Monocular 3D Fingerprint Reconstruction and Unwarping

Abstract: Compared with contact-based fingerprint acquisition techniques, contactless acquisition has the advantages of less skin distortion, larger fingerprint area, and hygienic acquisition. However, perspective distortion is a challenge in contactless fingerprint recognition, which changes ridge orientation, frequency, and minutiae location, and thus causes degraded recognition accuracy. We propose a learning based shape from texture algorithm to reconstruct a 3D finger shape from a single image and unwarp the raw image to suppress perspective distortion. Experimental results on contactless fingerprint databases show that the proposed method has high 3D reconstruction accuracy. Matching experiments on contactless-contact and contactless-contactless matching prove that the proposed method improves matching accuracy.