Citation

Martin, Aerun and Kamaruddin, Mohd Nazeri and Md Sani, Zamani and Abas, Fazly Salleh (2021) Road Marker Classification Mechanism Using Slope Contour Analysis in Foggy. In: 2nd FET PG Engineering Colloquium Proceedings 2021, 1-15 Dec. 2021, Online Conference. (Unpublished)

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Abstract

Obtaining the dark channel prior in foggy images will produce significant difference in pixels values of the foggy-free areas and atmospheric lights. Since the foggy images is the linear combination of the atmospheric light and the original non-foggy image, the fraction of atmospheric image from the foggy image will retrieve the original image without the impact of foggy. Once the foggy is reduced, the road marker visibility will be improved indiscriminately which can be further processed for feature extraction using Convolutional Neural Network.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Road marker classification, image enhancement, Computational Neural Network
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	25 Jan 2022 07:50
Last Modified:	20 Feb 2023 07:34
URII:	http://shdl.mmu.edu.my/id/eprint/9873

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