Automatic license plate recognition system for traffic monitoring

dc.contributor.author	Asiedu, Patrick Nana
dc.date.accessioned	2023-05-05T11:08:07Z
dc.date.available	2023-05-05T11:08:07Z
dc.date.issued	2021-05
dc.description	Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Electrical and Electronic Engineering, May 2021
dc.description.abstract	In Ghana, road accidents are primarily caused by road traffic law violations. Technologies, such as Automatic License Plate Recognition(ALPR), have been implemented to help reduce road accidents in other countries. However, they are not utilized in less developed countries like Ghana. In this project, an ALPR is implemented using two approaches: computer vision algorithms and YOLOv4. The computer vision approach obtained a 71% ALPR accuracy at 3 meters distance and 60 degrees inclination between the license plate and camera at 7 pm night time. The YOLOv4 obtained a 99% ALPR accuracy at 6 meters distance and 60 degrees inclination between the license plate at 7 pm night time.The results of testing show that the YOLOv4 approach was more accurate than the one with computer vision.
dc.description.sponsorship	Ashesi University
dc.identifier.uri	https://hdl.handle.net/20.500.11988/856
dc.language.iso	en
dc.subject	road safety	en
dc.title	Automatic license plate recognition system for traffic monitoring
dc.type	Capstone project	en

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