Citation
Tan, Vickey and Loh, Yuen Peng (2022) Dashboard Camera View Vehicle License Plate Compliance Verification. Journal of Logistics, Informatics and Service Science, 9 (4). pp. 37-50. ISSN 2409-2665
Text
Vol.9.No.4.04.pdf - Published Version Restricted to Repository staff only Download (375kB) |
Abstract
Dashboard cameras have become a popular device installed in vehicles around the world. The visual information captured in the form of images and videos has the potential for many practical applications, for instance the verification of license plate compliance can be applied using such cameras, which allow more efficient enforcement as compared to static surveillance cameras or manual verification by authorities. From existing literature, it is found that despite a rise in research and deployment of license plate detection and recognition systems as well as optical character verification, there has yet to be any notable progress of either fields in such a dynamic application. Hence, this project proposes a license plate detection and compliance verification framework for Malaysian standard vehicle license plates. Specifically, the YOLOv4 detector is adapted as the license plate detection model with an image processing pipeline for verification, named the Malaysian License Plate Verification (MLPV) system. Experiments were carried out to evaluate the classification of compliance on license plate only images, dashcam view images supported by license plate detection, and dashcam videos via frames processing. The results show great potential for license plate verification to be performed based on dashcam videos in practical scenarios.
Item Type: | Article |
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Uncontrolled Keywords: | License plate detection, Optical character verification, Computer vision, Image processing |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics |
Divisions: | Faculty of Computing and Informatics (FCI) |
Depositing User: | Ms Nurul Iqtiani Ahmad |
Date Deposited: | 22 Mar 2023 01:57 |
Last Modified: | 22 Mar 2023 01:57 |
URII: | http://shdl.mmu.edu.my/id/eprint/11252 |
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