Abstract
License Plate Recognition (LPR) is an image processing technology that uses license plate number to identify vehicles. Many current LPR research fully rely on still photos, whereby minimal attention is given to an automated real-time LPR. Several automated real-time based LPR methods are less practical in crucial circumstances, such as the use of non-fixed cameras, recognition of moving vehicles in complex scenes, and the occurrence of extreme illumination variations.
Thus, the aim of this project is to develop an automated real-time car plate number detection and recognition system that utilize a mobile application. In this proposed system, the images captured from the mobile cameras can either be transmitted to a server or perform offline for automated detection and recognition using a suitable mobile resource. This can be achieved by enhancing the algorithm for LPR using deep learning. This paper presents a new proposed algorithm that efficiently identify license plate number accurately and without any human intervention.
Hence, Intelligent Transportation Systems (ITS) will benefit considerably from the proposed automated real-time LPR system. The integration of advanced intelligent system in vehicle surveillance will allow an effective adoption of smart technologies in cities and transportation industry.
Keywords: license plate recognition, deep learning, intelligent transportation system, image processing.
Funded by MARA (DPIM), with support from Universiti Kuala Lumpur.
Cite
@article{osman2022real,
title = {{Development of Real-Time Vehicle's Plate Number Recognition System Using Deep Learning Approach for Surveillance System in Malaysia}},
author = {Osman, Husna and Abdullah, Munaisyah and Mustapha, Jawahir Che and Al-Nawah, Salah Mohammed Yahya and Jaffar, Jasrina},
year = {2022},
journal = {Jurnal Penyelidikan Berimpak Tinggi MARA},
volume = {Jilid 2},
pages = {105--122},
url = {https://salahmyn.me/research/real-time-plate-recognition-malaysia/}
}