A two-dimensional random projected minutiae vicinity decomposition-based cancellable fingerprint template

Zhe Jin, Bok Min Goi, Andrew Teoh, Yong Haur Tay

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)


With the massive deployment of biometric applications, protecting the biometric template has attracted great attention because of the privacy issue. Although many proposals on protecting biometric template have been reported in literature, design a method simultaneously satisfying four criteria, that is performance, non-invertibility, cancellability, and diversity still remains unsolved. In this paper, we proposed a two-dimensional random projected minutiae vicinity decomposition (MVD) technique to secure minutiae-based fingerprint template. Minutiae vicinity is first formed from a set of fingerprint minutiae and further used to generate a set of local features, namely MVD features; then, a random matrix derived from user-specific token is used to project MVD features for the concealment of the topology of MVD. Comprehensive experiments on fingerprint verification competition datasets are carried out, and the lowest equal error rate obtained in the stolen-token scenario is 3.07% and 1.02% for fingerprint verification competition 2002 database 1 and database 2, respectively. Besides, detail analyses on the irreversibility, cancellability, template size, and computational cost have been carried out.

Original languageEnglish
Pages (from-to)1691-1701
Number of pages11
JournalSecurity and Communication Networks
Issue number11
Publication statusPublished - 1 Nov 2014
Externally publishedYes


  • Fingerprint template protection
  • Minutiae vicinity decomposition
  • Two-dimensional random projection

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