Visualization and Intelligent Systems Laboratory
VISLab

 

 

Contact Information

VISLab
Winston Chung Hall Room 216
University of California, Riverside
900 University Avenue
Riverside, CA 92521-0425


Tel: (951)-827-3954

CRIS
Bourns College of Engineering
UCR
NSF IGERT on Video Bioinformatics

UCR Collaborators:
CSE
ECE
ME
STAT
PSYC
ENTM
BIOL
BPSC
ECON
MATH
BIOENG
MGNT

Other Collaborators:
Keio University

Other Activities:
IEEE Biometrics Workshop 2014
IEEE Biometrics Workshop 2013
Worshop on DVSN 2009
Multibiometrics Book

Webmaster Contact Information:
Alex Shin
wshin@ece.ucr.edu

Last updated: July 1, 2017

 

 

Error Rate of Fingerprint Matching

Presented by: Xuejun Tan

ABSTRACT: Fingerprint has long been used for person authentication and people believe that every person's fingerprint is unique. However, there is not enough scientific research to explain what is the probability that two fingerprints, which are impressions of different fingers, may be taken as the same one. In this paper, we proposed a formal framework to estimate the error rate of fingerprint matching. Not like a previous work, which only takes into account of the positions of minutiae, in our model, we also take into account of the relations between different minutiae. The results of our work show that the error rate of fingerprint matching is not only decided by the number of minutiae in the template and query fingerprints and the uncertainty area of a minutia, but also the ridge counts between two different minutiae.
The comparison between the theoretical result and the real-data result, which uses NIST-4 fingerprint database, shows that it still needs much work on fingerprint matching in real-world applications, so that the performance of the existing fingerprint matching algorithm can be close to the theoretical result.