Cancelable multi-biometrics: Mixing iris-codes based on adaptive bloom filters

In this work adaptive Bloom filter-based transforms are applied in order to mix binary iris biometric templates at feature level, where iris-codes are obtained from both eyes of a single subject. The irreversible mixing transform, which generates alignment-free templates, obscures information present in different iris-codes. In addition, the transform is parameterized in order to achieve unlinkability, implementing cancelable multi-biometrics. Experiments which are carried out on the IITD Iris Database version 1.0 confirm the soundness of the proposed approach, (1) maintaining biometric performance at equal error rates below 0.5% for different feature extraction methods and fusion scenarios and (2) achieving a compression of mixed templates down to 10% of original size.