On the similarity of identical twin fingerprints

Reliable and accurate veri!cation of people is extremely important in a number of business transactions as well as access to privileged information. Automatic veri!cation methods based on physical biometric characteristics such as !ngerprint or iris can provide positive veri!cation 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 veri!cation are su0ciently unique to distinguish one person from another. Identical twins have the closest genetics-based relationship and, therefore, the maximum similarity between !ngerprints is expected to be found among identical twins. We show that a state-of-the-art automatic !ngerprint veri!cation 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.