Iris Recognition System Based on Zak-Gabor Wavelet Packets

• Autorzy: Czajka A. , Pacut A.
• Języki publikacji: EN

Abstrakty

EN

The paper proposes a new iris coding method based on Zak-Gabor wavelet packet transform. The essential component of the iris recognition methodology design is an effective adaptation of the transformation parameters that makes the coding sensitive to the frequencies characterizing ones eye. We thus propose to calculate the between-to-within class ratio of weakly correlated Zak-Gabor transformation coefficients allowing for selection the frequencies the most suitable for iris recognition. The Zak-Gabor-based coding is non-reversible, i.e., it is impossible to reconstruct the original iris image given the iris template. Additionally, the inference about the iris image properties from the Zak-Gabor-based code is limited, providing a possibility to embed the biometric replay attack prevention methodology into the coding. We present the final prototype system design, including the hardware, and evaluate its performance using the database of 720 iris images.

Słowa kluczowe

EN

biometrics; iris recognition; Zak-Gabor transform

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2010
• Tom: nr 4
• Strony: 10--18
• Opis fizyczny: Bibliogr. 6 poz., rys., tab.

Twórcy

autor

Czajka A.

autor

Pacut A.

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

Bibliografia

• [1] J. Daugman, “Biometric personal identification system based on iris analysis”, United States Patent US 5,291,560, assignee: IriScan Inc., NJ, USA, March 1, 1994.
• [2] A. Pacut and A. Czajka, “Aliveness detection for iris biometrics”, in Proc. 40th IEEE Int. Carnahan Conf. Secur. Technol. ICCST 2006, Lexington, USA, 2006.
• [3] Information technology – Biometric data interchange formats – Part 6: Iris image data, ISO/IEC International Standard 19794-6:2005(E)
• [4] T. T. Chinen and T. R. Reed, “A performance analysis of fast gabor transform methods”, Graph. Mod. Image Proces., vol. 59, no. 3, pp. 117–127, 1997.
• [5] M. J. Bastiaans, “Gabor’s expansion and the zak transform for continuous-time and discrete-time signals”, in Signal and Image Representation in Combined Spaces, J. Zeevi and R. Coifman, Eds. Academic Press, 1995, pp. 1–43.
• [6] A. Czajka and A. Pacut, “BiomIrisSDK – software development kit for iris recognition”, NASK Review, pp. 34–39, 2009.