The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information.

Index Terms: Biometrics, FingerCode, fingerprints, flow pattern, Gabor filters, matching, texture, verification.

Features

  • Fingerprint matching
  • Implementation of 1D and 2D recursive Gabor filtering
  • Complex filtering techniques
  • 8 Gabor filters 0 22.5 45 67.5 90 112.5 135 157.5 degrees
  • Convolution is performed in frequency domain DataBase

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Additional Project Details

Programming Language

MATLAB

Related Categories

MATLAB Mathematics Software, MATLAB HMI Software, MATLAB Machine Learning Software

Registered

2015-03-16