• DocumentCode
    594770
  • Title

    Fingerprint liveness detection by local phase quantization

  • Author

    Ghiani, Luca ; Marcialis, Gian Luca ; Roli, F.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Univ. of Cagliari, Cagliari, Italy
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    537
  • Lastpage
    540
  • Abstract
    Fingerprint liveness detection consists in verifying if an input fingerprint image, acquired by a fingerprint verification system, belongs to a genuine user or is an artificial replica. Although several hardware- and software-based approaches have been proposed so far, this issue still remains unsolved due to the very high difficulty in finding effective features for detecting the fingerprint liveness. In this paper, we present a novel features set, based on the local phase quantization (LPQ) of fingerprint images. LPQ method is well-known for being insensitive to blurring effects, thus we believe it could be useful for detecting the differences between an alive and a fake fingerprint, due to the loss of information which may occur during the replica fabrication process. The method is tested on the four data sets of the Second International Fingerprint Liveness Detection Competition, and shows promising and competitive results with other state-of-the-art features sets.
  • Keywords
    fingerprint identification; LPQ method; Second International Fingerprint Liveness Detection Competition; alive fingerprint; artificial replica; blurring effects; data sets; fake fingerprint; features set; fingerprint image; fingerprint verification system; hardware-based approaches; local phase quantization; replica fabrication process; software-based approaches; Feature extraction; Fingerprint recognition; Fourier transforms; Quantization; Semiconductor optical amplifiers; Standards; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460190