On the Individuality of Fingerprints

  • Authors:

  • Sharath Pankanti;Salil Prabhakar;Anil K. Jain

  • Affiliations:

  • IBM T.J. Watson Research Center, Yorktown Heights, NY;DigitalPersona Inc., 805 Veterans Blvd., #301, Redwood City,CA;Department of Computer Science and Engineering, Michigan State University, East lansing, MI

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 2002

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Abstract

Fingerprint identification is based on two basic premises: 1) persistence: the basic characteristics of fingerprints do not change with time and 2) individuality: the fingerprint is unique to an individual. The validity of the first premise has been established by the anatomy and morphogenesis of friction ridge skin. While the second premise has been generally accepted to be true based on empirical results, the underlying scientific basis of fingerprint individuality has not been formally established. As a result, the validity of fingerprint evidence is now being challenged in several court cases. A scientific basis for establishing fingerprint individuality will not only result in the admissibility of fingerprint identification in the courts of law, but will also establish an upper bound on the performance of an automatic fingerprint verification system. We address the problem of fingerprint individuality by quantifying the amount of information available in minutiae features to establish a correspondence between two fingerprint images. We derive an expression which estimates the probability of a false correspondence between minutiae-based representations from two arbitrary fingerprints belonging to different fingers. For example, the probability that a fingerprint with 36 minutiae points will share 12 minutiae points with another arbitrarily chosen fingerprint with 36 minutiae points is 6.10\times 10^{-8}. These probability estimates are compared with typical fingerprint matcher accuracy results. Our results show that 1) contrary to the popular belief, fingerprint matching is not infallible and leads to some false associations, 2) while there is an overwhelming amount of discriminatory information present in the fingerprints, the strength of the evidence degrades drastically with noise in the sensed fingerprint images, 3) the performance of the state-of-the-art automatic fingerprint matchers is not even close to the theoretical limit, and 4) because automatic fingerprint verification systems based on minutia use only a part of the discriminatory information present in the fingerprints, it may be desirable to explore additional complementary representations of fingerprints for automatic matching.