Reliable and accurate identification of people is extremely important in a number of business transactions as well as access to privileged information. This is especially crucial when a user is at a remote location connected through a network. Automatic identification methods based on physical biometric characteristics such as fingerprint or iris can provide positive identification with a very high accuracy. However, the biometricsbased methods assume that the physical characteristics of an individual (as captured by a sensor) used for identification are unique. This claim has only been verified qualitatively but it has not been established in a quantitative manner. We determine the intrinsic similarity between fingerprints which is one of the major factors that will determine the limitations of an automatic fingerprint identification system. Identical twins have the closest geneticsbased relationship and, therefore, the maximum similarity between fingerprints is expected to be found among identical twins. We show that a stateoftheart automatic fingerprint identification system can successfully distinguish identical twins though with a slightly lower accuracy than nontwins. The implications of our results for various fingerprintbased identification systems are discussed.