Estimating Ridge Topologies with High Curvature for Fingerprint Authentication Systems

An orientation model provides an analytical means for describing fingerprint ridge orientations. It can help in data storage and recovery as well as other possible communication applications related to biometric security. Since fingerprint ridge patterns often possess both smooth features and high curvature patterns, it is not easy to describe the overall topology with a single analytical model. A combination approach of different models is a way to address the problem. In this paper, we explore this topic by investigating local orientation models for estimating high curvature patterns in the singular regions. Our experimental results show that the resulting combination approach can improve the overall topology estimation and thus the end performance of a fingerprint authentication system.