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EnglishTo make automatic fingerprint identification systems (AFIS) capable of searching across several millions of fingerprints in a few seconds, very powerful (and expensive) distributed computing architectures are typically used. The recent improvement of algorithms and the availability of powerful CPUs and GPUs makes it now possible to deploy large scale fingerprint recognition on low-cost hardware, thus approaching a larger number of applications (e.g., welfare benefits in poor countries). This chapter discusses architectural design, algorithms and hardware optimization to speed-up fingerprint recognition on large databases.
| Titolo: | Large scale fingerprint recognition accelerated in hardware | |
| Autore/i: | Raffaele Cappelli; Matteo Ferrara; Davide Maltoni | |
| Autore/i Unibo: | ||
| Anno: | 2018 | |
| Titolo del libro: | Hand-Based Biometrics: Methods and technology | |
| Pagina iniziale: | 111 | |
| Pagina finale: | 133 | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1049/PBSE008E_ch6 | |
| Abstract: | To make automatic fingerprint identification systems (AFIS) capable of searching across several millions of fingerprints in a few seconds, very powerful (and expensive) distributed computing architectures are typically used. The recent improvement of algorithms and the availability of powerful CPUs and GPUs makes it now possible to deploy large scale fingerprint recognition on low-cost hardware, thus approaching a larger number of applications (e.g., welfare benefits in poor countries). This chapter discusses architectural design, algorithms and hardware optimization to speed-up fingerprint recognition on large databases. | |
| Data stato definitivo: | 6-feb-2018 | |
| Appare nelle tipologie: | 2.01 Capitolo / saggio in libro |
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http://hdl.handle.net/11585/619576
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