xTARP: Improving the Tented Arch Reference Point Detection Algorithm

Abstract

In 2013, Tams et al. proposed a method to determine directed reference points in fingerprints based on a mathematical model of typical orientation fields of tented arch type fingerprints. Although this Tented Arch Reference Point (TARP) method has been used successfully for prealignment in biometric cryptosystems, its accuracy does not yet ensure satisfactory error rates for single finger systems. In this paper, we improve the TARP algorithm by deploying an improved orientation field computation and by integrating an additional mathematical model for arch type fingerprints. The resulting Extended Tented Arch Reference Point (xTARP) method combines the arch model with the tented arch model and achieves a significantly better accuracy than the original TARP algorithm. When deploying the xTARP method in the Fuzzy Vault construction of Butt et al., the false non-match rate (FNMR) at a security level of 20 bits is reduced from 7:4% to 1:7%.