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A Survey and Comparison of License Plate Recognition using different Classifiers

by Megha S. Utge
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 132 - Number 8
Year of Publication: 2015
Authors: Megha S. Utge
10.5120/ijca2015907494

Megha S. Utge . A Survey and Comparison of License Plate Recognition using different Classifiers. International Journal of Computer Applications. 132, 8 ( December 2015), 5-7. DOI=10.5120/ijca2015907494

@article{ 10.5120/ijca2015907494,
author = { Megha S. Utge },
title = { A Survey and Comparison of License Plate Recognition using different Classifiers },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 132 },
number = { 8 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 5-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume132/number8/23612-2015907494/ },
doi = { 10.5120/ijca2015907494 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:28:46.201138+05:30
%A Megha S. Utge
%T A Survey and Comparison of License Plate Recognition using different Classifiers
%J International Journal of Computer Applications
%@ 0975-8887
%V 132
%N 8
%P 5-7
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

LPR is a well know image processing technology. Now a days vehicles play a very big role in transportation. Also the use of vehicles has been increasing because of population growth and human needs in recent years. Therefore, control of vehicles is becoming a big problem and much more difficult to solve . license plate are available in various colors and style The presence of noise, blurring in the image, uneven illumination, dim light and foggy conditions make the task even more difficult. In the proposed system ANN classifier will be used. Firstly preprocessing techniques will be done on input image, such as grayscale, blurring ,thresholding and frequency calculation then segmentation. Finally use Artificial neural network classifier as a recognition method. In this paper a survey has done compared and analyzed with different recognition method.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Plate localization plate detection Extraction segmentation recognition

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