Research Article
Improving the accuracy of Iris Recognition System using Neural Network and Particle swarm Optimization
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 79 - Issue 3 |
| Published: October 2013 |
| Authors: Nuzhat Faiz Shaikh, D. D. Doye |
10.5120/13718-1497
|
Nuzhat Faiz Shaikh, D. D. Doye . Improving the accuracy of Iris Recognition System using Neural Network and Particle swarm Optimization. International Journal of Computer Applications. 79, 3 (October 2013), 1-6. DOI=10.5120/13718-1497
@article{ 10.5120/13718-1497,
author = { Nuzhat Faiz Shaikh,D. D. Doye },
title = { Improving the accuracy of Iris Recognition System using Neural Network and Particle swarm Optimization },
journal = { International Journal of Computer Applications },
year = { 2013 },
volume = { 79 },
number = { 3 },
pages = { 1-6 },
doi = { 10.5120/13718-1497 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2013
%A Nuzhat Faiz Shaikh
%A D. D. Doye
%T Improving the accuracy of Iris Recognition System using Neural Network and Particle swarm Optimization%T
%J International Journal of Computer Applications
%V 79
%N 3
%P 1-6
%R 10.5120/13718-1497
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Iris recognition is the process of recognizing a person by analyzing the apparent pattern of his or her iris. Many techniques have been developed for iris recognition so far. Here, we propose a new iris recognition system with the help of local histogram and then optimized with FFBNN-PSO. In the proposed system, first the input eye images are preprocessed using adaptive median filter to remove the salt and pepper noise. Then, the features, which are extracted from the preprocessed image are given to FFBNN for training. In order to get accurate results, the FFBNN parameters are optimized using PSO.
References
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