IET Biometrics · 2014 · 124 citations · 40 references
ComputingComputer ScienceAuthenticationComputer VisionFeature EngineeringBiometric AuthenticationFeature DetectionFeature ExtractionFeature TransformationPattern RecognitionTemplate MatchingBiometric Feature ExtractionBiometric RecognitionBiometric System Performance EvaluationBiometric Template ProtectionBloom FiltersInvariant Feature RepresentationIris RecognitionIris Recognition Authentication
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.
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Space/time trade-offs in hash coding with allowable errors
Burton H. Bloom · Communications of the ACM · 1970 · 7.5K citations · Full text
John Daugman · IEEE Transactions on Circuits and Systems for Video Technology · 2004 · 2.9K citations
Network Applications of Bloom Filters: A Survey
Andrei Broder, Michael Mitzenmacher · Internet Mathematics · 2004 · 2K citations · Full text