NDLI: SIFT based iris recognition with normalization and enhancement

Content Provider	Springer Nature Link
Author	Yang, Gongping Pang, Shaohua Yin, Yilong Li, Yanan Li, Xuzhou
Copyright Year	2012
Abstract	SIFT is a novel and promising method for iris recognition. However, some shortages exist in many related methods, such as difficulty of feature extraction, feature loss, and noise point introduction. In this paper, a new method named SIFT-based iris recognition with normalization and enhancement is proposed for achieving better performance. In Comparison with other SIFT-based iris recognition algorithms, the proposed method can overcome the difficulties of extreme point extraction and exclude the noise points without feature loss. Experimental results demonstrate that the normalization and enhancement steps are crucial for SIFT-based iris recognition, and the proposed method can achieve satisfactory recognition performance.
Starting Page	401
Ending Page	407
Page Count	7
File Format	PDF
ISSN	18688071
Journal	International Journal of Machine Learning and Cybernetics
Volume Number	4
Issue Number	4
e-ISSN	1868808X
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2012-06-13
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Iris recognition SIFT Enhancement Normalization Computational Intelligence Artificial Intelligence (incl. Robotics) Control, Robotics, Mechatronics Statistical Physics, Dynamical Systems and Complexity Systems Biology Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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