On application of bloom filters to iris biometrics

• Published in: IET biometrics Vol. 3; no. 4; pp. 207 - 218
• Main Authors: Rathgeb, Christian, Breitinger, Frank, Busch, Christoph, Baier, Harald
• Format: Journal Article
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 01.12.2014; John Wiley & Sons, Inc
• Subjects: Acceleration; Adaptive algorithms; adaptive Bloom fllter‐based transform; Adaptive filters; binary iris biometric feature vectors; biometric data compression; Biometric identification; biometric identiflcation acceleration; biometric performance degradation; biometric template protection; Biometrics; Boundaries; CASIA‐v3 iris database; Compressing; Compression; computer science; Data compression; data structures; Enrollments; Feature extraction; feature extraction algorithms; Invariants; iris recognition; iris‐codes; Mathematical analysis; Performance degradation; Privacy; Representations; Rotation; rotation‐invariant cancellable templates; rotation‐invariant feature representation; Transforms; Vectors (mathematics); visual databases; data compression; biometric template protection; biometric performance degradation; feature extraction algorithms; transforms; visual databases; biometric identiflcation acceleration; rotation-invariant feature representation; binary iris biometric feature vectors; biometric data compression; computer science; feature extraction; rotation-invariant cancellable templates; adaptive Bloom fllter-based transform; CASIA-v3 iris database; data structures; iris recognition; iris-codes
• ISSN: 2047-4938; 2047-4946; 2047-4946
• DOI: 10.1049/iet-bmt.2013.0049

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.