Advances in fingerprint modeling
Image and Vision Computing
High resolution partial fingerprint alignment using pore-valley descriptors
Pattern Recognition
A novel matching algorithm for distorted fingerprints based on penalized quadratic model
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Data acquisition and processing of 3-D fingerprints
IEEE Transactions on Information Forensics and Security
An effective biometric cryptosystem combining fingerprints with error correction codes
Expert Systems with Applications: An International Journal
Fake finger detection based on thin-plate spline distortion model
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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Coping with nonlinear distortions in fingerprint matching is a challenging task. This paper proposes a novel method, a fuzzy feature match (FFM) based on a local triangle feature set to match the deformed fingerprints. The fingerprint is represented by the fuzzy feature set: the local triangle feature set. The similarity between the fuzzy feature set is used to characterize the similarity between fingerprints. A fuzzy similarity measure for two triangles is introduced and extended to construct a similarity vector including the triangle-level similarities for all triangles in two fingerprints. Accordingly, a similarity vector pair is defined to illustrate the similarities between two fingerprints. The FFM method maps the similarity vector pair to a normalized value which quantifies the overall image to image similarity. The proposed algorithm has been evaluated with NIST 24 and FVC2004 fingerprint databases. Experimental results confirm that the proposed FFM based on the local triangle feature set is a reliable and effective algorithm for fingerprint matching with nonlinear distortions.