License plate localisation based on morphological operations

X. Zhai; F. Bensaali; S. Ramalingam

doi:10.1109/ICARCV.2010.5707933

License plate localisation based on morphological operations

X. Zhai, F. Bensaali, S. Ramalingam

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

20 Citations (Scopus)

74 Downloads (Pure)

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.

Original language	English
Title of host publication	Procs of the 11th Int Conf on Control Automation Robotics and Vision (ICARCV)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1128-1132
ISBN (Print)	978-1-4244-7814-9
DOIs	https://doi.org/10.1109/ICARCV.2010.5707933
Publication status	Published - 2010

Keywords

number plate localisation
ANPR
morphological operation

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10.1109/ICARCV.2010.5707933

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Cite this

@inproceedings{400c49ddbf414c3cb7b51d0d51ddc7a2,

title = "License plate localisation based on morphological operations",

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.",

keywords = "number plate localisation, ANPR, morphological operation",

author = "X. Zhai and F. Bensaali and S. Ramalingam",

note = "“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.”",

year = "2010",

doi = "10.1109/ICARCV.2010.5707933",

language = "English",

isbn = "978-1-4244-7814-9",

pages = "1128--1132",

booktitle = "Procs of the 11th Int Conf on Control Automation Robotics and Vision (ICARCV)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

}

TY - GEN

T1 - License plate localisation based on morphological operations

AU - Zhai, X.

AU - Bensaali, F.

AU - Ramalingam, S.

N1 - “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.”

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - number plate localisation

KW - ANPR

KW - morphological operation

UR - http://www.scopus.com/inward/record.url?scp=79952387925&partnerID=8YFLogxK

U2 - 10.1109/ICARCV.2010.5707933

DO - 10.1109/ICARCV.2010.5707933

M3 - Conference contribution

SN - 978-1-4244-7814-9

SP - 1128

EP - 1132

BT - Procs of the 11th Int Conf on Control Automation Robotics and Vision (ICARCV)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

License plate localisation based on morphological operations

Abstract

Keywords

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