Performance Anchored Score Normalization for Multi-biometric Fusion

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.

[1]  Naser Damer,et al.  An Overview on Multi-biometric Score-level Fusion - Verification and Identification , 2013, ICPRAM.

[2]  Sudeep Sarkar,et al.  Evaluation and analysis of a face and voice outdoor multi-biometric system , 2007, Pattern Recognit. Lett..

[3]  Jon Atli Benediktsson,et al.  Multiple Classifier Systems , 2015, Lecture Notes in Computer Science.

[4]  Stan Z. Li,et al.  Advances in Biometrics, International Conference, ICB 2007, Seoul, Korea, August 27-29, 2007, Proceedings , 2007, ICB.

[5]  Anil K. Jain,et al.  Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Kalyan Veeramachaneni,et al.  Fusing correlated data from multiple classifiers for improved biometric verification , 2009, 2009 12th International Conference on Information Fusion.

[7]  Dario Maio,et al.  Combining Fingerprint Classifiers , 2000, Multiple Classifier Systems.

[8]  Arun Ross,et al.  Score normalization in multimodal biometric systems , 2005, Pattern Recognit..

[9]  Phalguni Gupta,et al.  Quantitative Evaluation of Normalization Techniques of Matching Scores in Multimodal Biometric Systems , 2007, ICB.

[10]  P. Rousseeuw,et al.  Wiley Series in Probability and Mathematical Statistics , 2005 .

[11]  Werner A. Stahel,et al.  Robust Statistics: The Approach Based on Influence Functions , 1987 .

[12]  Xin Chen,et al.  Multi-biometrics using facial appearance, shape and temperature , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[13]  Samy Bengio,et al.  Database, protocols and tools for evaluating score-level fusion algorithms in biometric authentication , 2006, Pattern Recognit..