Comparison of Feature Extractors in License Plate Recognition

Siti Norul Huda Sheikh Abdullah, Marzuki Khalid, Rubiyah Yusof, Khairuddin Omar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)

Abstract

Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates using blob labeling and clustering for segmentation, seven popular and one proposed edge detectors for feature extraction and neural networks for classification.There were eight experiments conducted using eight different edge dectectors: Kirsch, Sobel, Laplacian, Wallis, Prewitt, Frei Chen and a proposed edge detector. The result had shown kirsch edge detectors is the best technique for feature exractor while the proposed achieved better results compared to Prewitt, Frei Chen and Wallis.

Original languageEnglish
Title of host publicationProceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages502-506
Number of pages5
ISBN (Print)0769528457, 9780769528458
DOIs
Publication statusPublished - 2007
Event1st Asia International Conference on Modelling and Simulation - Asia Modelling Symposium 2007, AMS 2007 - Phuket, Thailand
Duration: 27 Mar 200730 Mar 2007

Other

Other1st Asia International Conference on Modelling and Simulation - Asia Modelling Symposium 2007, AMS 2007
CountryThailand
CityPhuket
Period27/3/0730/3/07

Fingerprint

Extractor
Detectors
Detector
Labeling
Feature extraction
Neural networks
Feature Extraction
Segmentation
Clustering
Neural Networks
Experiments
Requirements
Experiment

ASJC Scopus subject areas

  • Modelling and Simulation

Cite this

Sheikh Abdullah, S. N. H., Khalid, M., Yusof, R., & Omar, K. (2007). Comparison of Feature Extractors in License Plate Recognition. In Proceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007 (pp. 502-506). [4148711] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AMS.2007.25

Comparison of Feature Extractors in License Plate Recognition. / Sheikh Abdullah, Siti Norul Huda; Khalid, Marzuki; Yusof, Rubiyah; Omar, Khairuddin.

Proceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007. Institute of Electrical and Electronics Engineers Inc., 2007. p. 502-506 4148711.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Sheikh Abdullah, SNH, Khalid, M, Yusof, R & Omar, K 2007, Comparison of Feature Extractors in License Plate Recognition. in Proceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007., 4148711, Institute of Electrical and Electronics Engineers Inc., pp. 502-506, 1st Asia International Conference on Modelling and Simulation - Asia Modelling Symposium 2007, AMS 2007, Phuket, Thailand, 27/3/07. https://doi.org/10.1109/AMS.2007.25
Sheikh Abdullah SNH, Khalid M, Yusof R, Omar K. Comparison of Feature Extractors in License Plate Recognition. In Proceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007. Institute of Electrical and Electronics Engineers Inc. 2007. p. 502-506. 4148711 https://doi.org/10.1109/AMS.2007.25
Sheikh Abdullah, Siti Norul Huda ; Khalid, Marzuki ; Yusof, Rubiyah ; Omar, Khairuddin. / Comparison of Feature Extractors in License Plate Recognition. Proceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007. Institute of Electrical and Electronics Engineers Inc., 2007. pp. 502-506
@inproceedings{5dfe31a797ce4945ad51efda666c4b27,
title = "Comparison of Feature Extractors in License Plate Recognition",
abstract = "Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates using blob labeling and clustering for segmentation, seven popular and one proposed edge detectors for feature extraction and neural networks for classification.There were eight experiments conducted using eight different edge dectectors: Kirsch, Sobel, Laplacian, Wallis, Prewitt, Frei Chen and a proposed edge detector. The result had shown kirsch edge detectors is the best technique for feature exractor while the proposed achieved better results compared to Prewitt, Frei Chen and Wallis.",
author = "{Sheikh Abdullah}, {Siti Norul Huda} and Marzuki Khalid and Rubiyah Yusof and Khairuddin Omar",
year = "2007",
doi = "10.1109/AMS.2007.25",
language = "English",
isbn = "0769528457",
pages = "502--506",
booktitle = "Proceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Comparison of Feature Extractors in License Plate Recognition

AU - Sheikh Abdullah, Siti Norul Huda

AU - Khalid, Marzuki

AU - Yusof, Rubiyah

AU - Omar, Khairuddin

PY - 2007

Y1 - 2007

N2 - Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates using blob labeling and clustering for segmentation, seven popular and one proposed edge detectors for feature extraction and neural networks for classification.There were eight experiments conducted using eight different edge dectectors: Kirsch, Sobel, Laplacian, Wallis, Prewitt, Frei Chen and a proposed edge detector. The result had shown kirsch edge detectors is the best technique for feature exractor while the proposed achieved better results compared to Prewitt, Frei Chen and Wallis.

AB - Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates using blob labeling and clustering for segmentation, seven popular and one proposed edge detectors for feature extraction and neural networks for classification.There were eight experiments conducted using eight different edge dectectors: Kirsch, Sobel, Laplacian, Wallis, Prewitt, Frei Chen and a proposed edge detector. The result had shown kirsch edge detectors is the best technique for feature exractor while the proposed achieved better results compared to Prewitt, Frei Chen and Wallis.

UR - http://www.scopus.com/inward/record.url?scp=84963988087&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84963988087&partnerID=8YFLogxK

U2 - 10.1109/AMS.2007.25

DO - 10.1109/AMS.2007.25

M3 - Conference contribution

AN - SCOPUS:84963988087

SN - 0769528457

SN - 9780769528458

SP - 502

EP - 506

BT - Proceedings - 1st Asia International Conference on Modelling and Simulation: Asia Modelling Symposium 2007, AMS 2007

PB - Institute of Electrical and Electronics Engineers Inc.

ER -