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Reseach Article

Recognition of Vehicle Registration Plate with ìNeural Networkî using ìSegmentationî

by Mukesh Kumar Sharma, Hemant Kumar Garg
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 25
Year of Publication: 2014
Authors: Mukesh Kumar Sharma, Hemant Kumar Garg
10.5120/16750-6995

Mukesh Kumar Sharma, Hemant Kumar Garg . Recognition of Vehicle Registration Plate with ìNeural Networkî using ìSegmentationî. International Journal of Computer Applications. 95, 25 ( June 2014), 18-24. DOI=10.5120/16750-6995

@article{ 10.5120/16750-6995,
author = { Mukesh Kumar Sharma, Hemant Kumar Garg },
title = { Recognition of Vehicle Registration Plate with ìNeural Networkî using ìSegmentationî },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 25 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 18-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number25/16750-6995/ },
doi = { 10.5120/16750-6995 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:20:23.562087+05:30
%A Mukesh Kumar Sharma
%A Hemant Kumar Garg
%T Recognition of Vehicle Registration Plate with ìNeural Networkî using ìSegmentationî
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 25
%P 18-24
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
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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Index Terms

Computer Science
Information Sciences

Keywords

Segmentation Neural Network Double Thresholds Algorithm VRPR