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Trust the biometrie mainstream: Multi-biometric fusion and score coherence

Damer, Naser ; Rhaibani, Chadi Izzou ; Braun, Andreas ; Kuijper, Arjan (2017)
Trust the biometrie mainstream: Multi-biometric fusion and score coherence.
Kos, Greece (28 Aug.-2 Sept. 2017)
doi: 10.23919/EUSIPCO.2017.8081598
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Multi-biometrics aims at building more accurate unified biometric decisions based on the information provided by multiple biometric sources. Information fusion is used to optimize the process of creating this unified decision. In previous works dealing with score-level multi-biometric fusion, the scores of different biometric sources belonging to the comparison of interest are used to create the fused score. This is usually achieved by assigning static weights for the different biometric sources with more advanced solutions considering supplementary dynamic information like sample quality and neighbours distance ratio. This work proposes embedding score coherence information in the fusion process. This is based on our assumption that a minority of biometric sources, which points out towards a different decision than the majority, might have faulty conclusions and should be given relatively smaller role in the final decision. The evaluation was performed on the BioSecure multimodal biometric database with different levels of simulated noise. The proposed solution incorporates, and was compared to, three baseline static weighting approaches. The enhanced performance induced by including the coherence information within a dynamic weighting scheme in comparison to the baseline solution was shown by the reduction of the equal error rate by 45% to 85% over the different test scenarios and proved to maintain high performance when dealing with noisy data.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2017
Autor(en): Damer, Naser ; Rhaibani, Chadi Izzou ; Braun, Andreas ; Kuijper, Arjan
Art des Eintrags: Bibliographie
Titel: Trust the biometrie mainstream: Multi-biometric fusion and score coherence
Sprache: Englisch
Publikationsjahr: 2017
Verlag: IEEE
Buchtitel: 2017 25th European Signal Processing Conference (EUSIPCO)
Veranstaltungsort: Kos, Greece
Veranstaltungsdatum: 28 Aug.-2 Sept. 2017
DOI: 10.23919/EUSIPCO.2017.8081598
URL / URN: https://doi.org/10.23919/EUSIPCO.2017.8081598
Kurzbeschreibung (Abstract):

Multi-biometrics aims at building more accurate unified biometric decisions based on the information provided by multiple biometric sources. Information fusion is used to optimize the process of creating this unified decision. In previous works dealing with score-level multi-biometric fusion, the scores of different biometric sources belonging to the comparison of interest are used to create the fused score. This is usually achieved by assigning static weights for the different biometric sources with more advanced solutions considering supplementary dynamic information like sample quality and neighbours distance ratio. This work proposes embedding score coherence information in the fusion process. This is based on our assumption that a minority of biometric sources, which points out towards a different decision than the majority, might have faulty conclusions and should be given relatively smaller role in the final decision. The evaluation was performed on the BioSecure multimodal biometric database with different levels of simulated noise. The proposed solution incorporates, and was compared to, three baseline static weighting approaches. The enhanced performance induced by including the coherence information within a dynamic weighting scheme in comparison to the baseline solution was shown by the reduction of the equal error rate by 45% to 85% over the different test scenarios and proved to maintain high performance when dealing with noisy data.

Freie Schlagworte: Multibiometrics, Biometric fusion, Information fusion, CRISP
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing
Hinterlegungsdatum: 05 Mai 2020 14:41
Letzte Änderung: 05 Mai 2020 14:41
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