Rama Akkiraju, Pinar Keskinocak, et al.
Applied Intelligence
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.
Rama Akkiraju, Pinar Keskinocak, et al.
Applied Intelligence
Vicki L Hanson, Edward H Lichtenstein
Cognitive Psychology
Wooseok Choi, Tommaso Stecconi, et al.
Advanced Science
Guo-Jun Qi, Charu Aggarwal, et al.
IEEE TPAMI