Multibiometric systems can solve a number of problems of unimodal approaches. One source for such problems can be found in the lack of dynamic update of parameters, which does not allow current systems to adapt to changes in the working settings. They are generally calibrated once and for all, so that they are tuned and optimized with respect to standard conditions. In this work we propose an architecture where, for each single-biometry subsystem, parameters are dynamically optimized according to the behaviour of all the others. This is achieved by an additional component, the supervisor module, which analyzes the responses from all subsystems and modifies the degree of reliability required from each of them to accept the respective responses. The paper explores two integration architectures with different interconnection degree, demonstrating that a tight component interaction increases system accuracy and allows identifying unstable subsystems.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
|Titolo:||Multibiometric People Identification: A Self-Tuning Architecture.|
|Data di pubblicazione:||2009|
|Citazione:||Multibiometric People Identification: A Self-Tuning Architecture. / DE MARSICO, Maria; Nappi, M; Riccio, D.. - STAMPA. - 5558(2009), pp. 980-989. ((Intervento presentato al convegno 3rd IAPR/IEEE International Conference on Biometrics, ICB 2009 tenutosi a Sassari, Italy nel 2-5 giugno 2009.|
|Appare nella tipologia:||04b Atto di convegno in volume|