Secure Biometric Verification Station Based on Iris Recognition

• Autorzy: Czajka A. , Piech K.
• Języki publikacji: EN

Abstrakty

EN

This paper describes an application of the Zak-Gabor-based iris coding to build a secure biometric verification station (SBS), consisting of a professional iris capture camera, a processing unit with specially designed iris recognition and communication software, as well as a display (LCD). Specially designed protocol controls the access to the station and secures the communication between the station and the external world. Reliability of the Zak-Gabor-based coding, similarly to other wavelet-based methods, strongly depends on appropriate choice of the wavelets employed in image coding. This choice cannot be arbitrary and should be adequate to the employed iris image quality. Thus in this paper we propose an automatic iris feature selection mechanism employing, among others, the minimum redundancy, maximum relevance (mRMR) methodology as one, yet important, step to assess the optimal set of wavelets used in this iris recognition application. System reliability is assessed with approximately 1000 iris images collected by the station for 50 different eyes.

Słowa kluczowe

EN

feature selection; application of biometrics; iris recognition; Zak-Gabor-based iris coding

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2012
• Tom: nr 3
• Strony: 40--49
• Opis fizyczny: Bibliogr. 9 poz., rys.

Twórcy

autor

Czajka A.

autor

Piech K.

• Research and Academic Computer Network (NASK), Wąwozowa st 18, 02-796 Warsaw, Poland,

Bibliografia

• [1] A. Czajka and A. Pacut, “Zak’s transform for automatic identity verification”, in Proc. 4th Int. Conf. Rec. Adv. Soft Comput. RASC 2002, Nottingham, United Kingdom, 2002, pp. 374–379.
• [2] A. Czajka and A. Pacut, “Iris recognition system based on Zak- Gabor wavelet packets”, J. Telecom. Inform. Technol., no. 4, pp. 10–18, 2010.
• [3] J. Daugman, “The importance of being random: statistical principles of iris recognition”, Pattern Recognition, vol. 36, pp. 279–291, 2003.
• [4] “Information Technology – Biometric data interchange formats – Iris image data”, ISO/IEC FDIS 19794-6:2011, 2011.
• [5] M. J. Bastiaans, “Gaborñs expansion and the Zak transform for continuous-time and discrete-time signals”, in Signal and Image Rep- resentation in Combined Spaces, J. Zeevi and R. Coifman, Eds. Academic Press, 1995, pp. 1–43.
• [6] A. Czajka and A. Pacut, “SDK for iris recognition”, NASK Review, pp. 34–39, 2009.
• [7] H. Peng, F. Long, and C. Ding, “Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy”, IEEE Trans. Pattern Anal. Machine Intelligence, vol. 27, no. 8, 2005.
• [8] H. Peng, “Mutual Information computation”, MATLAB implementation, August 23, 2007 [Online]. Available: http://www.mathworks.com/matlabcentral/fileexchange/14888
• [9] A. Kozakiewicz, A. Felkner, J. Furtak, Z. Zieliński, M. Brudka, and M. Małowidzki, “Secure workstation for special applications”, in Secure and Trust Computing, Data Management, and Applications, C. Lee, J.-M. Seigneur, J. J. Park, R. R. Wagner, Eds., Communications in Computer and Information Science, vol. 187. Berlin: Springer, 2011, pp. 174-181.