDF Ab. Ghani, Hadhrami and Besar, Rosli and Md. Sani, Zamani and Kamaruddin, Mohd Nazeri and Syahali, Syabeela and Mohamed Daud, Atiqullah and Martin, Aerun (2021) Advances in lane marking detection algorithms for all-weather conditions. International Journal of Electrical and Computer Engineering, 11 (4). pp. 3365-3373. ISSN 2088-8708 http://ijece.iaescore.com/index.php/IJECE/article/view/23491/14954 10.11591/ijece.v11i4.pp3365-3373 |
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Driving vehicles in all-weather conditions is challenging as the lane markers tend to be unclear to the drivers for detecting the lanes. Moreover, the vehicles will move slower hence increasing the road traffic congestion which causes difficulties in detecting the lane markers especially for advanced driving assistance systems (ADAS). Therefore, this paper conducts a thorough review on vision-based lane marking detection algorithms developed for all-weather conditions. The review methodology consists of two major areas, which are a review on the general system models employed in the lane marking detection algorithms and a review on the types of weather conditions considered for the algorithms. Throughout the review process, it is observed that the lane marking detection algorithms in literature have mostly considered weather conditions such as fog, rain, haze and snow. A new contour-angle method has also been proposed for lane marker detection. Most of the research work focus on lane detection, but the classification of the types of lane markers remains a significant research gap that is worth to be addressed for ADAS and intelligent transport systems. |
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Article |
author |
Ab. Ghani, Hadhrami Besar, Rosli Md. Sani, Zamani Kamaruddin, Mohd Nazeri Syahali, Syabeela Mohamed Daud, Atiqullah Martin, Aerun |
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Ab. Ghani, Hadhrami Besar, Rosli Md. Sani, Zamani Kamaruddin, Mohd Nazeri Syahali, Syabeela Mohamed Daud, Atiqullah Martin, Aerun Advances in lane marking detection algorithms for all-weather conditions |
author_facet |
Ab. Ghani, Hadhrami Besar, Rosli Md. Sani, Zamani Kamaruddin, Mohd Nazeri Syahali, Syabeela Mohamed Daud, Atiqullah Martin, Aerun |
author_sort |
Ab. Ghani, Hadhrami |
title |
Advances in lane marking detection algorithms for all-weather conditions |
title_short |
Advances in lane marking detection algorithms for all-weather conditions |
title_full |
Advances in lane marking detection algorithms for all-weather conditions |
title_fullStr |
Advances in lane marking detection algorithms for all-weather conditions |
title_full_unstemmed |
Advances in lane marking detection algorithms for all-weather conditions |
title_sort |
advances in lane marking detection algorithms for all-weather conditions |
publisher |
Institute of Advanced Engineering and Science |
publishDate |
2021 |
url |
http://eprints.utem.edu.my/id/eprint/25810/2/ADVANCES%20IN%20LANE%20MARKING%20DETECTION%20ALGORITHMS%20FOR%20ALL-WEATHER.PDF http://eprints.utem.edu.my/id/eprint/25810/ http://ijece.iaescore.com/index.php/IJECE/article/view/23491/14954 |
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