Abstract
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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Fronthaler, H., Kollreider, K., Bigun, J. (2005). Local Feature Extraction in Fingerprints by Complex Filtering. In: Li, S.Z., Sun, Z., Tan, T., Pankanti, S., Chollet, G., Zhang, D. (eds) Advances in Biometric Person Authentication. IWBRS 2005. Lecture Notes in Computer Science, vol 3781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11569947_10
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DOI: https://doi.org/10.1007/11569947_10
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