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Fingerprints from 61 pairs of male monozygotic twins (MZ), 47 pairs of female MZ, 40 pairs of same-sex male dizygotic twins (DZ), 44 pairs of same-sex female DZ, 4 pairs of opposite-sex DZ, and 28 brothers and 31 sisters of those twins are used for the study of fingerprint similarities. Similarities of fingerprint pattern, ridge count, and minutiae are evaluated for two population groups genetically related to each other in different degrees. It is concluded that fingerprint similarities, including pattern, ridge count, and possibly minutiae, between MZ individuals are significantly higher than those between other population groups, including DZ twins.

A method is developed for assigning a probability to a fingerprint, including a partial print, based on the number of individual (Galton) characteristics present. A multinomial model is used, the categories of which are the individual characteristics and combinations of them. The negative of the logarithm of the probability of any particular configuration is related to the entropy function of information theory. The parameters of the model are estimated from data (fingerprints). Confidence bounds are obtained for the negative log probability of any configuration.

A FORTRAN program has been written to compare the minutiae coded in an “unknown” fingerprint with the minutiae of fingerprints stored in a data base. The criteria for matching are scores based on the type and number of minutiae matched. Minutiae of low relative frequency have higher scoring weights than those that are more common. The matching mechanism is tested by using a fingerprint coded several times, first by a single individual and then by six other individuals who have no previous knowledge about fingerprints. These tests yield satisfactory results.

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