Matching with Secure Fingerprint Templates Using Non-invertible Transform

This paper presents an approach to generate secure minutiae information in fingerprint templates. Using triplets of minutia points, useful geometrical properties can be derived from minutia triplets to hide their coordinates, direction of minutia, and scale. This non-invertible transform enables matching from the results in the anonymous domain to fight against malicious attacks to biometrics. The goal is to achieve non-invertibility of the transformed templates without loss of discriminating capability. Proposed features can match two templates without alignment under low time complexity and memory requirement. The proposed approach is proven effective using the FVC2002 database to compare matching performances. The best result shows 3.61% of equal-error rate for the database DB2_A.