Article Abstract

	Title:	Learning-based license plate detection in vehicle image database
	Author:	Huaifeng Zhang, Wenjing Jia, Xiangjian He, Qiang Wu
	Address:	Faculty of Information Technology, University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia. ' Faculty of Information Technology, University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia. ' Faculty of Information Technology, University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia. ' Faculty of Information Technology, University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia
	Journal:	International Journal of Intelligent Information and Database Systems 2007 - Vol. 1, No.2  pp. 228 - 243
	Abstract:	This paper proposes a learning-based algorithm to detect license plates of vehicles from vehicle image database. There are three main contributions in this paper. The first contribution is to define a novel vertical edge map, which makes the image processing more effectively. The second contribution is to propose a learning-based cascade classifier composing of two kinds of sub-classifiers, which makes the system very robust. The third contribution is to experimentally estimate the parameter of scaling factor and chose an optimal one for the algorithm to seek a good balance between detection rate and processing time.
	Keywords:	content-based image retrieval; CBIR; vehicle image databases; license plate detection; AdaBoost; cascade classifiers; vehicle license plates; learning algorithms; image processing.
	DOI:	10.1504/IJIIDS.2007.014952
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