Iris recognition: the consequences of image compression

Authors:
Robert W. Ives;Daniel A. Bishop;Yingzi Du;Craig Belcher
Affiliations:
Department of Electrical and Computer Engineering, U.S. Naval Academy, Annapolis, MD;School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA;Department of Electrical and Computer Engineering, Indiana University, Purdue University Indianapolis, Indianapolis, IN;Department of Electrical and Computer Engineering, Indiana University, Purdue University Indianapolis, Indianapolis, IN
Venue:
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Year:
2010

Citing 6
Cited 2

Elements of information theory

Elements of information theory
High Confidence Visual Recognition of Persons by a Test of Statistical Independence

IEEE Transactions on Pattern Analysis and Machine Intelligence
Corrections to "A selective feature information approach for iris image-quality measure"

IEEE Transactions on Information Forensics and Security
Effect of Severe Image Compression on Iris Recognition Performance

IEEE Transactions on Information Forensics and Security
New Methods in Iris Recognition

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
How iris recognition works

IEEE Transactions on Circuits and Systems for Video Technology

A comprehensive approach for skin recognition

International Journal of Biometrics
A comprehensive approach for sclera image quality measure

International Journal of Biometrics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA) is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.