Drivable Area Extraction based on Shadow Corrected Images

Mohamed Sabry, Mostafa El Hayani, Amr Farag, Slim Abdennadher, Amr El Mougy

Abstract

Drivable area detection is a complex task that needs to operate efficiently in any environmental condition to ensure wide adoption of autonomous vehicles. In the case of low cost camera-based drivable area detection, the spatial information is required to be uniform as much as possible to ensure the robustness and reliability of the results of any algorithm in most weather and illumination conditions. The general change in illumination and shadow intensities present a significant challenge and can cause major accidents if not considered. Moreover, drivable area detection in unstructured environments is more complex due to the absence of vital spatial information such as road markings and lanes. In this paper, a shadow reduction approach combining Computer Vision (CV) - Image Processing (IM) with Deep Learning (DL) is used on a low cost monocular camera based system for reliable and uniform shadow removal. In addition, a validation test is applied with a DL model to validate the approach. This system is developed for the Self-driving Car (SDC) lab at the German University in Cairo (GUC) and is to be used in the shell eco-marathon autonomous competition 2021.

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Paper Citation


in Harvard Style

Sabry M., El Hayani M., Farag A., Abdennadher S. and El Mougy A. (2021). Drivable Area Extraction based on Shadow Corrected Images.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 760-767. DOI: 10.5220/0010238507600767


in Bibtex Style

@conference{icaart21,
author={Mohamed Sabry and Mostafa El Hayani and Amr Farag and Slim Abdennadher and Amr El Mougy},
title={Drivable Area Extraction based on Shadow Corrected Images},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={760-767},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010238507600767},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Drivable Area Extraction based on Shadow Corrected Images
SN - 978-989-758-484-8
AU - Sabry M.
AU - El Hayani M.
AU - Farag A.
AU - Abdennadher S.
AU - El Mougy A.
PY - 2021
SP - 760
EP - 767
DO - 10.5220/0010238507600767