Yehuda Naveli, Michal Rimon, et al.
AAAI/IAAI 2006
Reliable and accurate verification of people is extremely important in a number of business transactions as well as access to privileged information. Automatic verification methods based on physical biometric characteristics such as fingerprint or iris can provide positive verification with a very high accuracy. However, the biometrics-based methods assume that the physical characteristics of an individual (as captured by a sensor) used for verification are sufficiently unique to distinguish one person from another. Identical twins have the closest genetics-based relationship and, therefore, the maximum similarity between fingerprints is expected to be found among identical twins. We show that a state-of-the-art automatic fingerprint verification system can successfully distinguish identical twins though with a slightly lower accuracy than nontwins. © 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Yehuda Naveli, Michal Rimon, et al.
AAAI/IAAI 2006
Dzung Phan, Vinicius Lima
INFORMS 2023
Annina Riedhauser, Viacheslav Snigirev, et al.
CLEO 2023
Jianchang Mao, Patrick J. Flynn, et al.
Computer Vision and Image Understanding