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Vehicle Number Plate Recognition System: A Literature Review and Implementation using Template Matching

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Aniruddh Puranic, Deepak K. T., Umadevi V.
10.5120/ijca2016907652

Aniruddh Puranic, Deepak K T. and Umadevi V.. Article: Vehicle Number Plate Recognition System: A Literature Review and Implementation using Template Matching. International Journal of Computer Applications 134(1):12-16, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Aniruddh Puranic and Deepak K. T. and Umadevi V.},
	title = {Article: Vehicle Number Plate Recognition System: A Literature Review and Implementation using Template Matching},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {134},
	number = {1},
	pages = {12-16},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

The growing affluence of urban India has made the ownership of vehicles a necessity. This has resulted in an unexpected civic problem - that of traffic control and vehicle identification. Parking areas have become overstressed due to the growing numbers of vehicles on the roads today. The Automatic Number Plate Recognition System (ANPR) plays an important role in addressing these issues as its application ranges from parking admission to monitoring urban traffic and to tracking automobile thefts. There are numerous ANPR systems available today which are based on different methodologies. In this paper, we attempt to review the various techniques and their usage. The ANPR system has been implemented using template Matching and its accuracy was found to be 80.8% for Indian number plates.

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Keywords

Educational Institutions, Automatic Number Plate Recognition, Artificial Neural Networks, Template Matching.