Biometric bits extraction through phase quantization based on feature level fusion

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2 Citations (Scopus)


Biometric bits extraction has emerged as an essential technique for the study of biometric template protection as well as biometric cryptosystems. In this paper, we present a non-invertible but revocable bits extraction technique by means of quantizing the facial data from two feature extractors in the phase domain, which we coin as aligned feature-level fusion phase quantization (AFPQ). In this technique, we utilize helper data to achieve the revocability requirement of bits extraction. The feature averaging and remainder normalization technique are integrated with the helper data to reduce feature variance within the same individual and increase the distinctiveness of bit strings of different individuals to achieve good recognition performance. A scenario in which the system is compromised by an adversary is also considered. As a generic technique, AFPQ can be easily extended to multiple different biometric modalities.

Original languageEnglish
Pages (from-to)255-273
Number of pages19
JournalTelecommunication Systems
Issue number3-4
Publication statusPublished - 2011 Aug

Bibliographical note

Funding Information:
Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) through the Biometrics Engineering Research Center (BERC) at Yonsei University. No. R112002105080020(2010).

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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