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Reseach Article

Article:IRIS Recognition using Texture Features Extracted from Haarlet Pyramid

by Dr.H.B.Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 11 - Number 12
Year of Publication: 2010
Authors: Dr.H.B.Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal
10.5120/1638-2202

Dr.H.B.Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal . Article:IRIS Recognition using Texture Features Extracted from Haarlet Pyramid. International Journal of Computer Applications. 11, 12 ( December 2010), 1-5. DOI=10.5120/1638-2202

@article{ 10.5120/1638-2202,
author = { Dr.H.B.Kekre, Sudeep D. Thepade, Juhi Jain, Naman Agrawal },
title = { Article:IRIS Recognition using Texture Features Extracted from Haarlet Pyramid },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 11 },
number = { 12 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume11/number12/1638-2202/ },
doi = { 10.5120/1638-2202 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:00:21.530517+05:30
%A Dr.H.B.Kekre
%A Sudeep D. Thepade
%A Juhi Jain
%A Naman Agrawal
%T Article:IRIS Recognition using Texture Features Extracted from Haarlet Pyramid
%J International Journal of Computer Applications
%@ 0975-8887
%V 11
%N 12
%P 1-5
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Iris recognition has been a fast growing, challenging and interesting area in real-time applications. A large number of iris recognition algorithms have been developed for decades. The paper presents novel Haarlet Pyramid based iris recognition technique. Here iris recognition is done using the image feature set extracted from Haar Wavelets at various levels of decomposition. Analysis was performed of the proposed method, consisting of the False Acceptance Rate and the Genuine Acceptance Rate. The proposed technique is tested on an iris image database having 384 images. The results show that Haarlets level-5 outperforms other Haarlets, because the higher level Haarlets are giving very fine texture features while the lower level Haarlets are representing very coarse texture features which are less useful for discrimination of images in iris recognition.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Iris recognition Haarlet Pyramid Haarlet Levels False Acceptance Rate Genuine Acceptance Rate