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Filterbank-Based Fingerprint Matching 5.3

We have developed a novel, hybrid technique for core point detection.


Last Week downloads: 0
Total downloads: 1,015
  • Last Updated: Dec 9, 2008
  • License: Shareware €30.00
  • OS: Windows XP/2000/98/Me/NT
  • Requirements: No special requirements

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3 out of 5 based on 2 ratings for Filterbank-Based Fingerprint Matching 5.3

For Filterbank-Based Fingerprint Matching 5.3Publisher's description


Filterbank-Based Fingerprint Matching is a Home & Education software developed by Luigi Rosa. After our trial and test, the software is proved to be official, secure and free. Here is the official description for Filterbank-Based Fingerprint Matching:

EditByBSEditor: 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. 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.

The localization of core point represents the most critical step of the whole process.
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