Filterbank-Based Fingerprint Matching
based matching has difficulty
in quickly matching two fingerprint images containing different number of unregistered minutiae points.
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.
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