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Evaluation and Enhancement of Automatic License Pattern Recognition System
Conference proceeding   Open access

Evaluation and Enhancement of Automatic License Pattern Recognition System

Nauman Akram Butt, Anchal Garg and Pradeep Hewage
2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)
12th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO'2025) (Noida NCR, India, 18/09/2025–19/09/2025)
27/11/2025

Abstract

Number plate Licence plate Vehicle cloning Evaluation metric Logical framework Vehicle detection Usual route identification ALPR
Vehicle cloning, the act of duplicating licence plates and in some cases whole car is an emerging threat which presents a challenge that has not been catered for in existing solutions. Although the Automatic Licence plate Recognition (ALPR) system has been at a mature stage for a while, this unique problem is not addressed, and we have not come across any commercial solution either. This paper is first to address two key areas in enhancement of ALPR system. First the evaluation metric was developed to address unfairness of accuracy of string level match enhancing accuracy from 43% to 96%. Secondly, we introduced a novel framework using 'Usual Route Identification' algorithm to analyse a Vehicle's usual journey which helps to flag if unusual routes are taken or located outside off a set radius indicating a potential case of vehicle cloning. This study will show how appropriate metric can enhance the capability of ALPR systems, proposes a functionality that aids law enforcement authorities, and adds to academic knowledgebase.
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A novel approach to enhance ALPR system performance458.74 kBDownloadView
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