Cancellable iris template generation based on Indexing-First-One hashing

Yen Lung Lai, Zhe Jin, Andrew Beng Jin Teoh, Bok Min Goi, Wun She Yap, Tong Yuen Chai, Christian Rathgeb

Research output: Contribution to journalArticlepeer-review

87 Citations (Scopus)


Eye iris has been widely recognized as one of the strongest biometrics attributed to its high accuracy performance. However, templates in conventional iris recognition systems are unprotected and highly vulnerable to numerous security and privacy attacks. Despite a number of cancellable biometric schemes have been proposed but at the expense of substantially decreased accuracy performance. In this paper, we introduce a new cancellable iris scheme, coined as “Indexing-First-One” (IFO) hashing. IFO hashing is inspired from the Min-hashing that primarily used in text retrieval domain. However, IFO hashing has been further strengthened by two novel mechanisms, namely P-order Hadamard product and modulo threshold function. The IFO hashing scheme strikes the balance between accuracy performance and privacy/security protection. Comprehensive experiments on CASIA-v3 iris benchmark database and rigorous analysis demonstrate decent accuracy performance with respect to its original counterparts yet offer strong resilience against several major security and privacy attacks.

Original languageEnglish
Pages (from-to)105-117
Number of pages13
JournalPattern Recognition
Publication statusPublished - 2017 Apr 1

Bibliographical note

Funding Information:
This research was partly supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government(MSIP) (NO. 2016R1A2B4011656), Malaysian MOSTI Science fund 01-02-11-SF0201. Wun-She Yap would like to acknowledge the financial support by the Malaysian MOSTI Science Fund number 01-02-11-SF0189.

Publisher Copyright:
© 2016 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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