Automatic identification methods based on physical biometric characteristics such as fingerprint or iris can provide positive identification 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 identification are distinctive. 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 identification system can successfully distinguish identical twins though with a slightly lower accuracy than nontwins. © Springer-Verlag Berlin Heidelberg 2001.
CITATION STYLE
Jain, A. K., Prabhakar, S., & Pankanti, S. (2001). Twin test: On discriminability of fingerprints. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2091 LNCS, pp. 211–217). Springer Verlag. https://doi.org/10.1007/3-540-45344-x_30
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