Journal ArticleDOI
Likelihood Ratio-Based Biometric Score Fusion
TLDR
Experiments on three multibiometric databases indicate that the proposed fusion framework achieves consistently high performance compared to commonly used score fusion techniques based on score transformation and classification.Abstract:
Multibiometric systems fuse information from different sources to compensate for the limitations in performance of individual matchers. We propose a framework for the optimal combination of match scores that is based on the likelihood ratio test. The distributions of genuine and impostor match scores are modeled as finite Gaussian mixture model. The proposed fusion approach is general in its ability to handle 1) discrete values in biometric match score distributions, 2) arbitrary scales and distributions of match scores, 3) correlation between the scores of multiple matchers, and 4) sample quality of multiple biometric sources. Experiments on three multibiometric databases indicate that the proposed fusion framework achieves consistently high performance compared to commonly used score fusion techniques based on score transformation and classification.read more
Citations
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Journal ArticleDOI
Multimodal Biometric Fusion: Performance under Spoof Attacks
TL;DR: Investigation of the performance of serial and parallel biometric fusion modes under realistic spoof attacks confirms that multimodal biometric systems in both fusion modes are not intrinsically robust against spoof attacks as believed so far, and experimentally finds that incorporating the biometric sample quality inBiometric fusion increases the robustness of the multi-million dollar systems under spoof attacks.
Secure Multibiometric Systems
TL;DR: This thesis proposes a novel liveness detection algorithm which combines perspirationand morphology-based static features and demonstrates that, by incorporating the proposed algorithm in the fusion scheme, the multimodal system results robust in presence of spoof attacks.
Journal Article
Research Avenues in Multimodal Biometrics
G. Hemantha Kumar,Mohammad Imran +1 more
TL;DR: A brief overview of multimodal biometrics and its advantages, challenges, drawbacks and limitations is given.
Journal ArticleDOI
Hierarchical fusion network for periocular and iris by neural network approximation and sparse autoencoder
TL;DR: A hierarchical fusion network is proposed to fuse multiple fusion approaches from transformation-based and classification-based categories into a unified framework for classification and demonstrates the effectiveness of the proposed hierarchical fusion approach for periocular and iris modalities.
Proceedings ArticleDOI
Heterogeneous sharpness for cross-spectral face recognition
Zhicheng Cao,Natalia A. Schmid +1 more
TL;DR: A generalized definition of sharpness is proposed by first achieving image quality parity and then finding and building a relationship between the image quality of two heterogeneous images and the new sharpness metric is named heterogeneous sharpness.
References
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Journal ArticleDOI
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