Abstract
Over the recent years, new public security tendency to fit up public areas with biometric devices has emerged new requirements in biometric recognition dealing with what we call here “mass biometry”. If the goal in “individual biometry” is to authenticate and/or identify an individual within a set of favored folks, the aim in “mass biometry” is to classify a suspect individual or behavior within a flow of mass customary information. In this case, the ability of handling relatively poor information and the skill of high speed processing become chief requirements. These antagonistic requests make the “mass biometry” and related applications among the most challenging frames. In this paper we present an ANN based system in a “mass biometry” context using facial biometric features. The proposed system takes advantage from kernel functions ANN model and IBM ZISC based hardware. Experimental results validating our system are presented and discussed.
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References
Faundez-Zanuy, M., Fabregas, J.: Testing report of a fingerprint-based door-opening system. IEEE Aerospace and Electronic Systems Magazine 20(6), 18–20 (2005)
Samborska, A.: Feature Space Reduction and Classification in Automatic Voice Quality Estimation. Image processing and Communication Journal, IP&C Journal (2006)
Carlos, M., Travieso-González, J.B., Alonso, S., David, M.A.: Ferrer-Ballester Optimization of a biometric system identification by hand geometry. In: Complex systems intelligence and modern technological applications, Cherbourg, France, pp. 581–586 (2004)
Valchuk, T., Wyrzykowski, R., Kompanets, L.: Mental Characteristics of Person as Basic Biometrics. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds.) ECCV 2002. LNCS, vol. 2359, pp. 78–90. Springer, Heidelberg (2002)
Kompanets, L.: Counterterrorism-Oriented Psychology and Biometrics Techniques Based on Brain Asymmetry, Eyes “Fingerprints”, Face Asymmetry and Person Psyche. In: Proc. of SCI 2003, Orlando, Florida, USA, July 2003, pp. 18–21 (2003)
Faundez-Zanuy, M.: Data fusion in biometrics. IEEE Aerospace and Electronic Systems Magazine 20(1), 34–38 (2005)
Reyneri, L.M.: Weighted Radial Basis Functions for Improved Pattern Recognition and Signal Processing. Neural Processing Let. 2(3), 2–6 (1995)
Haykin, S.: Neural nets, 2nd edn. A comprehensive foundation. Prentice Hall, Englewood Cliffs (1999)
Handbook of Brain Theory and Neural Networks, 2nd edn. MIT Press, Cambridge (2003)
ZISC/ISA ACCELERATOR card for PC, User Manual, IBM France (February 1995)
De Tremiolles, G.: Contribution to the theoretical study of neuro-mimetic models and to their experimental validation: a panel of industrial applications., Ph.D. Report, University of PARIS XII (in French) (March 1998)
Madani, K., De Tremiolles, G., Tanhoff, P.: Image processing using RBF like neural networks: A ZISC-036 based fully parallel implementation solving real world and real complexity industrial problems. Applied Intelligence (18), 195–231 (2003)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall, Englewood Cliffs (2002)
Zhao, W., Chellapa, R., Rozenfeld, A., Phillips, P.J.: Face recognition: A Literature Survey, Tech. Report, Univ. of Maryland (2003), http://www.cfar.umd.edu/ftp/TrsfaceSurvey.ps.gz
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Madani, K., Chebira, A., Amarger, V. (2009). A.N.N. Based Approach to Mass Biometry Taking Advantage from Modularity. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds) Bio-Inspired Systems: Computational and Ambient Intelligence. IWANN 2009. Lecture Notes in Computer Science, vol 5517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02478-8_164
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DOI: https://doi.org/10.1007/978-3-642-02478-8_164
Publisher Name: Springer, Berlin, Heidelberg
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