Privacy preserved duplicate check using multi-biometric fusion

Automated recognition of individuals can be performed using biometrics without any requirement of explicit knowledge of a PIN or a password. On the one side biometrics has given convenience to citizens as they do not need to memorize a bunch of passwords, but on the other side intra (inter) class variations within (between) biometric features makes biometric authentications untrustworthy. Therefore, decisions based on biometric authentications are made more reliable by using several biometric authentications performed on single or multiple biomet-ric modalities (i.e. multi-biometric fusion). This paper describes a method to identify if a person tries to re-enrol him/herself in a database, when he/she is already enrolled. This is referred to as duplicate check. In this work, duplicate check is performed using two modalities: face and iris. The templates used during the duplicate check are compliant to the ISO/IEC 24745 - Biometric information protection. Such templates are known as protected biometric templates. The protected biometric templates used in this work are generated using the recently published irreversible transformation based on Bloom filters. Scores are calculated from face and iris Bloom filters based templates by comparison with their respective enrolment templates using the normalized Hamming distance. As a decision of the duplicate check, these scores from both modalities are fused with appropriate weighting factors in order to get improved performance compared to using single individual modalities. The presented scheme is experimentally validated using two public benchmark databases namely the LFW and the CASIA-Iris-Thousand databases for face and iris respectively.