Enhanced Road Lane Detection Facing Sun Glare

Authors

  • Mohammed El Amine Moumene Department of Mathematics and Computer Science, faculty of exact sciences and informatics, University Abdelhamid Ibn Badis Mostaganem, Algeria https://orcid.org/0000-0003-1031-8701
  • Mohamed Benkedadra Department of Mathematics and Computer Science, faculty of exact sciences and informatics, University Abdelhamid Ibn Badis Mostaganem, Algeria https://orcid.org/0000-0002-2590-8344

DOI:

https://doi.org/10.13052/jmm1550-4646.17414

Keywords:

oad lane detection, high dynamic range imaging, neural network.

Abstract

There are several studies on road lane detection but very few address adverse conditions for acquisition such as sun glare. Loss of details in underexposed images captured facing a low sun leads to misleading road lane detection. High Dynamic Range Imaging methods are used to acquire most details in such scenes. Unfortunately, these techniques are heavy on computations and therefore unsuitable for real time road lane detection. In this paper, we propose a machine learning solution that avoids High Dynamic Range Imaging computations that are the radiance map estimation, tone-mapping algorithms and quality measures calculation. We train a neural network on a High Dynamic Range Imaging dataset. The resulting model produces suitable images for road lane detection facing sun glare, in real time. Subjective and objective comparisons with the most popular High Dynamic Range Imaging method, Mertens Algorithm, are conducted to prove the effectiveness of the proposed Neural Network. The delivered images demonstrated an improvement in road lane detection.

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Author Biographies

Mohammed El Amine Moumene, Department of Mathematics and Computer Science, faculty of exact sciences and informatics, University Abdelhamid Ibn Badis Mostaganem, Algeria

Mohammed El Amine Moumene received a computer engineering degree from Mostaganem University in 2010 and a Ph.D. degree in computer vision from Oran 1 University in 2018. He is currently working as an assistant professor at the Department of Mathematics and Computer Science in Mostaganem university. His research areas include computer vision, machine learning and data mining.

Mohamed Benkedadra, Department of Mathematics and Computer Science, faculty of exact sciences and informatics, University Abdelhamid Ibn Badis Mostaganem, Algeria

Mohamed Benkedadra received a bachelor degree in Computer Systems from Mostaganem university in 2018, then a Master degree in Information Systems Engineering from the same university in 2020. He is currently working as the CTO of a start-up and a freelance contractor software engineer. He is specialized in web and crawling technologies, machine learning based computer vision.

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Published

2021-06-21

Issue

Section

Articles