Please use this identifier to cite or link to this item: http://dspace.aiub.edu:8080/jspui/handle/123456789/1843
Title: Vehicle Number Plate Detection and Recognition Techniques: A Review
Authors: Parvin, Shahnaj
Islam, Dr. Ezharul
Rozario, Liton J.
Keywords: Number plate detection
Number plate recognition
Optical Character Recognition
You Only Look Once (YOLO)
Convolutional Neural Network
Vehicle detection
Issue Date: 17-Mar-2021
Publisher: ASTES
Series/Report no.: Volume 06 (02);ASTESJ_060249
Abstract: Vehicle number plate detection and recognition is an integral part of the Intelligent Transport System (ITS) as every vehicle has a number plate as part of its identity. The quantity of vehicles on road is growing in the modern age, so numerous crimes are also increasing day by day. Almost every day the news of missing vehicles and accidents are perceived. Vehicles tracking is often required to investigate all these illegal activities. So, vehicle number plate identification, as well as recognition, is an active field of study. However, vehicle number plate identification has always been a challenging task for some reasons, for example, brightness changes, vehicle shadows, and non-uniform license plate character type, various styles, and environment color effects. In this review work, various state-of-the-art vehicle number plate detection, as well as recognition strategies, have been outlined on how researchers have experimented with these techniques, which methods have been developed or used, what datasets have been focused on, what kinds of characters have been recognized and how much progress have been achieved. Hopefully, for future research, this review would be very useful.
URI: http://dspace.aiub.edu:8080/jspui/handle/123456789/1843
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