Real-Time Fingerprint Spoof Detection with Image Processing

EasyChair Preprint 13640

Abstract

Biometric authentication systems, particularly those relying on fingerprint recognition, are susceptible to spoofing attacks, wherein malicious actors attempt to deceive the system by presenting artificial fingerprints. Traditional fingerprint sensors often struggle to differentiate between genuine and spoofed prints, necessitating the development of robust anti-spoofing mechanisms. In this context, real-time fingerprint spoof detection using advanced image processing techniques emerges as a critical research area.
This study explores the implementation of real-time fingerprint spoof detection using cutting-edge image processing algorithms. We leverage high-resolution imaging coupled with deep learning models to analyze intricate patterns and features within fingerprint images. Our approach integrates feature extraction, classification, and verification stages to accurately discern between genuine and fake fingerprints.

Keyphrases: Fingerprint, image processing, spoof detection

@booklet{EasyChair:13640,
  author    = {Sophia Lorraine and Thomas Micheal},
  title     = {Real-Time Fingerprint Spoof Detection with Image Processing},
  howpublished = {EasyChair Preprint 13640},
  year      = {EasyChair, 2024}}