Generating Registration-free Cancelable Fingerprint Templates
Cancelable biometrics bridges the gap between the convenience of biometric authentication and security offered by cryptographic systems. There have been several prior attempts to construct cancelable templates out of fingerprint biometrics. However, existing approaches require pre-alignment of fingerprint images and therefore, are not robust to image registration errors. In this paper, we propose a provably secure, registration-free construction of cancelable fingerprint templates. Firstly, we present a new fingerprint representation based on localized, self-aligned texture features. Secondly, we demonstrate how to construct cancelable templates from them and also show how to harden the security of the proposed construction further. And finally, we present arguments for it resilience against various modes of adversarial attack.