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A memetic-based fuzzy support vector machine model and its application to license plate recognition

Samma, Hussein, Lim, Chee Peng, Saleh, Junita Mohamad and Suandi, Shahrel Azmin 2016, A memetic-based fuzzy support vector machine model and its application to license plate recognition, Memetic computing, vol. 8, no. 3, pp. 235-251, doi: 10.1007/s12293-016-0187-0.

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Title A memetic-based fuzzy support vector machine model and its application to license plate recognition
Author(s) Samma, Hussein
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Saleh, Junita Mohamad
Suandi, Shahrel Azmin
Journal name Memetic computing
Volume number 8
Issue number 3
Start page 235
End page 251
Total pages 17
Publisher Springer
Place of publication New York, N.Y.
Publication date 2016-09
ISSN 1865-9284
1865-9292
Summary In this paper, a novel fuzzy support vector machine (FSVM) coupled with a memetic particle swarm optimization (MPSO) algorithm is introduced. Its application to a license plate recognition problem is studied comprehensively. The proposed recognition model comprises linear FSVM classifiers which are used to locate a two-character window of the license plate. A new MPSO algorithm which consists of three layers i.e. a global optimization layer, a component optimization layer, and a local optimization layer is constructed. During the construction process, MPSO performs FSVM parameters tuning, feature selection, and training instance selection simultaneously. A total of 220 real Malaysian car plate images are used for evaluation. The experimental results indicate the effectiveness of the proposed model for undertaking license plate recognition problems.
Language eng
DOI 10.1007/s12293-016-0187-0
Field of Research 099999 Engineering not elsewhere classified
0803 Computer Software
1004 Medical Biotechnology
Socio Economic Objective 970110 Expanding Knowledge in Technology
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30087684

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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