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Biometric Template Binarization

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Encyclopedia of Biometrics
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Synonyms

Biometric discretization

Definition

Biometric binarization is the process of converting real-valued biometric features into a binary string. For many modalities (e.g., face, fingerprint, and signature) where the extracted features are intrinsically real valued, biometric binarization is developed for transforming the features into an acceptable form of input to many template protection schemes such as fuzzy commitment, fuzzy extractor, secure sketch, and helper data systems. Due to noisy nature of biometrics, the binary biometric representation extracted during verification may contain errors (bit differences) with reference to the reference template. The number of bit differences must not exceed the system (Hamming distance) decision threshold for obtaining a positive match.

Biometric binarization can be assessed using three criteria â€“ performance, security, and privacy. Performance is referred to as the classification performance of binary representations where a good...

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References

  1. Y. Chang, W. Zhang, T. Chen, Biometric-based cryptographic key generation, in Proceedings of IEEE International Conference on Multimedia and Expo (ICME’04), Taipei, vol. 3, 2004, pp. 2203–2206

    Google Scholar 

  2. C. Chen, R. Veldhuis, Binary Biometric Representation through Pairwise Polar Quantization, in Proceedings of the 3rd International Conference on Advances in Biometrics (ICB’09), Sardinia Island. LNCS, vol. 5558, 2009, pp. 72–81

    Google Scholar 

  3. C. Chen, R. Veldhuis, Binary biometric representation through pairwise adaptive phase quantization. EURASIP J. Inf. Secur. 2011, Article ID 543106, 16pp (2011)

    Google Scholar 

  4. C. Chen, R. Veldhuis, T. Kevenaar, A. Akkermans, Multi-bits biometric string generation based on the likelihood ratio, in Proceedings of 1st IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS’07), Washington DC, 2007, pp. 1–6

    Google Scholar 

  5. C. Chen, R. Veldhuis, T. Kevenaar, A. Akkermans, Biometric quantization through detection rate optimized bit allocation. EURASIP J. Adv. Signal Process. 2009, Article ID 784834, 16pp (2009)

    Google Scholar 

  6. F. Hao, C.W. Chan, Private key generation from on-line handwritten signatures. Inf. Manage. Comput. Secur. 10(4), 159–164 (2002)

    MathSciNet  Google Scholar 

  7. A. Kumar, D. Zhang, Hand Geometry Recognition using Entropy-based Discretization. IEEE Trans. Inf. Forensics Secur. 2, 181–187 (2007)

    Google Scholar 

  8. M.-H. Lim, A.B.J. Teoh, Non-user-specific multivariate biometric discretization with medoid-based segmentation, in Proceedings of 6th Chinese Conference on Biometric Recognition (CCBR’11), Beijing. LNCS, vol. 7098, 2011, pp. 279–287

    Google Scholar 

  9. M.-H. Lim, A.B.J. Teoh, A novel class of encoding scheme for efficient biometric discretization: linearly separable subcode. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 35(2), 300–313 (2013)

    Google Scholar 

  10. M.-H. Lim, A.B.J. Teoh, K.-A. Toh, An efficient dynamic reliability-dependent bit allocation for biometric discretization. Pattern Recognit. 45(5), 1960–1971 (2012)

    Google Scholar 

  11. F. Monrose, M.K. Reiter, Q. Li, S. Wetzel, Cryptographic key generation from voice, in Proceedings of the IEEE Symposium on Security and Privacy (S&P’01), Oakland, 2001, pp. 202–213

    Google Scholar 

  12. J.-P. Linnartz, P. Tuyls, New shielding functions to enhance privacy and prevent misuse of biometric templates, in Proceedings of the 4th International Conference on Audio and Video Based Person Authentication (AVBPA’03), Guildford. LNCS, vol. 2688, 2003, pp. 393–402

    Google Scholar 

  13. W. Sheng, W.G.J. Howells, M.C. Fairhurst, F. Deravi, Template-free biometric-key generation by means of fuzzy genetic clustering. IEEE Trans. Inf. Forensics Secur. 3(2), 183–191 (2008)

    Google Scholar 

  14. A.B.J. Teoh, W.K. Yip, S. Lee, Cancellable biometrics and annotations on BioHash. Pattern Recognit. 41(6), 2034–2044 (2008)

    MATH  Google Scholar 

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Correspondence to Meng-Hui Lim .

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Lim, MH., Teoh, A.B.J. (2015). Biometric Template Binarization. In: Li, S.Z., Jain, A.K. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7488-4_9079

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