Fast fingerprint identification for large databases
A two-level parallel AFIS is proposed to deal with large databases. It makes possible to perform pattern identifications in arbitrarily large databases. The framework is flexible for any kind of databases, and any matching algorithm. The achieved speedup is nearly linear. The framework performs 400000 matchings in 0.5s, with no precision loss.
large databases distributed computing minutiae matching parallel computing real-time fingerprint identification