TY - GEN
T1 - Selection of distinguish points for class distribution preserving transform for biometric template protection
AU - Feng, Yi C.
AU - Yuen, Pong C.
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - This paper addresses the biometric template security issue. Follow out previous work on class distribution transform, the proposed scheme selects the distinguish points automatically. By considering the geometric relationship with the biometric templates, the proposed scheme transforms a real-value biometric template to a binary string such that the class distribution is preserved and proved mathematically. The binary string is then further encoded using BCH and hashing method to ensure that the template protecting algorithm is non-invertible. Two face databases, namely ORL and FERET, are selected for evaluation and LDA is used for creating the original template. Experimental results show that by integrating the proposed scheme into the LDA (original) algorithm, the system performance can be further improved by 1.1% and 4%, in terms of equal error rate, on ORL and FERET databases respectively. The results show that the proposed scheme not only can preserve the original template discriminant power, but also improve the performance if the original template is not fully optimized.
AB - This paper addresses the biometric template security issue. Follow out previous work on class distribution transform, the proposed scheme selects the distinguish points automatically. By considering the geometric relationship with the biometric templates, the proposed scheme transforms a real-value biometric template to a binary string such that the class distribution is preserved and proved mathematically. The binary string is then further encoded using BCH and hashing method to ensure that the template protecting algorithm is non-invertible. Two face databases, namely ORL and FERET, are selected for evaluation and LDA is used for creating the original template. Experimental results show that by integrating the proposed scheme into the LDA (original) algorithm, the system performance can be further improved by 1.1% and 4%, in terms of equal error rate, on ORL and FERET databases respectively. The results show that the proposed scheme not only can preserve the original template discriminant power, but also improve the performance if the original template is not fully optimized.
KW - Biometric template security
KW - Class distribution preserving
KW - Face recognition
KW - One-way transform
UR - http://www.scopus.com/inward/record.url?scp=37849024120&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-74549-5_67
DO - 10.1007/978-3-540-74549-5_67
M3 - Conference proceeding
AN - SCOPUS:37849024120
SN - 9783540745488
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 636
EP - 645
BT - Advances in Biometrics - International Conference, ICB 2007, Proceedings
PB - Springer Verlag
T2 - 2007 International Conference on Advances in Biometrics, ICB 2007
Y2 - 27 August 2007 through 29 August 2007
ER -