On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast and Accurate Fingerprint Verification
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
A Minutia Matching Algorithm in Fingerprint Verification
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Fingerprint Matching Using an Orientation-Based Minutia Descriptor
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint minutiae matching using the adjacent feature vector
Pattern Recognition Letters
Performance Evaluation of Fingerprint Verification Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint matching combining the global orientation field with minutia
Pattern Recognition Letters
Fingerprint matching using ridges
Pattern Recognition
Fingerprint matching by genetic algorithms
Pattern Recognition
Fingerprint matching using OrientationCodes and PolyLines
Pattern Recognition
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
Computer
Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Developing accurate fingerprint verification algorithms is an active research area. A large amount of fingerprint verification algorithms are based on minutiae descriptors. An important component of these algorithms is the alignment strategy. The single alignment strategy, with O(n2) time complexity, uses the local matching minutiae pair that maximizes the similarity value to align the minutiae. Nevertheless, even if the selected minutiae pair is a true matching pair, it is not necessarily the best pair to carry out fingerprint alignment. The multiple alignments strategy alleviates these limitations by performing multiple minutiae alignments, increasing the time complexity to O(n4). In this paper, we improve the multiple alignment strategy, reducing its complexity while still achieving a high accuracy. The new strategy is based on the rationale that most minutiae descriptors from one fingerprint correspond with their most similar descriptors from the other fingerprint. To test the new strategy behavior, we adapt three well known algorithms to a traditional multiple alignment strategy and to our strategy. Several experiments in the FVC2004 database show that our strategy outperforms both the single and the multiple alignments strategies.