Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
FVC2000: Fingerprint Verification Competition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Matching Using Feature Space Correlation
ECCV '02 Proceedings of the International ECCV 2002 Workshop Copenhagen on Biometric Authentication
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
FVC2002: Second Fingerprint Verification Competition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
A New Correlation Criterion Based on Gradient Fields Similarity
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Biometric Systems: Technology, Design and Performance Evaluation
Biometric Systems: Technology, Design and Performance Evaluation
Fingerprint Matching With Rotation-Descriptor Texture Features
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Pores and Ridges: Fingerprint Matching Using Level 3 Features
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
The surround Imager™: a multi-camera touchless device to acquire 3d rolled-equivalent fingerprints
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A method for fingerprint alignment and matching
Proceedings of the 10th International Conference on Advances in Mobile Computing & Multimedia
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Correlation-based techniques are a promising approach to fingerprint matching for the new generation of high resolution and touchless fingerprint sensors, since they can match ridge shapes, breaks, etc. However, a major drawback of these techniques is the high computational effort required. In this paper a coarse alignment step is proposed which reduces the amount of correlations that should be performed. Contrarily to other alignment approaches based on minutiae or core location, the alignment is based on the orientation field estimations. Also the orientation coherence is used to identify the best areas for correlation. The accuracy of the approach is demonstrated by experimental results with an FVC2000 fingerprint database. The approach is also very well suited for hardware acceleration due to the regularity of the used operations.