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    Abstract
2017 (Vol. 14, Issue: 12)
Research Article

Iris Recognitions Identification and Verification using Hybrid Techniques

Ban Jaber Adnan Al-Juburi, Professor Hind Rustum Mohammed and Assad Noori Hashim Al-Shareefi
Faculty of Computer Science and Mathematics, University of Kufa, Iraq
 

DOI: 10.19026/rjaset.14.5150
Submitted Accepted Published
August 6, 2017 September 9, 2017 December 15, 2017

  How to Cite this Article:

Ban Jaber Adnan Al-Juburi, Professor Hind Rustum Mohammed and Assad Noori Hashim Al-Shareefi, 2017. Iris Recognitions Identification and Verification using Hybrid Techniques.  Research Journal of Applied Sciences, Engineering and Technology, 14(12): 473-482.

DOI: 10.19026/rjaset.14.5150

URL: http://www.maxwellsci.com/jp/mspabstract.php?jid=RJASET&doi=rjaset.14.5150

Abstract:


The aim of this study is proposed a new IRS using hybrid methods. These methods used to extract features of tested eye images. Gabor wavelet and Zernike moment used to extract features of iris. Canny edge detection and Hough transform used to determine the iris. The proposed system tested on CASIA-v4.0 interval database. The results show that the proposed method having good accuracy about 97%. PSNR applied on the training and testing iris image to measure the simmilarity between them. PSNR is support the proposed system where, highest value of PSNR for the tesed image dells with the image is belong to the same person in training database.

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    Competing interests

The authors have no competing interests.
    Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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© The Author(s) 2017

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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