On the individuality fingerprints

By Sharath Pankanti, Salil Prabhakar, Anil K. Jain. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001

713 citations recorded by the source corpus.

Fingerprint identification is based on two basic premises: (i) persistence: the basic characteristics of fingerprints do not change with time; and (ii) individuality: the fingerprint is unique to an individual. The validity of the first premise has been established. While the second premise is generally accepted to be true, the underlying scientific basis of fingerprint individuality has not been formally tested. We address the problem of fingerprint individuality by quantifying the amount of information available in minutiae points to establish a correspondence between two fingerprint images. We derive an expression which estimates the probability of falsely associating minutiae-based representations from two arbitrary fingerprints. 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/spl times/10/sup -8/. These probability estimates are compared with typical fingerprint matcher accuracy results. Our results show that: (i) fingerprint matching is not infallible and leads to some false associations, (ii) the performance of automatic fingerprint matcher does not even come close to the theoretical performance, and (iii) due to the limited information content of the minutiae-based representation, automatic system designers should explore the use of non-minutiae-based information present in the fingerprints.

Subfields: Genetics, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/ab66662067ecbac9674c1f5d738a33612e82d5ce

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Citations in the corpus

Fingerprint classification: a review (2004, background): “The uniqueness of fingerprints has been studied and it is well established that the probability of two fingerprints matching is vanishingly small [2, 3].”
Biometrics: a grand challenge (2004, background): “For example, the individuality information contained in minutia-based representation of fingerprints is shown in [10].”
Biometrics: a tool for information security (2006, methodology): “[14] where is the probability of two position-matched minutiae having similar orientation, and is assumed to be an integer (since ).”
Pores and Ridges: High-Resolution Fingerprint Matching Using Level 3 Features (2007, methodology): “The threshold t 2 is chosen based on the 12-point guideline that is considered as sufficient evidence for making positive identification in many courts of law [5].”
A Fingerprint Orientation Model Based on 2D Fourier Expansion (FOMFE) and Its Application to Singular-Point Detection and Fingerprint Indexing (2007, background): “Although commercial FVS products have been available on the market, the performance of current FISs on large databases is not yet satisfactory [3], [4].”
Combining minutiae descriptors for fingerprint matching (2008, methodology): “D feature vector from the matching result, and convert the feature vector into a matching score using support vector classifier.”
Fingerprint recognition by combining global structure and local cues (2006, methodology): “Second, to analyze the individuality of fingerprints, Pankanti et al. [7] proposed a mathematical model based on minutiae points with the assumption that minutiae points are independent.”
A hybrid fingerprint matcher (2002, background): “Although not scientifically established, fingerprints are believed to be unique across individuals, and across fingers of the same individual [4].”
FVC2002: Second Fingerprint Verification Competition (2002, background): “[1]. FVC2000 received great attention from both academic and commercial organizations; on the one hand, it established a common benchmark, allowing system developers to unambiguously compare their algorithms, on the other it provided the first overview of the state-ofthe-art in fingerprint recogniti”
Guide to Biometrics (2003, background): “Given a representation seheme and a sirnilarity metrie, there are two approaehes to deterrnining the individuality of the fingerprints: theoretieal and empirie al [158].”
Biometric cryptosystems: issues and challenges (2004, background): “minutiae dispersion to be conservatively pixels [28] for prealigned mated fingerprints.”