dc.contributor.author | Zhai, X. | |
dc.contributor.author | Bensaali, F. | |
dc.contributor.author | Ramalingam, S. | |
dc.date.accessioned | 2012-12-11T10:59:44Z | |
dc.date.available | 2012-12-11T10:59:44Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Zhai , X , Bensaali , F & Ramalingam , S 2010 , License plate localisation based on morphological operations . in Procs of the 11th Int Conf on Control Automation Robotics and Vision (ICARCV) . Institute of Electrical and Electronics Engineers (IEEE) , pp. 1128-1132 . https://doi.org/10.1109/ICARCV.2010.5707933 | |
dc.identifier.isbn | 978-1-4244-7814-9 | |
dc.identifier.other | dspace: 2299/5759 | |
dc.identifier.uri | http://hdl.handle.net/2299/9355 | |
dc.description | “This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” | |
dc.description.abstract | Automatic Number Plate Recognition (ANPR) systems allow users to track, identify and monitor moving vehicles by automatically extracting their number plates. This paper presents an improved method to locate car plates in an ANPR system. The proposed method is based on morphological open and close operations where different Structuring Elements (SE) are used to maximally eliminate non-plate region and enhance plate region. This method has been tested using a database of UK number plates and results achieved have shown significant improvements in terms of the detection rate compare to other existing plate localisation systems. | en |
dc.format.extent | 420778 | |
dc.language.iso | eng | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | |
dc.relation.ispartof | Procs of the 11th Int Conf on Control Automation Robotics and Vision (ICARCV) | |
dc.subject | number plate localisation | |
dc.subject | ANPR | |
dc.subject | morphological operation | |
dc.title | License plate localisation based on morphological operations | en |
dc.contributor.institution | School of Engineering and Technology | |
dc.contributor.institution | Science & Technology Research Institute | |
dc.identifier.url | http://www.scopus.com/inward/record.url?scp=79952387925&partnerID=8YFLogxK | |
rioxxterms.versionofrecord | 10.1109/ICARCV.2010.5707933 | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |