POLYBIO: Multimodal Biometric Data Acquisition Platform and Security System

Biometrics is the automated method of recognizing a person based on a physiological or behavioural characteristic. Biometric technologies are becoming the foundation of an extensive array of highly secure identification and personal verification solutions. In the last few years there is increasing evidence that technologies based on multimodal biometrics can provide better identification results if proper fusion schemes are accommodated. In this work, we present a novel platform for multimodal biometric acquisition which combines voice, video, fingerprint and palm photo acquisition through an integrated device, and the preliminary fusion experiments on combining the acquired biometrics modalities. The results are encouraging and show clear improvement both in terms of False Acceptance Rate and False Rejection Rates compared to the corresponding single modality approaches. In the current report, fusion was accommodated at the output of the single modalities; however, fusion experimentation is ongoing and further fusion methodologies are under investigation.

[1]  Arun Ross,et al.  Information fusion in biometrics , 2003, Pattern Recognit. Lett..

[2]  Arun Ross,et al.  Multibiometric systems , 2004, CACM.

[3]  F. Galton Personal Identification and Description , Nature.

[4]  Stefan Fischer,et al.  Expert Conciliation for Multi Modal Person Authentication Systems by Bayesian Statistics , 1997, AVBPA.

[5]  Jiri Matas,et al.  On Combining Classifiers , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Jr. J.P. Campbell,et al.  Speaker recognition: a tutorial , 1997, Proc. IEEE.

[7]  Arun Ross,et al.  Handbook of Multibiometrics , 2006, The Kluwer international series on biometrics.

[8]  Sharath Pankanti,et al.  On the individuality fingerprints , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[9]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[10]  Chuanyi Ji,et al.  Combinations of Weak Classifiers , 1996, NIPS.

[11]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[12]  H Hermansky,et al.  Perceptual linear predictive (PLP) analysis of speech. , 1990, The Journal of the Acoustical Society of America.

[13]  Josef Kittler,et al.  Audio- and Video-Based Biometric Person Authentication, 5th International Conference, AVBPA 2005, Hilton Rye Town, NY, USA, July 20-22, 2005, Proceedings , 2005, AVBPA.

[14]  Arun Ross,et al.  An introduction to multibiometrics , 2007, 2007 15th European Signal Processing Conference.

[15]  Benoit Geller,et al.  Blind estimation of timing and carrier frequency offsets in OFDM systems , 2007, 2009 17th European Signal Processing Conference.

[16]  Rama Chellappa,et al.  Fourier Coding of Image Boundaries , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  C. Collado,et al.  Miniaturization of superconducting filters using Hilbert fractal curves , 2005, IEEE Transactions on Applied Superconductivity.

[18]  R. P. Ramachandran,et al.  Robust speaker recognition: a feature-based approach , 1996, IEEE Signal Processing Magazine.

[19]  Roberto Brunelli,et al.  Person identification using multiple cues , 1995, IEEE Transactions on Pattern Analysis and Machine Intelligence.