Paper Info
Title
A Unified Model for Fingerprint Authentication and Presentation Attack Detection
Abstract
Typical fingerprint recognition systems are comprised of a spoof detection module and a subsequent recognition module, running one after the other. In this paper, we reformulate the workings of a typical fingerprint recognition system. In particular, we posit that both spoof detection and fingerprint recognition are correlated tasks. Therefore, rather than performing the two tasks separately, we propose a joint model for spoof detection and matching <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> to simultaneously perform both tasks without compromising the accuracy of either task. We demonstrate the capability of our joint model to obtain an authentication accuracy (1:1 matching) of TAR = 100% @ FAR = 0.1% on the FVC 2006 DB2A dataset while achieving a spoof detection ACE of 1.44% on the LiveDet 2015 dataset, both maintaining the performance of stand-alone methods. In practice, this reduces the time and memory requirements of the fingerprint recognition system by 50% and 40%, respectively; a significant advantage for recognition systems running on resource-constrained devices and communication channels.
Year
DOI
Venue
2021
10.1109/IJCB52358.2021.9484382
2021 IEEE International Joint Conference on Biometrics (IJCB)
Keywords
DocType
ISSN
communication channels,resource-constrained devices,LiveDet 2015 dataset,FVC 2006 DB2A dataset,joint model,spoof matching,spoof detection ACE,authentication accuracy,recognition module,spoof detection module,typical fingerprint recognition system,presentation attack detection,fingerprint authentication,unified model
Conference
2474-9680
ISBN
Citations 
PageRank 
978-1-6654-3781-3
2
0.35
References 
Authors
0
6
Name
Order
Citations
PageRank
Additya Popli120.35
Saraansh Tandon220.35
Joshua J. Engelsma3225.78
Naoyuki Onoe420.35
Atsushi Okubo520.35
Anoop M. Namboodiri625526.36