DocumentCode
2347674
Title
On the individuality fingerprints
Author
Pankanti, Sharath ; Prabhakar, Salil ; Jain, Anil K.
Author_Institution
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
Volume
1
fYear
2001
fDate
2001
Abstract
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 6.10×10-8. 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.
Keywords
fingerprint identification; image matching; image representation; probability; arbitrary fingerprints; automatic fingerprint matcher; court cases; false associations; fingerprint evidence; fingerprint identification; fingerprint image correspondence; fingerprint individuality; fingerprint matcher accuracy results; minutiae points; minutiae-based representations; non-minutiae based information; probability estimates; Anatomy; Cities and towns; Fingerprint recognition; Forensics; Friction; Laboratories; Pharmaceuticals; Skin; Testing; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
ISSN
1063-6919
Print_ISBN
0-7695-1272-0
Type
conf
DOI
10.1109/CVPR.2001.990563
Filename
990563
Link To Document