Farooq, M.U., Ahmed, A. orcid.org/0000-0002-4980-2376, Khan, S.M. et al. (1 more author) (2021) Estimation of Traffic Occupancy using Image Segmentation. Engineering, Technology and Applied Science Research, 11 (4). pp. 7291-7295. ISSN 2241-4487
Abstract
Increased traffic flow results in high road occupancy. Traffic road occupancy is often used as a parameter for the prediction of traffic conditions by traffic engineers. Although traffic monitoring systems are based on a large number of technologies, challenges are still present. Most of the methods work efficiently for free-flow traffic but not in heavy congestion. Image processing techniques are more effective than other methods, as they are based on loop sensors and detectors to monitor road traffic. A huge number of image frames are processed in image processing hence there is a need for a more efficient and low-cost image processing technique for accurate vehicle detection. In this paper, a novel approach is adopted to calculate road occupancy. The proposed framework has robust performance under road conjunction and diverse environmental conditions. A combination of image segmentation threshold technique and shadow removal technique is used. The study comprised of segmenting 1056 images extracted from recorded videos. The obtained results by image segmentation were compared with traffic road occupancy calculated manually using Autocad. A final percentage difference of 8.17 was observed.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | image segmentation; road occupancy; shadow removal |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Sustainable Transport Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Jun 2024 09:58 |
Last Modified: | 13 Jun 2024 09:58 |
Status: | Published |
Publisher: | Engineering, Technology and Applied Science Research |
Identification Number: | 10.48084/etasr.4218 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:213476 |
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