SynCoLFinGer: Synthetic Contactless Fingerprint Generator

TL;DR

SynCoLFinGer is a novel method for generating realistic synthetic contactless fingerprint images by modeling capturing conditions, subject traits, and environmental factors, enabling diverse quality levels for research and system testing.

Contribution

It introduces the first synthetic contactless fingerprint generator that accounts for various real-world influences and produces images comparable to real fingerprints.

Findings

Generated fingerprints show high resemblance to real samples.

Synthetic images achieve comparable biometric quality scores.

The method supports diverse quality levels for different applications.

Abstract

We present the first method for synthetic generation of contactless fingerprint images, referred to as SynCoLFinGer. To this end, the constituent components of contactless fingerprint images regarding capturing, subject characteristics, and environmental influences are modeled and applied to a synthetically generated ridge pattern using the SFinGe algorithm. The proposed method is able to generate different synthetic samples corresponding to a single finger and it can be parameterized to generate contactless fingerprint images of various quality levels. The resemblance of the synthetically generated contactless fingerprints to real fingerprints is confirmed by evaluating biometric sample quality using an adapted NFIQ 2.0 algorithm and biometric utility using a state-of-the-art contactless fingerprint recognition system.