Palmprint recognition aims at finding out the palmprint template from the database, which is from the same palm as a given palmprint input. Feature extraction plays an important role in the recognition process. In this paper, we propose a new feature extraction method by converting a spatial domain palmprint image into a frequency domain image using Fourier Transform (FT) and representing palmprint features in the frequency domain. The extracted features are used as indexes to the palmprint templates in the database and the searching for the best match is leaded by these features in a layered fashion. The experimental result shows that the proposed FT based feature extraction method is effective in terms of accuracy and efficiency on our palmprint database.
[1] Miller, B. Vital signs of identity. IEEE Spectrum, 1994,32(2):22~30.
[2] Jain, A., Bolle, R., Pankanti, S. Biometrics: Personal Identification in Networked Society. Kluwer Academic Publishers, 1999.
[3] Zhang, D. Automated Biometrics--Technologies and Systems. Kluwer Academic Publishers, 2000.
[4] Zhang, D., Shu, W. Two novel characteristics in palmprint verification: datum point invariance and line feature matching. Pattern Recognition, 1999,33(4):691~702.
[5] Titchmarsh, E.C. Introduction to the Theory of Fourier Integral. New York: Oxford University Press, 1948.
[6] Cooley, J.W., Lewis, P.A.W., Welch, P.D. Historical notes on the fast Fourier transform. IEEE Transactions on Audio and Electroacoustics, 1967,AU-15(2):76~79.
[7] Cooley, J.W., Lewis, P.A.W., Welch, P.D. Application of the fast Fourier transform to computation of Fourier integrals. IEEE Transactions on Audio and Electroacoustics, 1967,AU-15(2):79~84.
[8] Brigham, E.O. The Fast Fourier Transform. Englewood Cliffs, NJ: Prentice-Hall, 1974.
[9] Andrews, H.C. Computer Techniques in Image Processing. New York: Academic Press, 1970.