On application of bloom filters to iris biometrics
- Author(s): Christian Rathgeb 1 ; Frank Breitinger 1 ; Christoph Busch 1 ; Harald Baier 1
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View affiliations
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Affiliations:
1:
Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany
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Affiliations:
1:
Biometrics and Internet Security Research Group, Hochschule Darmstadt, Germany
- Source:
Volume 3, Issue 4,
December 2014,
p.
207 – 218
DOI: 10.1049/iet-bmt.2013.0049 , Print ISSN 2047-4938, Online ISSN 2047-4946
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.
Inspec keywords: iris recognition; feature extraction; data structures; visual databases; transforms; data compression
Other keywords: binary iris biometric feature vectors; biometric identiflcation acceleration; rotation-invariant cancellable templates; computer science; rotation-invariant feature representation; feature extraction algorithms; CASIA-v3 iris database; iris-codes; biometric template protection; biometric data compression; adaptive Bloom fllter-based transform; biometric performance degradation
Subjects: Computer vision and image processing techniques; Integral transforms; Image recognition; File organisation; Integral transforms
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