Title
Improved Iris Recognition through Fusion of Hamming Distance and Fragile Bit Distance
Abstract
The most common iris biometric algorithm represents the texture of an iris using a binary iris code. Not all bits in an iris code are equally consistent. A bit is deemed fragile if its value changes across iris codes created from different images of the same iris. Previous research has shown that iris recognition performance can be improved by masking these fragile bits. Rather than ignoring fragile bits completely, we consider what beneficial information can be obtained from the fragile bits. We find that the locations of fragile bits tend to be consistent across different iris codes of the same eye. We present a metric, called the fragile bit distance, which quantitatively measures the coincidence of the fragile bit patterns in two iris codes. We find that score fusion of fragile bit distance and Hamming distance works better for recognition than Hamming distance alone. To our knowledge, this is the first and only work to use the coincidence of fragile bit locations to improve the accuracy of matches.
Year
DOI
Venue
2011
10.1109/TPAMI.2011.89
IEEE Trans. Pattern Anal. Mach. Intell.
Keywords
Field
DocType
image texture,hamming distance,iris recognition,image fusion,biometrics,hamming codes
Iris recognition,Computer vision,Hamming code,Pattern recognition,Image fusion,Computer science,Image texture,Hamming distance,Coincidence,Artificial intelligence,Biometrics,Binary number
Journal
Volume
Issue
ISSN
33
12
0162-8828
Citations 
PageRank 
References 
28
1.18
9
Authors
3
Name
Order
Citations
PageRank
Karen Hollingsworth1734.56
Kevin W. Bowyer211121734.33
Patrick J. Flynn34405307.04