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EnglishThis paper proposes a novel fingerprint retrieval system that combines level-1 (local orientation and frequencies) and level-2 (minutiae) features. Various score- and rank-level fusion strategies and a novel hybrid fusion approach are evaluated. Extensive experiments are carried out on six public databases and a systematic comparison is made with eighteen retrieval methods and seventeen exclusive classification techniques published in the literature. The novel approach achieves impressive results: its retrieval accuracy is definitely higher than competing state-of-the-art methods, with error rates that in some cases are even one or two orders of magnitude smaller.
| Titolo: | A Fingerprint Retrieval System Based on Level-1 and Level-2 Features | |
| Autore/i: | CAPPELLI, RAFFAELE; FERRARA, MATTEO | |
| Autore/i Unibo: | ||
| Anno: | 2012 | |
| Rivista: | ||
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1016/j.eswa.2012.02.064 | |
| Abstract: | This paper proposes a novel fingerprint retrieval system that combines level-1 (local orientation and frequencies) and level-2 (minutiae) features. Various score- and rank-level fusion strategies and a novel hybrid fusion approach are evaluated. Extensive experiments are carried out on six public databases and a systematic comparison is made with eighteen retrieval methods and seventeen exclusive classification techniques published in the literature. The novel approach achieves impressive results: its retrieval accuracy is definitely higher than competing state-of-the-art methods, with error rates that in some cases are even one or two orders of magnitude smaller. | |
| Data prodotto definitivo in UGOV: | 2013-05-06 21:55:29 | |
| Appare nelle tipologie: | 1.01 Articolo in rivista |
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http://hdl.handle.net/11585/117123
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