• Title of article

    An alignment-free fingerprint bio-cryptosystem based on modified Voronoi neighbor structures

  • Author/Authors

    Yang، نويسنده , , Wencheng and Hu، نويسنده , , Jiankun and Wang، نويسنده , , Song and Stojmenovic، نويسنده , , Milos، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    12
  • From page
    1309
  • To page
    1320
  • Abstract
    Bio-cryptography is an emerging security technology which combines cryptography with biometrics. A good bio-cryptosystem is required to protect the privacy of the relevant biometric data as well as achieving high recognition accuracy. Fingerprints have been widely used in bio-cryptosystem design. However, fingerprint uncertainty caused by distortion and rotation during the image capturing process makes it difficult to achieve a high recognition rate in most bio-cryptographic systems. Moreover, most existing bio-cryptosystems rely on the accurate detection of singular points for fingerprint image pre-alignment, which is very hard to achieve, and the image rotation transformation during the alignment process can cause significant singular point deviation and minutiae changes. In this paper, by taking full advantage of local Voronoi neighbor structures (VNSs), e.g. local structural stability and distortion insensitivity, we propose an alignment-free bio-cryptosystem based on fixed-length bit-string representations extracted from modified VNSs, which are rotation- and translation-invariant and distortion robust. The proposed alignment-free bio-cryptosystem is able to provide strong security while achieving good recognition performance. Experimental results in comparison with most existing alignment-free bio-cryptosystems using the publicly-available databases show the validity of the proposed scheme.
  • Keywords
    Fingerprint , Bio-cryptosystem , Modified Voronoi neighbor structure , Distortion robust , Alignment-free , Fuzzy extractor
  • Journal title
    PATTERN RECOGNITION
  • Serial Year
    2014
  • Journal title
    PATTERN RECOGNITION
  • Record number

    1736079