OCR-based neural network for ANPR

Xiaojun Zhai, Faycal Bensaali, Reza Sotudeh

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

24 Citations (Scopus)


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
Original languageEnglish
Title of host publicationProcs 2012 IEEE Int Conf on Imaging Systems and Techniques IST)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Print)978-1-4577-1776-5
Publication statusPublished - 2012
EventImaging Systems and Techniques (IST), 2012 IEEE International Conference on - Manchester, United Kingdom
Duration: 16 Jul 201217 Jul 2012


ConferenceImaging Systems and Techniques (IST), 2012 IEEE International Conference on
Country/TerritoryUnited Kingdom


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