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Recognition of Vehicle Registration Plate with “Neural Network” using “Segmentation”

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 95 - Number 25
Year of Publication: 2014
Authors:
Mukesh Kumar Sharma
Hemant Kumar Garg
10.5120/16750-6995

Mukesh Kumar Sharma and Hemant Kumar Garg. Article: Recognition of Vehicle Registration Plate with Neural Network using Segmentation. International Journal of Computer Applications 95(25):18-24, June 2014. Full text available. BibTeX

@article{key:article,
	author = {Mukesh Kumar Sharma and Hemant Kumar Garg},
	title = {Article: Recognition of Vehicle Registration Plate with Neural Network using Segmentation},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {95},
	number = {25},
	pages = {18-24},
	month = {June},
	note = {Full text available}
}

Abstract

Localization algorithms have been working with very large number of various domains. But the research area is under discussion with the domain of VRPR i. e. vehicle registration plate recognition system. The authenticity of license plate recognition system deals with the performance of the localization algorithm. This computational process takes a lot of time to confine the vehicle license plate. In this research area is under discussion to the diverse types of localization algorithm and one distinct of them should be worked for a particular relevance. Different states have their distinct types of plates for example. Some utilize single line horizontal plate while others utilize multi-line non horizontal and differently located number plate. Some of the broadly utilized localizations algorithm which is worked in the neural network recognizer is Double threshold scheme.

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