David Carmel, Haggai Roitman, et al.
ACM TIST
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.
David Carmel, Haggai Roitman, et al.
ACM TIST
Ronen Feldman, Martin Charles Golumbic
Ann. Math. Artif. Intell.
Gaku Yamamoto, Hideki Tai, et al.
AAMAS 2008
Susan L. Spraragen
International Conference on Design and Emotion 2010