Abstract
In the present work, a new representation of fingerprints in form of geometric graph, is proposed. This representation is obtained by fusing two previously defined approaches found in the literature and proves to be very tolerant to occlusions and distortions in the minutiae. Also, a novel matching fingerprint algorithm that uses geometric graphs was introduced. The mentioned algorithm applies frequent geometric subgraph mining in order to match fingerprint representations for computing a final similarity score. The introduced proposal reports very promising accuracy values and it applies a new approach allowing many future improvements.
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Muñoz-Briseño, A., Gago-Alonso, A., Hernández-Palancar, J. (2015). Fingerprint Matching Using a Geometric Subgraph Mining Approach. In: Pardo, A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015. Lecture Notes in Computer Science(), vol 9423. Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_20
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DOI: https://doi.org/10.1007/978-3-319-25751-8_20
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