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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Fronthaler, H., Kollreider, K., & Bigun, J. (2005). Local feature extraction in fingerprints by complex filtering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3781 LNCS, pp. 77–84). https://doi.org/10.1007/11569947_10
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