Artificial Intelligence Techniques for the Recognition of Multi-Plate Multi-vehicle Tracking Systems: A Systematic Review

In recent years, the number of vehicles has been rising enormously, which has caused difficulties in detecting a vehicle and the person involved in any criminal activity or traffic violation. With the advent of Artificial Intelligence, the Automatic License Plate Recognition System has been used for...

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Bibliographic Details
Published in:Archives of computational methods in engineering 2022-11, Vol.29 (7), p.4897-4914
Main Authors: Kaur, Parneet, Kumar, Yogesh, Gupta, Surbhi
Format: Article
Language:English
Subjects:
Artificial intelligence
Automatic vehicle identification systems
Character recognition
Crime
Engineering
Image acquisition
License plates
Licenses
Mathematical and Computational Engineering
Photosensitivity
Review Article
Tracking systems
Traffic control
Traffic management
Vehicle identification
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Summary:In recent years, the number of vehicles has been rising enormously, which has caused difficulties in detecting a vehicle and the person involved in any criminal activity or traffic violation. With the advent of Artificial Intelligence, the Automatic License Plate Recognition System has been used for quite some time. automatic licence plate recognition (ALPR) is a photosensitive identification system that identifies the license numbers after effective detection from an acquired image dataset. The ALPR system also plays a significant role in law enforcement and rendering services in smart cities. It is an automated system that can identify a vehicle by recognizing the characters of the license plate. This system is fundamental to traffic control and managing criminal activities, intelligent parking systems, and various applications. Also, it provides a brief outline of various license plate detection and recognition techniques reported by researchers in India and other countries. The comparative analysis also highlights the work done in the direction of automatic license plate recognition by the different researchers using various learning techniques and results obtained by using the detection rate, accuracy, and localization. This study follows an investigational approach to analyze the character recognition techniques used in ALPR systems; research challenges the researchers face. This paper contributes an extensive review of the existing scenario of ALPR systems.
ISSN:1134-3060
1886-1784
DOI:10.1007/s11831-022-09753-4