First International Fingerprint Liveness Detection Competition—LivDet 2009

Abstract

Fingerprint recognition systems are vulnerable to artificial spoof fingerprint attacks, like molds made of silicone, gelatin or Play-Doh. "Liveness detection", which is to detect vitality information from the biometric signature itself, has been proposed to defeat these kinds of spoof attacks. The goal for the LivDet 2009 competition is to compare different methodologies for softwarebased fingerprint liveness detection with a common experimental protocol and large dataset of spoof and live images. This competition is open to all academic and industrial institutions which have a solution for software-based fingerprint vitality detection problem. Four submissions resulted in successful completion: Dermalog, ATVS, and two anonymous participants (one industrial and one academic). Each participant submitted an algorithm as a Win32 console application. The performance was evaluated for three datasets, from three different optical scanners, each with over 1500 images of "fake" and over 1500 images of "live" fingerprints. The best results were from the algorithm submitted by Dermalog with a performance of 2.7% FRR and 2.8% FAR for the Identix (L-1) dataset. The competition goal is to become a reference event for academic and industrial research in software-based fingerprint liveness detection and to raise the visibility of this important research area in order to decrease risk of fingerprint systems to spoof attacks.

A high performance fingerprint liveness detection method based on quality related features

“…In this particular case we can observe a very big difference in the performance of the system when the training and test sets are exchanged, with an abnormally high False Fake Rate (over 50%) when the development set is used for training and the test set for evaluation. This same behaviour was observed in the rest of the participants in the LivDet competition (results of the competition are analyzed in [19]). …”

“…• LivDet Database [19]. It comprises three datasets of real and fake fingerprints captured each of them with a different flat optical sensor: (i) Biometrika FX2000 (569 dpi), (ii) CrossMatch Verifier 300CL (500 dpi), and (iii) Identix DFR2100 (686 dpi).…”

“…The performance of the proposed method is evaluated on the database provided in the Fingerprint Liveness Detection Competition LivDet 2009 [19], and on a publicly available database captured at the ATVS group [15]. The complete experimental dataset comprises over 10,500 real and fake images captured with five different sensors.…”

Evaluating software-based fingerprint liveness detection using Convolutional Networks and Local Binary Patterns

“…We used the datasets provided by the Liveness Detection Competition (LivDet) in the years of 2009 [9], 2011 [49] and 2013 [50].…”

Combining match scores with liveness values in a fingerprint verification system

“…The performance of the proposed methods was evaluated on a subset of the CrossMatch database taken from the Fingerprint Liveness Detection Competition 2009 [13]. It is made up of live and spoof fingerprint samples imaged using a CrossMatch optical scanner with a resolution factor of 500 dpi and an image size of 480x640 pixels.…”