Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing

Zhe Jin; Andrew Beng Jin Teoh

doi:10.1109/ICIEA.2015.7334128

Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing

Zhe Jin, Andrew Beng Jin Teoh

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

ISO/IEC 19794-2 compliant fingerprint minutiae template is an unordered and variable-size point set data. Such characteristic leads to restriction to the applications that can only operate on the ordered fixed-length bit-string, such as cryptographic protocols and biometric cryptosystem scheme like fuzzy commitment and fuzzy extractor operating in hamming domain. In this paper, we propose a discriminative fixed-length binary representation converted from fingerprint minutia based on Kernelized Locality-Sensitive Hashing (KLSH), which enables speedy matching. The proposed method includes four steps: minutiae descriptor extraction; Kernelized Locality-Sensitive Hashing for fixed length vector generation; dynamic feature binarization and matching. Experimental results on FVC2002 databases justify the feasibility of the proposed template in terms of matching accuracy and template randomness.

Original language	English
Title of host publication	Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	296-301
Number of pages	6
ISBN (Electronic)	9781467373173
DOIs	https://doi.org/10.1109/ICIEA.2015.7334128
Publication status	Published - 2015 Nov 20
Event	10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015 - Auckland, New Zealand Duration: 2015 Jun 15 → 2015 Jun 17

Publication series

Name	Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015

Other

Other	10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
Country/Territory	New Zealand
City	Auckland
Period	15/6/15 → 15/6/17

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

All Science Journal Classification (ASJC) codes

Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/ICIEA.2015.7334128

Cite this

Jin, Z., & Teoh, A. B. J. (2015). Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing. In Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015 (pp. 296-301). Article 7334128 (Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEA.2015.7334128

Jin, Zhe ; Teoh, Andrew Beng Jin. / Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing. Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 296-301 (Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015).

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abstract = "ISO/IEC 19794-2 compliant fingerprint minutiae template is an unordered and variable-size point set data. Such characteristic leads to restriction to the applications that can only operate on the ordered fixed-length bit-string, such as cryptographic protocols and biometric cryptosystem scheme like fuzzy commitment and fuzzy extractor operating in hamming domain. In this paper, we propose a discriminative fixed-length binary representation converted from fingerprint minutia based on Kernelized Locality-Sensitive Hashing (KLSH), which enables speedy matching. The proposed method includes four steps: minutiae descriptor extraction; Kernelized Locality-Sensitive Hashing for fixed length vector generation; dynamic feature binarization and matching. Experimental results on FVC2002 databases justify the feasibility of the proposed template in terms of matching accuracy and template randomness.",

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Jin, Z & Teoh, ABJ 2015, Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing. in Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015., 7334128, Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015, Institute of Electrical and Electronics Engineers Inc., pp. 296-301, 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015, Auckland, New Zealand, 15/6/15. https://doi.org/10.1109/ICIEA.2015.7334128

Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing. / Jin, Zhe; Teoh, Andrew Beng Jin.
Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 296-301 7334128 (Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Jin Z, Teoh ABJ. Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing. In Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 296-301. 7334128. (Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015). doi: 10.1109/ICIEA.2015.7334128

Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing

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