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Service-oriented architecture based on biometric using random features and incremental neural networks

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Abstract

We propose a service-oriented architecture based on biometric system where training and classification tasks are used by millions of users via internet connection. Such a large-scale biometric system needs to consider template protection, accuracy and efficiency issues. This is a challenging problem since there are tradeoffs among these three issues. In order to simultaneously handle these issues, we extract both global and local features via controlling the sparsity of random bases without training. Subsequently, the extracted features are fused with a sequential classifier. In the proposed system, the random basis features are not stored for security reason. The non-training based on feature extraction followed by a sequential learning contributes to computational efficiency. The overall accuracy is consequently improved via an ensemble of classifiers. We evaluate the performance of the proposed system using equal error rate under a stolen-token scenario. Our experimental results show that the proposed method is robust over severe local deformation with efficient computation for simultaneous transactions. Although we focus on face biometrics in this paper, the proposed method is generic and can be applied to other biometric traits.

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Acknowledgments

This research was supported by MKE, Korea under ITRC NIPA-2012-(C1090-1221-0008) and this research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2009-0067625).

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Authors and Affiliations

  1. Department of Computer Science, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul, 120-749, Korea

    Kwontaeg Choi, Youngjung Uh & Hyeran Byun

  2. School of Electrical and Electronic Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul, 120-749, Korea

    Kar-Ann Toh

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  1. Kwontaeg Choi
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  2. Kar-Ann Toh
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  3. Youngjung Uh
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  4. Hyeran Byun
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Correspondence to Hyeran Byun.

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Choi, K., Toh, KA., Uh, Y. et al. Service-oriented architecture based on biometric using random features and incremental neural networks. Soft Comput 16, 1539–1553 (2012). https://doi.org/10.1007/s00500-012-0827-3

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