A system for licence plate recognition using a hierarchically combined classifier

DSpace/Manakin Repository

Search OPUS


Advanced Search

Browse

My Account

Show simple item record

dc.contributor.author Zheng, L
dc.contributor.author He, X
dc.contributor.author Wu, Q
dc.contributor.author Samali, B
dc.date.accessioned 2012-10-12T03:33:45Z
dc.date.issued 2011-03
dc.identifier.citation International Journal of Intelligent Systems Technologies and Applications, 2011, 10 (2), pp. 189 - 202
dc.identifier.issn 1740-8865
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/18264
dc.description.abstract In a real time, automatic licence plate recognition system, licence detection, character segmentation and character recognition are three important components. All these three components generally require high accuracy and fast recognition speed to process. In this paper, general processing steps for license plate recognition (LPR) are addressed. After three types of combined classifiers are introduced and compared, a hierarchically combined classifier is designed based on an inductive learning-based method and an support vector machine (SVM)-based classification. This approach employs the inductive learning-based method to roughly divide all classes into smaller groups. Then, the SVM approach is used for character classification in individual groups. Having obtained a collection of samples of characters in advance from licence plates after licence detection and character segmentation steps, some known samples are available for training. After the training process, the inductive learning rules are extracted for rough classification and the parameters used for SVM-based classification are obtained. Then, a classification tree is constructed for next fast training and testing processes based on SVMs. The experimental results show that the hierarchically combined classifier is better than either the inductive learning-based classification or the SVM-based classification with a lower error rate and a faster processing speed. © 2011 Inderscience Enterprises Ltd.
dc.language eng
dc.relation.isbasedon 10.1504/IJISTA.2011.039019
dc.title A system for licence plate recognition using a hierarchically combined classifier
dc.type Journal Article
dc.parent International Journal of Intelligent Systems Technologies and Applications
dc.journal.volume 2
dc.journal.volume 10
dc.journal.number en_US
dc.publocation UK en_US
dc.identifier.startpage 189 en_US
dc.identifier.endpage 202 en_US
dc.cauo.name FEIT.School of Computing and Communications en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 990421
dc.personcode 000748
dc.personcode 870186
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords licence plate recognition; class tree; hierarchically combined classifier. en_US
dc.description.keywords clustering
dc.description.keywords localization
dc.description.keywords Routing
dc.description.keywords socionomic
dc.description.keywords Class tree
dc.description.keywords Hierarchically combined classifier
dc.description.keywords Licence plate recognition
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computing and Communications
pubs.organisational-group /University of Technology Sydney/Strength - Built Infrastructure
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)
utslib.collection.history School of Computing and Communications (ID: 335)


Files in this item

This item appears in the following Collection(s)

Show simple item record