Matching Fingerphotos to Slap Fingerprint Images
Debayan Deb, Tarang Chugh, Joshua Engelsma, Kai Cao, Neeta Nain, Jake, Kendall, and Anil K. Jain

TL;DR
This paper demonstrates that fingerphotos captured by smartphones can effectively match with traditional slap fingerprint images, enabling low-cost biometric authentication for various applications in developing countries.
Contribution
It introduces a method to match fingerphotos from smartphones with slap fingerprint images, showing promising accuracy and usability for large-scale biometric deployment.
Findings
Achieved 95.79% TAR at 0.1% FAR for fingerphoto-to-slap matching.
Baseline contact-based fingerprint matching achieved 98.55% TAR at 0.1% FAR.
Smartphone apps showed acceptable failure rates and acquisition times.
Abstract
We address the problem of comparing fingerphotos, fingerprint images from a commodity smartphone camera, with the corresponding legacy slap contact-based fingerprint images. Development of robust versions of these technologies would enable the use of the billions of standard Android phones as biometric readers through a simple software download, dramatically lowering the cost and complexity of deployment relative to using a separate fingerprint reader. Two fingerphoto apps running on Android phones and an optical slap reader were utilized for fingerprint collection of 309 subjects who primarily work as construction workers, farmers, and domestic helpers. Experimental results show that a True Accept Rate (TAR) of 95.79 at a False Accept Rate (FAR) of 0.1% can be achieved in matching fingerphotos to slaps (two thumbs and two index fingers) using a COTS fingerprint matcher. By comparison,…
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Taxonomy
TopicsBiometric Identification and Security · Face recognition and analysis · Forensic Fingerprint Detection Methods
