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Development of a license plate recognition system for a non-ideal environment

A new algorithm for license plate character recognition system is proposed on the basis of Signature analysis properties and features extraction. Signature analysis has been used to locate license plate region and its properties can be further utilised in supporting and affirming the license plate...

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Main Authors: Lorita Angeline, Hui, Keng Lau, Bablu Kumar Ghosh, Hui, Hwang Goh, Tze, Kenneth Kin Teo
Format: Article
Language:English
Published: United Kingdom Simulation Society 2012
Subjects:
TJ Mechanical engineering and machinery
Online Access:https://eprints.ums.edu.my/id/eprint/19360/1/Development%20of%20a%20license%20plate%20recognition%20system%20for%20a%20non.pdf
https://eprints.ums.edu.my/id/eprint/19360/
http://doi.org/10.5013/IJSSST.a.13.3C.05
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spelling my.ums.eprints.193602018-03-22T03:39:53Z https://eprints.ums.edu.my/id/eprint/19360/ Development of a license plate recognition system for a non-ideal environment Lorita Angeline Hui, Keng Lau Bablu Kumar Ghosh Hui, Hwang Goh Tze, Kenneth Kin Teo TJ Mechanical engineering and machinery A new algorithm for license plate character recognition system is proposed on the basis of Signature analysis properties and features extraction. Signature analysis has been used to locate license plate region and its properties can be further utilised in supporting and affirming the license plate character recognition. This paper presents the implementation of Signature Analysis combined with Features Extraction to form feature vector for each character with a length of 56. Implementation of these two methods is used in tracking of vehicle’s automatic license plate recognition system (ALPR). The developed ALPR comprises of three phase. The recognition stage utilised the vector to be trained in a simple multi-layer feed-forward back-propagation Neural Network with 56 inputs and 34 neurons in its output layer. The network is trained with both ideal and noisy characters. The results obtained show that the proposed system is capable to recognise both ideal and non-ideal license plate characters. The system also capable to tackle the common character misclassification problems due to similarity in characters. United Kingdom Simulation Society 2012-06 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/19360/1/Development%20of%20a%20license%20plate%20recognition%20system%20for%20a%20non.pdf Lorita Angeline and Hui, Keng Lau and Bablu Kumar Ghosh and Hui, Hwang Goh and Tze, Kenneth Kin Teo (2012) Development of a license plate recognition system for a non-ideal environment. International Journal of Simulation Systems, Science & Technology, IJSSST, 13 (3C). pp. 26-33. ISSN 1473-804x http://doi.org/10.5013/IJSSST.a.13.3C.05
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Lorita Angeline
Hui, Keng Lau
Bablu Kumar Ghosh
Hui, Hwang Goh
Tze, Kenneth Kin Teo
Development of a license plate recognition system for a non-ideal environment
description A new algorithm for license plate character recognition system is proposed on the basis of Signature analysis properties and features extraction. Signature analysis has been used to locate license plate region and its properties can be further utilised in supporting and affirming the license plate character recognition. This paper presents the implementation of Signature Analysis combined with Features Extraction to form feature vector for each character with a length of 56. Implementation of these two methods is used in tracking of vehicle’s automatic license plate recognition system (ALPR). The developed ALPR comprises of three phase. The recognition stage utilised the vector to be trained in a simple multi-layer feed-forward back-propagation Neural Network with 56 inputs and 34 neurons in its output layer. The network is trained with both ideal and noisy characters. The results obtained show that the proposed system is capable to recognise both ideal and non-ideal license plate characters. The system also capable to tackle the common character misclassification problems due to similarity in characters.
format Article
author Lorita Angeline
Hui, Keng Lau
Bablu Kumar Ghosh
Hui, Hwang Goh
Tze, Kenneth Kin Teo
author_facet Lorita Angeline
Hui, Keng Lau
Bablu Kumar Ghosh
Hui, Hwang Goh
Tze, Kenneth Kin Teo
author_sort Lorita Angeline
title Development of a license plate recognition system for a non-ideal environment
title_short Development of a license plate recognition system for a non-ideal environment
title_full Development of a license plate recognition system for a non-ideal environment
title_fullStr Development of a license plate recognition system for a non-ideal environment
title_full_unstemmed Development of a license plate recognition system for a non-ideal environment
title_sort development of a license plate recognition system for a non-ideal environment
publisher United Kingdom Simulation Society
publishDate 2012
url https://eprints.ums.edu.my/id/eprint/19360/1/Development%20of%20a%20license%20plate%20recognition%20system%20for%20a%20non.pdf
https://eprints.ums.edu.my/id/eprint/19360/
http://doi.org/10.5013/IJSSST.a.13.3C.05
_version_ 1760229570437447680
score 13.223943

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