NDLI: Iris recognition using ordinal encoding of Log-Euclidean covariance matrices

Content Provider	IEEE Xplore Digital Library
Author	Peihua Li Guolong Wu
Copyright Year	2012
Description	Author affiliation: School of Computer Science and Technology, School of Electrical Engineering, Harbin, Heilongjiang Province, China (Peihua Li; Guolong Wu)
Abstract	Iris recognition in less constrained environments is challenging due to the degraded iris images. This paper proposes a novel method fusing multiple cues for iris recognition in the non-ideal imagery. The covariance matrices are used to represent local iris texture property, which capture the correlation of spatial coordinates, intensities, 1st and 2nd-order partial derivatives. The covariance matrices are symmetric positive definite (SPD) which form a Riemannian space rather than a Euclidean one. In the Log-Euclidean framework, the space of SPD matrices is equipped with a linear space structure so that in the logarithmic domain the Euclidean operations are applicable. This enables us to compute the logarithms of covariance matrices, leading to the Log-Euclidean covariance matrices (LECM), which can be handled in common Euclidean operations. The ordinal measure is further used to represent the order relation of iris texture by comparing LECMs at different positions. We finally perform iris matching based on the Hamming distance in which the noise effects are considered. Experiments on challenging databases show the effectiveness of the proposed method.
Starting Page	2420
Ending Page	2423
File Size	193834
Page Count	4
File Format	PDF
ISBN	9781467322164
ISSN	10514651
e-ISBN	9784990644109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-11
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	ICPR Org Committee
Subject Keyword	Iris recognition Covariance matrix Symmetric matrices Databases Feature extraction Matrix decomposition Pattern recognition
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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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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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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