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Iris Features Extraction Using Beamlets and Wedgelets

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Wybrane pełne teksty z tego czasopisma
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Języki publikacji
EN
Abstrakty
EN
A new approach to iris feature extraction using geometrical wavelets is presented. Iris code is generated by using representation of the wavelet coefficients based on a wedgelet dictionary. The accuracy of identification in the case of head inclination by a certain angle for different ranges of possibilities of shifting the iris code is shown. Experimental results on the CASIA iris database show that the proposed method is effective and exhibits encouraging performance.
Rocznik
Strony
289--304
Opis fizyczny
Bibliogr. 18 poz., il.
Twórcy
Bibliografia
  • [l] Flom L., Safir A.: Iris recognition system, United States Patent No. 4.641.349, February 3, 1987.
  • [2] Daugman J.: "High confidence visual recognition of persons by a test of statistical independence" IEEE Transactions on Pattern Analysis and Machine Intelligence, v. 15, n. 11, Nov. 1993, pp.1148-1161.
  • [3] Daugman J.: "Biometric Personal Identification System Based on Iris Analysis" U.S. Patent No. 5, 291, 560, March 1, 1994
  • [4] Wildes R.: "Iris recognition: an emerging biometric technology" Proceedings of the IEEE Vol. 85, s. 13481363, 1997.
  • [5] Boles W.: "A security system based on human iris identification using wavelet transform" Proceedings of the first International Conference on Knowledge-Based Intelligent Electronic Systems, 1997, pp. 533-541
  • [6] Boles W. W., Boashash B.:, A human identification technique using images of the iris and wavelet transform, IEEE Transactions on Signal Processing, vol. 46, no. 4, pp. 11851188, 1998.
  • [7] Donoho D. L.: Wedgelets: Nearly-minimax estimation of edges. Annals of Stat., Vol. 27, s. 859897. 1999.
  • [8] Barrett A.: "Daugman's Iris Scanning Algorithm" Biometrics Test Center, San Jose State University 2/4/00 DaugmanAlgl.doc, vs. 2.0 ; 2000.
  • [9] Czajka A., Pacut A.: "Biometria tęczówki oka", Techniki Komputerowe, Biuletyn Informacyjny, nr 1/2002, str. 5-18, Instytut Maszyn Matematycznych, Warszawa, 2002
  • [10] Ma L., Tan T., Wang Y.:Iris recognition using circular symmetric filters, in Proc. 16th Int. Conf. Pattern Recognition, vol. II, 2002, pp. 414417.
  • [11] Ma L., Tan T., Wang Y., Zhang D.: Personal Identification Based on Iris Texture Analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 12, pp. 1519-1533, 2003
  • [12] Lisowska A.: Extended Wedgelets - Geometrical Wavelets in Efficient Image Coding, Machine Graphics and Vision, Vol. 13, No. 3, 2004, pp. 261-274
  • [13] Ma L., Tan T., Zhang D.,Wang Y.: Local Intensity Variation Analysis for Iris Recognition, Pattern Recognition, Vol. 37, No. 6, pp. 1287-1298, 2004.
  • [14] Ma L., Tan T., Wang Y., Zhang D.: Efficient iris recognition by characterizing key local variations, IEEE Transactions on Image Processing, vol. 13, no. 6, pp. 739750, 2004.
  • [15] X. Liu, K. W. Bowyer, and P. J. Flynn, Experiments with an improved iris segmentation algorithm, in Proceedings of the 4th IEEE Workshop on Automatic Identification Advanced Technologies (AUTO ID 05), pp. 118123, Buffalo, NY, USA,October 2005.
  • [16] Kaushik R., Prabir B.: Optimal Features Subset Selection and Classification for Iris Recognition, EURASIP Journal on Image and Video Processing Volume 2008 (2008), Article ID 743103, 20 pages doi:10.1155/2008/743103
  • [17] http://www.cl.cam.ac.uk/users/jgdl000/history.html
  • [18] http://www.cbsr.ia.ac.cn/IrisDatabase.htm
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA9-0032-0003
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