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21 November 2022
Article (Scientific journals)
Enhanced Road Lane Detection Facing Sun Glare
El Amine Moumene, Mohammed; Benkedadra, Mohamed 
2021 • In Journal of Mobile Multimedia, 17 (4), p. 773 - 788
Peer reviewed
 

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Keywords :
High dynamic range imaging; Neural network; Road lane detection; Communication; Media Technology; Industrial and Manufacturing Engineering
Abstract :
[en] 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.
Disciplines :
Computer science
Author, co-author :
El Amine Moumene, Mohammed;  Department of Mathematics and Computer Science, Faculty of Exact Sciences and Informatics, University Abdelhamid Ibn Badis Mostaganem, Algeria
Benkedadra, Mohamed  ;  Université de Mons - UMONS
Language :
English
Title :
Enhanced Road Lane Detection Facing Sun Glare
Publication date :
02 June 2021
Journal title :
Journal of Mobile Multimedia
ISSN :
1550-4646
Publisher :
River Publishers
Volume :
17
Issue :
4
Pages :
773 - 788
Peer reviewed :
Peer reviewed
Development Goals :
9. Industry, innovation and infrastructure
Research institute :
Infortech
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