On the Application of Bloom Filters to Iris Biometrics

In this work the application of adaptive Bloom filters to binary iris biometric feature vectors, i.e. 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 (1) biometric template protection, (2) compression of biometric data, and (3) acceleration of biometric identification, while at the same time no significant degradation of biometric performance is observed. According to these fields of application detailed investigations are presented. Experiments are carried out 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 cancelable 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.