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Large Scale Experiments on Fingerprint Liveness Detection

  • Gian Luca Marcialis
  • Luca Ghiani
  • Katja Vetter
  • Dirk Morgeneier
  • Fabio Roli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7626)

Abstract

Fingerprint liveness detection consists in extracting measurements, from a fingerprint image, allowing to distinguish between an “alive” fingerprint image, that is, an image coming from the fingertip of the claimed identity, and an artificial replica. Several algorithms have been proposed so far, but the robustness of their performance has not yet been compared when varying several environmental conditions. In this paper, we present a set of experiments investigating the performance of several feature sets designed for fingerprint liveness detection. In particular we assessed the decrease of performance when varying the pressure and the environmental illumination as well as the size of the region of interest (ROI) used for extracting such features. Experimental results on a large data set show the different dependence of some features sets on the investigated conditions.

Keywords

Local Binary Pattern Multi Layer Perceptron Large Scale Experiment Baseline System Fingerprint Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Gian Luca Marcialis
    • 1
  • Luca Ghiani
    • 1
  • Katja Vetter
    • 2
  • Dirk Morgeneier
    • 2
  • Fabio Roli
    • 1
  1. 1.Department of Electrical and Electronic EngineeringUniversity of CagliariItaly
  2. 2.Crossmatch Technologies Inch.USA

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