3D to 2D fingerprints: Unrolling and distortion correction

Abstract

Touchless 3D fingerprint sensors can capture both 3D depth information and albedo images of the finger surface. Compared with 2D fingerprint images acquired by traditional contact-based fingerprint sensors, the 3D fingerprints are generally free from the distortion caused by non-uniform pressure and undesirable motion of the finger. Several unrolling algorithms have been proposed for virtual rolling of 3D fingerprints to obtain 2D equivalent fingerprints, so that they can be matched with the legacy 2D fingerprint databases. However, available unrolling algorithms do not consider the impact of distortion that is typically present in the legacy 2D fingerprint images. In this paper, we conduct a comparative study of representative unrolling algorithms and propose an effective approach to incorporate distortion into the unrolling process. The 3D fingerprint database was acquired by using a 3D fingerprint sensor being developed by the General Electric Global Research. By matching the 2D equivalent fingerprints with the corresponding 2D fingerprints collected with a commercial contact-based fingerprint sensor, we show that the compatibility between the 2D unrolled fingerprints and the traditional contact-based 2D fingerprints is improved after incorporating the distortion into the unrolling process.