Title: Performance comparison of various techniques for automatic licence plate recognition systems

Authors: Nitin Sharma; Pawan Kumar Dahiya; Baldev Raj Marwah

Addresses: Department of Electronics and Communication Engineering, Chandigarh University, Gharuan, Punjab, India ' Department of Electronics and Communication Engineering, DCRUST, Murthal, Haryana, India ' Department of Transportation Engineering, IIT, Kanpur, India

Abstract: Automatic licence plate recognition (ALPR) system is direly needed nowadays for various applications like toll collection system, parking system, identification of stolen cars, incident management, electronic payment service, electronic customs clearance of commercial vehicle, automatic security roadside inspection, security monitoring in a car, emergency notification, and personal security, etc. An automatic licence plate recognition system performs three important processing steps on the input image, i.e., extraction, segmentation, and recognition. A number of algorithms are developed for these steps in the last few years. The result of which is significant improvement in the licence plate recognition. The aim of this study is a survey of the existing techniques for licence plate recognition. In this paper, a number of existing techniques for automatic licence plate recognition are presented and their benefits and limitations are discussed. Further, the paper also foresees the future scope in the area of automatic licence plate recognition system.

Keywords: automatic licence plate recognition system; ALPR; character extraction; character segmentation; character recognition; neural network; NN; optical character recognition; OCR; support vector machine; SVM.

DOI: 10.1504/IJCC.2022.10046084

International Journal of Cloud Computing, 2022 Vol.11 No.2, pp.138 - 156

Received: 23 Jul 2019
Accepted: 01 Oct 2019

Published online: 31 Mar 2022 *

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