Open Access Journal

ISSN : 2395-2717 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Electrical and Electronic Engineering(IJEREEE)

Monthly Journal for Electrical and Electronic Engineering

ISSN : 2395-2717 (Online)

Human Identification Based On Iris Recognition Using Support Vector Machines

Author : Lalitha. K 1 Deepika T V 2 Sowjanya M N 3 Stafford Michahial 4

Date of Publication :7th May 2016

Abstract: Biometric identification is automated recognition of individuals based on their physiological and behavioral characteristics. The iris which have very unique features such as crypts, furrows etc.Iris recognition systems make use of the uniqueness of the iris patterns to derive an unique mapping where it becomes possible to apply some matching algorithms to identify a person. Here we implement iris recognition technique based on SVM (support vector machine) classifier to recognize the static image with the database images to use this application in security purpose.

Reference :

    1. J. Daugman. How iris recognition works. In Proc. International Conference on,Image Processing, pages 1-6, 2002.
    2. R.Wildes. Iris recognition: an emerging biometric technology. In Proc. IEEE international conference on image processing, volume 85, pages 12{18, 1997.
    3.  J.Daugman. High condence visual recognition of persons by a test of statistical independence. In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 15, pages 1148-1161, 1993
    4. N. Ritter C. Barry. Database of 120 greyscale eye images. lions eye institute,perth western australia, 2004. 2004
    5. Cortes, C. & Vapnik, V. (1995). Support-vector network. Machine Learning,Volume 20, pages 1–25.
    6. Ioan Climent,Juan Diego Blanco, Roberto A Hexcel(Approximate String matching for Iris recognition by means of boosted Gabor Wavelet‖ IEEE Trans on Systems,2010 23rd SIBGRAPI
    7. J. L. Wayman, A. K. Jain, D. Maltoni, and D. M. (Eds.),Biometric Systems. Springer-Verlag, 2005, isbn 978-1-85233-596-0.46
    8.  J. G. Daugman, ―High confidence visual recognition of persons by a test of statistical independence,‖ IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 15, no. 11,pp. 1148–1161, 1993.
    9.  New methods in iris recognition,‖ IEEE Trans on Systems, Man and Cybernetics, part B: Cybernetics, vol. 37,
    10. R. P. Wildes, ―Iris recognition: An emerging biometric technology,‖Proc of the IEEE, vol. 85, no. 9, pp. 1348–1363,Sep. 1997.
    11. W. W. Boles and B. Boashash, ―A human identification technique using images of the iris and wavelet transform,‖ IEEE Trans on Signal Processing, vol. 46, no. 4, pp. 1185–1188, Apr. 1998.
    12.  L. Ma, Y. Wang, and T. Tan, ―Iris recognition using circular symmetric filters,‖ in Int Conf on Pattern Recognition (ICPR’02), vol. 2, 2002, pp. 414–417.
    13. L. Ma, T. Tan, Y. Wang, and D. Zhang, ―Efficient iris recognition by characterizing key local variations, IEEE Trans on Image Processing, vol. 13, no. 6, pp. 739–750, Jun.2004.

Recent Article