Accuracy Enhancement for License Plate Recognition

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Show simple item record Zheng, Lihong en_US Samali, Bijan en_US Yang, Laurence en_US He, Sean en_US
dc.contributor.editor Lihong Zheng; Xiangjian He; Samali B; Yang, LT en_US 2012-02-02T11:08:09Z 2012-02-02T11:08:09Z 2010 en_US
dc.identifier 2009007757 en_US
dc.identifier.citation Zheng Lihong et al. 2010, 'Accuracy Enhancement for License Plate Recognition', , IEEE Computer Society, Bradford, West Yorkshire UK, , pp. 511-516. en_US
dc.identifier.issn 978-0-7695-4108-2 en_US
dc.identifier.other E1 en_US
dc.description.abstract Automatic License Plate Recognition is useful for real time traffice management and surveillance. License plate recognition usually contains two steps, namely license plate detection/localization and character recognition. Recognizing character in a license plate is very difficult task due to poor illumination conditions and rapid motion of vehicles. When using an OCR for character recognition, it is crucial to correctly remove the license plate boundaries after the step for license plate detection. No matter which OCRs are used, the recognition accuracy will be significantly reduced if the boundaries are not properly removed. This paper presents an efficient algorithm for non character area removal. The algorithm is based on the license plates detected using an AdaBoost algorithm. Then it follows the steps of character height estimation, character width estimation, segmentation and block identification. The algorithm is efficient and can be applied in real time applications. The experiments are performed using OCR software for character recognition. It is shown that much higher recognition accuracy is obtained by gradually removing the license plate boundaries en_US
dc.language English en_US
dc.publisher IEEE Computer Society en_US
dc.relation.isbasedon en_US
dc.title Accuracy Enhancement for License Plate Recognition en_US
dc.parent Proceedings - 10th IEEE International Conference on Computer and Information Technology (CIT 2010) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Bradford, West Yorkshire UK en_US
dc.identifier.startpage 511 en_US
dc.identifier.endpage 516 en_US FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 080600 en_US
dc.personcode 10144691 en_US
dc.personcode 990421 en_US
dc.personcode 870186 en_US
dc.personcode 0000063964 en_US
dc.percentage 100 en_US Information Systems en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom IEEE International Conference on Computer and Information Technology en_US 20100629 en_US
dc.location.activity Bradford, West Yorkshire UK en_US
dc.description.keywords LPR, image segmentation, blob extraction, CCA en_US

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