NDLI: Automated Selection of Optimal Frames in NIR Iris Videos

Content Provider	IEEE Xplore Digital Library
Author	Mahadeo, N.K. Paplinski, A.P. Ray, S.
Copyright Year	2013
Description	Author affiliation: Clayton Sch. of Inf. Technol., Monash Univ., Clayton, CA, USA (Mahadeo, N.K.; Paplinski, A.P.; Ray, S.)
Abstract	A relatively new trend in the iris biometric area is the use of videos as a capturing device. Frame by frame approach is richer in information and gives more flexibility as opposed to the use of traditional still images. However, the quality, shape and size of the iris may vary from one frame to another. In this paper, we propose a new technique for selecting the best frames in an iris video. Taking advantage of the temporal correspondence in iris frames, we classify iris videos into 3 categories, namely Adequate, Motion Constrained and Time Constrained. Frames with blinks and off-angle gaze are eliminated using frame averaging and correlation. Quality factors, namely motion blur, out of focus, translational motion and lighting present in iris videos are detected and their effect on recognition performance is investigated. Experimental results are carried out on both the MBGC NIR Iris Video and the MBGC NIR Iris Still datasets from the National Institute for Standards and Technology (NIST). Firstly, this work demonstrates that the proposed optimal frame selection technique in NIR Iris Videos leads to significant improvement in recognition performance. Secondly, the performance of NIR Iris Still images vs. NIR Iris Videos is compared. Thirdly, we show that interoperability between iris frames and iris images in an iris recognition system affects performance. Finally, the computational time and the elimination of noisy frames at each stage using the proposed method are examined.
Starting Page	1
Ending Page	8
File Size	912738
Page Count	8
File Format	PDF
ISBN	9781479921263
DOI	10.1109/DICTA.2013.6691486
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-26
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image quality Iris Histograms Correlation Lighting Iris recognition Videos
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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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