Generation of Synthetic Fingerphotos with GANs

2026-08-15

AI Summary

This study addresses the scarcity of real-world data and privacy concerns in contactless fingerprint recognition by proposing a synthetic fingerprint generation framework based on StyleGAN2-ADA/3. Integrating biometric statistics with matching score analysis, this work presents the first quantitative assessment of the fidelity, privacy preservation, and diversity of synthetic samples. The research validates the efficacy of synthetic data for system development and establishes a standardized benchmark for quantitative evaluation. By releasing open-source code, this project provides a reliable solution that balances privacy protection with data augmentation for contactless biometrics, alongside a robust evaluation paradigm for future research in synthetic biometric data generation.

Abstract

Contactless fingerprinting is an emerging approach to biometric authentication that allows users to scan their fingerprints without touching a scanner. Due to the limited amount of contactless fingerprint data available and the security risks associated with sharing real individuals' fingerprints, it is valuable to explore methods of generating synthetic data that can be used in place of - or in conjunction with - real data to develop and evaluate contactless fingerprinting systems. In this paper, we present and evaluate synthetic fingerphotos generated using StyleGAN2-ADA and StyleGAN3, existing image generation architectures. We evaluate the realism, privacy preservation, and variety of the synthetic fingerphotos by comparing their biometric feature statistics to those of real fingerphotos, computing match scores between real and synthetic fingerphotos, and computing match scores between different synthetic fingerphotos. This paper provides a quantitative comparison point for future evaluations of synthetic fingerphotos. The evaluation code is made available at https://github.com/cmillerlynch/fingerphoto-gan.

Problem

• Contactless fingerprinting
• Synthetic fingerphotos
• Data scarcity
• Privacy preservation

Innovation

• Synthetic Fingerphotos
• StyleGAN2-ADA
• StyleGAN3
• Contactless Fingerprinting
• Quantitative Evaluation