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A High Performance Fingerprint Liveness Detection Method Based on Quality Related Features

Authors
  • Galbally, Javier
  • Alonso-Fernandez, Fernando
  • Fierrez, Julian
  • Ortega-Garcia, Javier
Publication Date
Jan 01, 2012
Identifiers
DOI: 10.1016/j.future.2010.11.024
OAI: oai:DiVA.org:hh-21193
Source
DiVA - Academic Archive On-line
Keywords
Language
English
License
Green
External links

Abstract

A new software-based liveness detection approach using a novel fingerprint parameterization based on quality related features is proposed. The system is tested on a highly challenging database comprising over 10,500 real and fake images acquired with five sensors of different technologies and covering a wide range of direct attack scenarios in terms of materials and procedures followed to generate the gummy fingers. The proposed solution proves to be robust to the multi-scenario dataset, and presents an overall rate of 90% correctly classified samples. Furthermore, the liveness detection method presented has the added advantage over previously studied techniques of needing just one image from a finger to decide whether it is real or fake. This last characteristic provides the method with very valuable features as it makes it less intrusive, more user friendly, faster and reduces its implementation costs. © 2010 Elsevier B.V. All rights reserved.

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