Spectral Minutiae Representations for Fingerprint Recognition

The spectral minutiae representation introduced in this paper is a novel method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation becomes translation that can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with a template protection scheme that requires a fixed-length feature vector as input. In this paper, the authors will first introduce the spectral minutiae representation scheme. Then they will present several biometric fusion approaches to improve the biometric system performance by combining multiple sources of biometric information.