The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Statistical Fingerprint Recognition Matching Method with an Optimal Threshold and Confidence Interval

  • Hong, C.S. (Department of Statistics, Sungkyunkwan University) ;
  • Kim, C.H. (Research Institute of Applied Statistics, Sungkyunkwan University)
  • Received : 2012.10.08
  • Accepted : 2012.11.14
  • Published : 2012.12.31
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Abstract

Among various biometrics recognition systems, statistical fingerprint recognition matching methods are considered using minutiae on fingerprints. We define similarity distance measures based on the coordinate and angle of the minutiae, and suggest a fingerprint recognition model following statistical distributions. We could obtain confidence intervals of similarity distance for the same and different persons, and optimal thresholds to minimize two kinds of error rates for distance distributions. It is found that the two confidence intervals of the same and different persons are not overlapped and that the optimal threshold locates between two confidence intervals. Hence an alternative statistical matching method can be suggested by using nonoverlapped confidence intervals and optimal thresholds obtained from the distributions of similarity distances.

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References

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