University of Hertfordshire

OCR-based neural network for ANPR

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Xiaojun Zhai
  • Faycal Bensaali
  • Reza Sotudeh
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Original languageEnglish
Title of host publicationProcs 2012 IEEE Int Conf on Imaging Systems and Techniques IST)
PublisherIEEE
Pages393-397
ISBN (Print)978-1-4577-1776-5
DOIs
Publication statusPublished - 2012
EventImaging Systems and Techniques (IST), 2012 IEEE International Conference on - Manchester, United Kingdom
Duration: 16 Jul 201217 Jul 2012

Conference

ConferenceImaging Systems and Techniques (IST), 2012 IEEE International Conference on
CountryUnited Kingdom
CityManchester
Period16/07/1217/07/12

Abstract

Optical Character Recognition (OCR) is the last stage in an Automatic Number Plate Recognition System (ANPRs). In this stage the number plate characters on the number plate image are converted into encoded texts. In this paper, an Artificial Neural Network (ANN) based OCR algorithm for ANPR application is presented. A database of 3700 UK binary character images have been used for testing the performance of the proposed algorithm. Results achieved have shown that the proposed algorithm can meet the real-time requirement of an ANPR system and can averagely process a character image in 8.4ms with 97.3% successful recognition rate

ID: 1043381