A Robust Warping Method for Fingerprint Matching

Abstract

This paper presents a robust warping method for minutiae based fingerprint matching approaches. In this method, a deformable fingerprint surface is described using a triangular mesh model. For given two extracted minutiae sets and their correspondences, the proposed method constructs an energy function using a robust correspondence energy estimator and smoothness measuring of the mesh model. We obtain a convergent deformation pattern using an efficient gradient based energy optimization method. This energy optimization approach deals successfully with deformation errors caused by outliers, which are more difficult problems for the thin-plate spline (TPS) model. The proposed method is fast and the run-time performance is comparable with the method based on the TPS model. In the experiments, we provide a visual inspection of warping results on given correspondences and quantitative results using database.