Abstract
This work presents a family of novel normalization techniques for score-level multi-biometric fusion. The proposed normalization is not only concerned to bring comparison scores to a common range and scale, it also focuses in bringing certain operational performance points in the distribution into alignment. The Performance Anchored Normalization (PAN) algorithms discussed here were tested on the extended Multi Modal Verification for Teleservices and Security applications database (XM2VTS) and proved to outperform conventional score normalization techniques in most tests. The tests were performed with combination fusion rules and presented as biometric verification performance measures.
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References
Damer, N., Opel, A., Shahverdyan, A.: An Overview on Multi-biometric Score-level Fusion: Verification and Identification. In: Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods, pp. 647–653. SciTePress, Lynnfield (2013)
Jain, A., Nandakumar, K., Ross, A.: Score normalization in multimodal biometric systems. Pattern Recognition 38, 2270–2285 (2005)
Snelick, R., Uludag, U., Mink, A., Indovina, M., Jain, A.: Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 450–455 (2005)
Singh, Y.N., Gupta, P.: Quantitative evaluation of normalization techniques of matching scores in multimodal biometric systems. In: Lee, S.-W., Li, S.Z. (eds.) ICB 2007. LNCS, vol. 4642, pp. 574–583. Springer, Heidelberg (2007)
Poh, N., Bengio, S.: Database, protocol and tools for evaluating score-level fusion algorithms in biometric authentication. Idiap-RR Idiap-RR-44-2004, IDIAP (2004)
Srinivas, N., Veeramachaneni, K., Osadciw, L.: Fusing correlated data from multiple classifiers for improved biometric verification. In: 12th International Conference on Information Fusion, FUSION 2009, pp. 1504–1511 (2009)
Vajaria, H., Islam, T., Mohanty, P., Sarkar, S., Sankar, R., Kasturi, R.: Evaluation and analysis of a face and voice outdoor multi-biometric system. Pattern Recogn. Lett. 28, 1572–1580 (2007)
Cappelli, R., Maio, D., Maltoni, D.: Combining fingerprint classifiers. In: Kittler, J., Roli, F. (eds.) MCS 2000. LNCS, vol. 1857, pp. 351–361. Springer, Heidelberg (2000)
Hampel, F., Ronchetti, E., Rousseeuw, P., Stahel, W.: Robust statistics: the approach based on influence functions. Wiley series in probability and mathematical statistics. Wiley (2005)
Chang, K.I., Bowyer, K.W., Flynn, P.J., Chen, X.: Multi-biometrics using facial appearance, shape and temperature. In: Proceedings of the Sixth IEEE International Conference on Automatic Face and Gesture Recognition, FGR 2004, pp. 43–48. IEEE Computer Society, Washington, DC (2004)
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Damer, N., Opel, A., Nouak, A. (2013). Performance Anchored Score Normalization for Multi-biometric Fusion. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2013. Lecture Notes in Computer Science, vol 8034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41939-3_7
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DOI: https://doi.org/10.1007/978-3-642-41939-3_7
Publisher Name: Springer, Berlin, Heidelberg
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