A hierarchical fingerprint alignment method and its application to fuzzy vault

Fuzzy vault is a practical and promising scheme, which can protect biometric templates and perform secure key management simultaneously. Aligning the query sample and the template sample in the encrypted domain remains a challenging task in the fingerprint-based fuzzy vault scheme. To some extent, all the existing fingerprint aligning methods in the encrypted domain have their own drawbacks, e.g., not enough alignment accuracy or information leakage because of publishing helper data. In this paper, a novel fingerprint aligning method is proposed, which integrates the fingerprint reference points and its neighboring region of interest(ROI) in a hierarchical manner. The concept of mutual information(MI) in the information theory is used to assess the coincidence extent of two fingerprints after being aligned. The novel alignment method is applied to fingerprint-based fuzzy vault implementation. Out of information leakage consideration, the orientation features of fingerprint minutiae are discarded and another distinguishing local feature, inter-minutiae ridge count, is used to replace the minutiae orientation in the implementation of fingerprint-based fuzzy vault. Experiment on FVC2002 DB2a is conducted to show the virtue of proposed alignment method and the promising performance of proposed fingerprint-based fuzzy vault implementation.