Abstract
A dual-factor authentication methodology coined as S-Iris Encoding is proposed based on the iterated inner-products between the secret pseudo-random number and the iris feature, and with thresholding to produce a unique compact binary code per person. A thresholding method is devised to exclude the weak inner-product during the encoding process, and thus contribute to the improvement of performance. S-Iris Encoding is primary formulated based on the cancelable biometrics principle to protect against biometrics fabrication. The problem could be rectified by S-Iris code through the token replacement so that a new code can be generated instantly just as a new credit card number can be issued if the old one is compromised. Besides that, S-Iris code is non-invertible and can only contribute to the authentication process when both genuine biometrics template and token are presented. By applying S-Iris Encoding with weak inner-product exclusion, the original iris feature length can be greatly reduced to around 4% of the original size and a 0% of equal error rate (EER) can be attained in CASIA Iris image database.
| Original language | English |
|---|---|
| Pages (from-to) | 169-177 |
| Number of pages | 9 |
| Journal | Computer Vision and Image Understanding |
| Volume | 102 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2006 May 1 |
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All Science Journal Classification (ASJC) codes
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
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High security Iris verification system based on random secret integration. / Siew Chin, Chong; Teoh, Beng Jin; Chek Ling, David Ngo.
In: Computer Vision and Image Understanding, Vol. 102, No. 2, 01.05.2006, p. 169-177.Research output: Contribution to journal › Article
TY - JOUR
T1 - High security Iris verification system based on random secret integration
AU - Siew Chin, Chong
AU - Teoh, Beng Jin
AU - Chek Ling, David Ngo
PY - 2006/5/1
Y1 - 2006/5/1
N2 - A dual-factor authentication methodology coined as S-Iris Encoding is proposed based on the iterated inner-products between the secret pseudo-random number and the iris feature, and with thresholding to produce a unique compact binary code per person. A thresholding method is devised to exclude the weak inner-product during the encoding process, and thus contribute to the improvement of performance. S-Iris Encoding is primary formulated based on the cancelable biometrics principle to protect against biometrics fabrication. The problem could be rectified by S-Iris code through the token replacement so that a new code can be generated instantly just as a new credit card number can be issued if the old one is compromised. Besides that, S-Iris code is non-invertible and can only contribute to the authentication process when both genuine biometrics template and token are presented. By applying S-Iris Encoding with weak inner-product exclusion, the original iris feature length can be greatly reduced to around 4% of the original size and a 0% of equal error rate (EER) can be attained in CASIA Iris image database.
AB - A dual-factor authentication methodology coined as S-Iris Encoding is proposed based on the iterated inner-products between the secret pseudo-random number and the iris feature, and with thresholding to produce a unique compact binary code per person. A thresholding method is devised to exclude the weak inner-product during the encoding process, and thus contribute to the improvement of performance. S-Iris Encoding is primary formulated based on the cancelable biometrics principle to protect against biometrics fabrication. The problem could be rectified by S-Iris code through the token replacement so that a new code can be generated instantly just as a new credit card number can be issued if the old one is compromised. Besides that, S-Iris code is non-invertible and can only contribute to the authentication process when both genuine biometrics template and token are presented. By applying S-Iris Encoding with weak inner-product exclusion, the original iris feature length can be greatly reduced to around 4% of the original size and a 0% of equal error rate (EER) can be attained in CASIA Iris image database.
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UR - http://www.scopus.com/inward/citedby.url?scp=33645837429&partnerID=8YFLogxK
U2 - 10.1016/j.cviu.2006.01.002
DO - 10.1016/j.cviu.2006.01.002
M3 - Article
VL - 102
SP - 169
EP - 177
JO - Computer Vision and Image Understanding
JF - Computer Vision and Image Understanding
SN - 1077-3142
IS - 2
ER -