TY - GEN
T1 - A low cost incremental biometric fusion strategy for a handheld device
AU - Allano, Lorene
AU - Garcia-Salicetti, Sonia
AU - Dorizzi, Bernadette
PY - 2008/12/1
Y1 - 2008/12/1
N2 - In this paper, we present some results on multimodality implementation resulting from the VINSI ("Vérification d'Identité Numérique Sécurisée Itinérante" for Secured Mobile Digital Identity Verification) French project. The VINSI handheld terminal allows identity verification in mobile conditions (airport gates) using two biometrics usable in future biometric passports (fingerprint and face). We propose an incremental fusion strategy aiming at improving the global performance of the combined system over each individual recognizer while optimizing the cost resulting from the fusion. Indeed, in this kind of application, time and complexity optimization is essential. To this aim, we split the fingerprint scores' range into different interest zones, on which we do not apply the same strategy depending on the relative quality of the modalities at hand. Results on a virtual database corresponding to VINSI applicative conditions (Combination of BIOMET fingerprints and FRGCv2 faces) show that this incremental fusion strategy allows the same improvement in performance as global fusion methods while significantly reducing the cost.
AB - In this paper, we present some results on multimodality implementation resulting from the VINSI ("Vérification d'Identité Numérique Sécurisée Itinérante" for Secured Mobile Digital Identity Verification) French project. The VINSI handheld terminal allows identity verification in mobile conditions (airport gates) using two biometrics usable in future biometric passports (fingerprint and face). We propose an incremental fusion strategy aiming at improving the global performance of the combined system over each individual recognizer while optimizing the cost resulting from the fusion. Indeed, in this kind of application, time and complexity optimization is essential. To this aim, we split the fingerprint scores' range into different interest zones, on which we do not apply the same strategy depending on the relative quality of the modalities at hand. Results on a virtual database corresponding to VINSI applicative conditions (Combination of BIOMET fingerprints and FRGCv2 faces) show that this incremental fusion strategy allows the same improvement in performance as global fusion methods while significantly reducing the cost.
KW - Biometrics
KW - Cost optimization
KW - Face
KW - Fingerprint
KW - Fusion
KW - Handheld device
KW - Incremental strategy
KW - Multiple classifiers system
UR - https://www.scopus.com/pages/publications/58349120653
U2 - 10.1007/978-3-540-89689-0_88
DO - 10.1007/978-3-540-89689-0_88
M3 - Conference contribution
AN - SCOPUS:58349120653
SN - 3540896880
SN - 9783540896883
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 842
EP - 851
BT - Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2008, Proceedings
T2 - Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, SSPR and SPR 2008
Y2 - 4 December 2008 through 6 December 2008
ER -