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

Damer, Naser and Rhaibani, Chadi Izzou and Braun, Andreas and Kuijper, Arjan (2017):
Trust the biometrie mainstream: Multi-biometric fusion and score coherence.
In: 2017 25th European Signal Processing Conference (EUSIPCO), pp. 2191-2195,
IEEE, Kos, Greece, 28 Aug.-2 Sept. 2017, DOI: 10.23919/EUSIPCO.2017.8081598,
[Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Damer, Naser and Rhaibani, Chadi Izzou and Braun, Andreas and Kuijper, Arjan
Title: Trust the biometrie mainstream: Multi-biometric fusion and score coherence
Language: English
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.

Title of Book: 2017 25th European Signal Processing Conference (EUSIPCO)
Publisher: IEEE
Uncontrolled Keywords: Multibiometrics, Biometric fusion, Information fusion, CRISP
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Location: Kos, Greece
Event Dates: 28 Aug.-2 Sept. 2017
Date Deposited: 05 May 2020 14:41
DOI: 10.23919/EUSIPCO.2017.8081598
Official URL: https://doi.org/10.23919/EUSIPCO.2017.8081598
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