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Weighted Integration of Neighbors Distance Ratio in Multi-biometric Fusion

Damer, Naser ; Nouak, Alexander (2015)
Weighted Integration of Neighbors Distance Ratio in Multi-biometric Fusion.
BIOSIG 2015.
doi: 10.1109/BIOSIG.2015.7314624
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

This work presents an approach to integrate biometric source weighting in the calculation of neighbors distance ratios to be used within a classification-based multi-biometric fusion process. The neighbors distance ratio represents the elevation of the top ranked identification match to the following ranks. Using biometric source weighing can help achieve more accurate initial identity ranking necessary for neighbors distance ratios. It also influences the effect of each biometric source on the ratios values. The proposed approach is developed and evaluated using the Biometric Scores Set BSSR1 database. The results are presented in the verification scenario as receiver operating curves (ROC). The achieved performance is compared to a number of baseline solutions and a satisfying and stable performance was achieved with a clear benefit of integrating the biometric source weights.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2015
Autor(en): Damer, Naser ; Nouak, Alexander
Art des Eintrags: Bibliographie
Titel: Weighted Integration of Neighbors Distance Ratio in Multi-biometric Fusion
Sprache: Englisch
Publikationsjahr: 2015
Verlag: Köllen, Bonn
Reihe: GI-Edition - Lecture Notes in Informatics (LNI); P-245
Veranstaltungstitel: BIOSIG 2015
DOI: 10.1109/BIOSIG.2015.7314624
Kurzbeschreibung (Abstract):

This work presents an approach to integrate biometric source weighting in the calculation of neighbors distance ratios to be used within a classification-based multi-biometric fusion process. The neighbors distance ratio represents the elevation of the top ranked identification match to the following ranks. Using biometric source weighing can help achieve more accurate initial identity ranking necessary for neighbors distance ratios. It also influences the effect of each biometric source on the ratios values. The proposed approach is developed and evaluated using the Biometric Scores Set BSSR1 database. The results are presented in the verification scenario as receiver operating curves (ROC). The achieved performance is compared to a number of baseline solutions and a satisfying and stable performance was achieved with a clear benefit of integrating the biometric source weights.

Freie Schlagworte: Business Field: Visual decision support, Research Area: Computer vision (CV), Research Area: Human computer interaction (HCI), Multibiometrics, Biometric fusion, Information fusion, Databases, Measurements, Neural networks, CRISP
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 08 Mai 2019 08:05
Letzte Änderung: 08 Mai 2019 08:05
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