Research Article
Method for Recognition of Vehicles with Kannada Number Plate
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 98 - Issue 8 |
| Published: July 2014 |
| Authors: Shivanand S. Rumma, Vishweshwarayya C. H, Bhuvaneshwari B. D |
10.5120/17203-7416
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Shivanand S. Rumma, Vishweshwarayya C. H, Bhuvaneshwari B. D . Method for Recognition of Vehicles with Kannada Number Plate. International Journal of Computer Applications. 98, 8 (July 2014), 15-17. DOI=10.5120/17203-7416
@article{ 10.5120/17203-7416,
author = { Shivanand S. Rumma,Vishweshwarayya C. H,Bhuvaneshwari B. D },
title = { Method for Recognition of Vehicles with Kannada Number Plate },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 98 },
number = { 8 },
pages = { 15-17 },
doi = { 10.5120/17203-7416 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Shivanand S. Rumma
%A Vishweshwarayya C. H
%A Bhuvaneshwari B. D
%T Method for Recognition of Vehicles with Kannada Number Plate%T
%J International Journal of Computer Applications
%V 98
%N 8
%P 15-17
%R 10.5120/17203-7416
%I Foundation of Computer Science (FCS), NY, USA
Abstract
For an intelligent transport system license plate location and vehicle license plate recognition is an important phase. The objective of this work is to design & implement a method for Number Plate Recognition (NPR) of Kannada number plates. This paper presents a method of number plate recognition, segmentation & recognition of the characters present in the Kannada number plate. The images of various vehicles have been taken manually and converted into gray-scale images. The wiener2 filter is used to remove the noise located in the number plates. The segmentation of gray-scale image generated by finding edges using sobel filter for smoothing image is used to reduce the number of connected component & then bwlabel is used to calculate the connected component & at the last single character is detected. The result shows that the proposed method have achieved accuracy of 85%.
References
- Siddartha Choubey and Sinha G. R (2011) Pixel Distribution Density based character recognition For Vehicle License Plate, (ICNCS 2011), 5, 26-30.
- Siddartha Choubey, Sinha G. R, Bhagwati Charan Patel, Abha Choubey and Kavita Thakur (2011) 2011 3rd International Conference on Machine Learning and Computing(ICMLC) 2011, Singapore, 4, 390-394.
- Ondrej Martinsky (2007) Algorithm and mathematical principles of automatic number plate recognition systems, B. Sc. -Thesis, BRNO University of Technology.
- Lee J. C. M. , Wong W. K. , Fong H. S (1999) IEEE, 2824-2828.
- Akoum A, Daya B, Chauvet P. (2009) Journal of Theoretical and Applied Information Technology, 25-32.
- Koval V. (2003) IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems Technology and Applications Ukraine, 123-127.
- Michael Seul, Practical Algorithms for Image Analysis Description, Examples and Code.
- Kroese B. (1996) An Introduction to Neural Networks, Amsterdam University of Amsterdam.
- Martin F, Garcia M and Alba J. L (2002) International Conference on Signal Processing Pattern Recognition and Applications, Greece.
- Humayun Karim Sulehria (2008) Electronics and Information Engineering, Issue, 7(6). 781-790.
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