Feature Selection Method for Iris Recognition Authentication System

Dr. Pooja garg; Anshu Parashar

Feature Selection Method for Iris Recognition Authentication System

Dr. Pooja garg * §

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Anshu Parashar

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§ H.C.T.M Kaithal

Feature Selection Method for Iris Recognition Authentication System

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Abstract

Iris-based biometric authentication is gaining importance in recent times. Iris biometric processing however, is a complex process and computationally very expensive. In the overall processing of iris biometric in an iris-based biometric authentication system, feature selection is an important task. In feature selection, we ex-tract iris features, which are ultimately used in matching. Since there is a large number of iris features and computational time increases as the number of features increases, it is therefore a challenge to develop an iris processing system with as few as possible number of features and at the same time without compromising the correctness. In this paper, we address this issue and present an approach to feature Selection Method.

References

13 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Pooja garg, Anshu Parashar. 2012. "Feature Selection Method for Iris Recognition Authentication System". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 12 (GJCST Volume 12 Issue F10).

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GJCST Volume 12 Issue F10

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Biometric feature extraction feature Selection method Iris Recognition

Classification

GJCST-F Classification FOR Code: I.2.3

Submission ReceivedFebruary 5, 2012
Peer Review Double Blind
Handling Editor
Accepted March 3, 2012
Published March 15, 2012

Version of record

v1.2

Issue date

June 20, 2012

Language

English

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Article Matrices

Total Score: 147

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Dr. Pooja garg, Anshu Parashar (PhD/Dr. count: 1)

View Count (all-time): 365

Total Views (Real + Logic): 4446

Total Downloads (simulated): 189

Publish Date: 2012 03, Thu

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Total Views: 4.4K

Total Downloads: 189

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