Local Feature Extraction in Fingerprints by Complex Filtering | Zendy

H. Fronthaler | Zendy; K. Kollreider | Zendy; Josef Bigün | Zendy

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Local Feature Extraction in Fingerprints by Complex Filtering

Author(s) -

H. Fronthaler,

K. Kollreider,

Josef Bigün

Publication year - 2005

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-29431-7

DOI - 10.1007/11569947_10

Subject(s) - computer science , minutiae , fingerprint (computing) , ridge , artificial intelligence , pattern recognition (psychology) , orientation (vector space) , feature (linguistics) , feature extraction , tensor (intrinsic definition) , set (abstract data type) , fingerprint recognition , computer vision , mathematics , geometry , linguistics , philosophy , paleontology , biology , programming language

A set of local feature descriptors for fingerprints is proposed. Minutia points are detected in a novel way by complex filtering of the structure tensor, not only revealing their position but also their direction. Parabolic and linear symmetry descriptions are used to model and extract local features including ridge orientation and reliability, which can be reused in several stages of fingerprint processing. Experimental results on the proposed technique are presented.

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