S. Ramalingam, W. E. Martin, Mike Rhead, Robert Gurney
{"title":"Electronic Number Plate Generation for Performance Evaluation","authors":"S. Ramalingam, W. E. Martin, Mike Rhead, Robert Gurney","doi":"10.1109/ICCST52959.2022.9896515","DOIUrl":null,"url":null,"abstract":"The authors have been involved in real world analysis of Automatic Number Plate Recognition (ANPR) data and systems particularly for law enforcement applications. As a result of such work with Law Enforcement Agencies, contributions have been made to the revision of the British Standards for ANPR. This led to the research team developing performance evaluation measures from an end-to-end system perspective. One such measure was the generation of synthetic image datasets suitable for ANPR performance evaluation. The prime requirement for any ANPR system is data accuracy. This paper reports the initial work and progress made using defined synthetic images to test and assess ANPR engines using a structured methodology.","PeriodicalId":364791,"journal":{"name":"2022 IEEE International Carnahan Conference on Security Technology (ICCST)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Carnahan Conference on Security Technology (ICCST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCST52959.2022.9896515","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The authors have been involved in real world analysis of Automatic Number Plate Recognition (ANPR) data and systems particularly for law enforcement applications. As a result of such work with Law Enforcement Agencies, contributions have been made to the revision of the British Standards for ANPR. This led to the research team developing performance evaluation measures from an end-to-end system perspective. One such measure was the generation of synthetic image datasets suitable for ANPR performance evaluation. The prime requirement for any ANPR system is data accuracy. This paper reports the initial work and progress made using defined synthetic images to test and assess ANPR engines using a structured methodology.