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 | |
| 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 | New Zealand |
| City | Auckland |
| Period | 15/6/15 → 15/6/17 |
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All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering
Cite this
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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
TY - GEN
T1 - Construct a new fixed-length binary fingerprint representation using Kernelized Locality-Sensitive Hashing
AU - Jin, Zhe
AU - Teoh, Andrew Beng Jin
PY - 2015/11/20
Y1 - 2015/11/20
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84960918867&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84960918867&partnerID=8YFLogxK
U2 - 10.1109/ICIEA.2015.7334128
DO - 10.1109/ICIEA.2015.7334128
M3 - Conference contribution
AN - SCOPUS:84960918867
T3 - Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
SP - 296
EP - 301
BT - Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -