Special Section on Biometrics: Advances in Security, Usability, and Interoperability

Effects of image compression on iris recognition system performance

[+] Author Affiliations
Robert W. Ives

U.S. Naval Academy, Electrical Engineering Department, 105 Maryland Avenue, Annapolis, Maryland 21402

Randy P. Broussard

U.S. Naval Academy, Electrical Engineering Department, 105 Maryland Avenue, Annapolis, Maryland 21402

Lauren R. Kennell

U.S. Naval Academy, Electrical Engineering Department, 105 Maryland Avenue, Annapolis, Maryland 21402

David L. Soldan

Kansas State University, Electrical and Computer Engineering Department, 2061 Rathbone Hall, Manhattan, Kansas 66506

J. Electron. Imaging. 17(1), 011015 (March 13, 2008). doi:10.1117/1.2891313
History: Received June 15, 2007; Revised November 01, 2007; Accepted November 06, 2007; Published March 13, 2008
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The human iris is perhaps the most accurate biometric for use in identification. Commercial iris recognition systems currently can be found in several types of settings where a person’s true identity is required: to allow passengers in some airports to be rapidly processed through security; for access to secure areas; and for secure access to computer networks. The growing employment of iris recognition systems and the associated research to develop new algorithms will require large databases of iris images. If the required storage space is not adequate for these databases, image compression is an alternative. Compression allows a reduction in the storage space needed to store these iris images. This may, however, come at a cost: some amount of information may be lost in the process. We investigate the effects of image compression on the performance of an iris recognition system. Compression is performed using JPEG-2000 and JPEG, and the iris recognition algorithm used is an implementation of the Daugman algorithm. The imagery used includes both the CASIA iris database as well as the iris database collected by the University of Bath. Results demonstrate that compression up to 50:1 can be used with minimal effects on recognition.

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© 2008 SPIE and IS&T

Citation

Robert W. Ives ; Randy P. Broussard ; Lauren R. Kennell and David L. Soldan
"Effects of image compression on iris recognition system performance", J. Electron. Imaging. 17(1), 011015 (March 13, 2008). ; http://dx.doi.org/10.1117/1.2891313


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