Sift Algorithm for Iris Feature Extraction

Kinjal M. Gandhi

Sift Algorithm for Iris Feature Extraction

Kinjal M. Gandhi * §

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Sift Algorithm for Iris Feature Extraction

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Abstract

Iris recognition is proving to be one of the most reliable biometric traits for personal identification. In fact, iris patterns have stable, invariant and distinctive features for personal identification. Reliable authorization and authentication are becoming necessary for many everyday applications. Iris recognition has been paid more attention due to its high reliability in personal identification. But iris feature extraction is easily affected by some practical factors, such as inaccurate localization, occlusion, and nonlinear elastic deformation. The objective of the study and proposed work is to adapt the increasing usage of biometric systems which can reduce the iris preprocessing and describe iris local properties effectively and have encouraging iris recognition performance. This work presents an efficient algorithm of iris feature extraction based on modified scale invariant feature transform algorithm (SIFT) .

References

10 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

Kinjal M. Gandhi. 2014. "Sift Algorithm for Iris Feature Extraction". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 14 (GJCST Volume 14 Issue F3).

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GJCST Volume 14 Issue F3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

biometric systems feature extraction Iris Recognition occlusion sift

Classification

I.2.10

Submission ReceivedDecember 13, 2013
Peer Review Double Blind
Handling Editor
Accepted December 31, 2013
Published January 15, 2014

Version of record

v1.2

Issue date

August 21, 2014

Language

English

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Article Matrices

Total Score: 142

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Kinjal M. Gandhi , Prof. R.H. Kulkarni (PhD/Dr. count: 0)

View Count (all-time): 470

Total Views (Real + Logic): 2616

Total Downloads (simulated): 215

Publish Date: 2014 01, Wed

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Total Views: 2.6K

Total Downloads: 215

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