RT Journal Article
A1 Christian Rathgeb
AD Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany
A1 Frank Breitinger
AD Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany
A1 Christoph Busch
AD Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany
A1 Harald Baier
AD Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany

PB iet
T1 On application of bloom filters to iris biometrics
JN IET Biometrics
VO 3
IS 4
SP 207
OP 218
AB In this study, the application of adaptive Bloom filters to binary iris biometric feature vectors, that is, iris-codes, is proposed. Bloom filters, which have been established as a powerful tool in various fields of computer science, are applied in order to transform iris-codes to a rotation-invariant feature representation. Properties of the proposed Bloom filter-based transform concurrently enable (i) biometric template protection, (ii) compression of biometric data and (iii) acceleration of biometric identification, whereas at the same time no significant degradation of biometric performance is observed. According to these fields of application, detailed investigations are presented. Experiments are conducted on the CASIA-v3 iris database for different feature extraction algorithms. Confirming the soundness of the proposed approach, the application of adaptive Bloom filters achieves rotation-invariant cancellable templates maintaining biometric performance, a compression of templates down to 20–40% of original size and a reduction of bit-comparisons to less than 5% leading to a substantial speed-up of the biometric system in identification mode.
K1 iris-codes
K1 rotation-invariant feature representation
K1 biometric identiflcation acceleration
K1 biometric data compression
K1 computer science
K1 biometric performance degradation
K1 adaptive Bloom fllter-based transform
K1 biometric template protection
K1 rotation-invariant cancellable templates
K1 binary iris biometric feature vectors
K1 CASIA-v3 iris database
K1 feature extraction algorithms
DO https://doi.org/10.1049/iet-bmt.2013.0049
UL https://digital-library.theiet.org/;jsessionid=2thkernkl0dkj.x-iet-live-01content/journals/10.1049/iet-bmt.2013.0049
LA English
SN 2047-4938
YR 2014
OL EN