Filterbank-Based Fingerprint Matching
2016-08-23
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With identity fraud in our society reaching unprecedented proportions and with an increasing emphasis on
the emerging automatic personal identification applications, biometrics-based verification, especially
fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings
of the traditional approaches to fingerprint representation. For a considerable fraction of population,
the representations based on explicit detection of complete ridge structures in the fingerprint are
difficult to extract automatically. The widely used minutiae-based representation does not utilize a
significant component of the rich discriminatory information available in the fingerprints. Local ridge
structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty
in quickly matching two fingerprint images containing different number of unregistered minutiae points.
T
the emerging automatic personal identification applications, biometrics-based verification, especially
fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings
of the traditional approaches to fingerprint representation. For a considerable fraction of population,
the representations based on explicit detection of complete ridge structures in the fingerprint are
difficult to extract automatically. The widely used minutiae-based representation does not utilize a
significant component of the rich discriminatory information available in the fingerprints. Local ridge
structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty
in quickly matching two fingerprint images containing different number of unregistered minutiae points.
T
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