한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

  • 제17권2호
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  • Pages.31-40
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  • 2012
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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Zernike 모멘트 기반의 회전 불변 홍채 인식

Rotation-Invariant Iris Recognition Method Based on Zernike Moments

  • 최창수 (충북대학교 전자정보대학 컴퓨터공학과) ;
  • 서정만 (한국재활복지대학 컴퓨터게임개발과) ;
  • 전병민 (충북대학교 전자정보대학 컴퓨터공학과)
  • Choi, Chang-Soo (Dept. of Computer Engineering, Chungbuk National University, College of Electronics & Information) ;
  • Seo, Jeong-Man (Dept. of Computer Game Design, Korea National College of Rehabilitation & Welfare) ;
  • Jun, Byoung-Min (Dept. of Computer Engineering, Chungbuk National University, College of Electronics & Information)
  • 투고 : 2011.12.08
  • 심사 : 2011.12.16
  • 발행 : 2012.02.29
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초록

홍채 인식은 홍채 패턴 정보를 이용하여 사람의 신원을 확인하는 생체 인식 기술이다. 이러한 홍채 인식 시스템에 있어 조명의 영향이나 동공의 크기, 머리의 기울어짐 등으로 인해 발생될 수 있는 홍채 패턴의 변화에 대해 무관한 특징을 추출하는 것은 중요한 과제이다. 본 논문에서는 Zernike Moment를 이용해 홍채의 회전에 강인한 홍채 인식 방법을 제안하였다. 빠르고 효과적인 인식을 위한 Zernike Moment를 선택하기 위해 전역 최적 차수를 이용하였고, 각각의 홍채 클래스와 매칭하기 위하여 국소 최적 차수를 사용 하였다. 제안된 방법은 특징 추출 및 특징 비교 시 회전에 대해 별도의 처리가 필요하지 않아 고속의 특징 추출 및 특징 비교가 가능하며 성능도 기존의 방법과 대등함을 실험을 통하여 확인하였다.

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. In this paper, we propose a novel method based on Zernike Moment which is robust to rotations of iris patterns. we utilized a selection of Zernike moments for the fast and effective recognition by selecting global optimum moments and local optimum moments for optimal matching of each iris class. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

키워드

참고문헌

  1. John Daugman, "High Confidence Visual Recognition of Person by a Test of tatistical Independence", IEEE Trans. Pattern Anal. Machine Intell., 15(11), pp. 1148-1161, 1993. https://doi.org/10.1109/34.244676
  2. R. Wildes, J.C. Asmuth, G.L. Green, S.C. Hsu, R.J. Kolczynski, J.R. Matey and S.E. McBride, "A system for automated iris recognition", Proceedings of the IEEE Workshop on Applications of Computer Vision, pp. 121-128, 1994.
  3. W.W. Boles, "A wavelet transform based technique for the recognition of the human iris", Proceedings of the International Symposium on Signal Processing and its Application, ISSPA, Gold Coast, Australia, pp. 25-30, August, 1996.
  4. C. Tisse L. Martin L. Torres and M. Robert, "Person Identification Technique Using Human Iris Recognition", Proc. Vision Interface, pp. 294-299, 2002.
  5. Y. Zhu, T. Tan and Y. Wang, "Biometric personal Identification based on iris pattern", Proceeding of. 15th International Conference on Pattern Recognition, vol. 2, pp. 801-804, 2000.
  6. S. Lim K. Lee O. Byeon and T. Kim, "Efficient Iris Recognition through Improvement of Feature Vector and Classifier", ETRI Journal, vol. 23, no. 2, pp. 61-70, 2001. https://doi.org/10.4218/etrij.01.0101.0203
  7. S. Noh, K. Pae, C. Lee, J. Kim. "Multiresolution independent component analysis for iris identification," The 2002 International Technical Conference on Circuits/Systems, Computers and Communications, Phuket, Thailand, 2002.
  8. Li Ma, Tieniu Tan and Yunhong Wang, "Efficient Iris Recognition by Characterizing Key Local Variations", IEEE Trans. Image Processing ,13(6), pp. 739-750, 2004. https://doi.org/10.1109/TIP.2004.827237
  9. RajeshM. Bodade and Sanjay N. Talbar, "Shift Invariant Iris Feature Extraction using Rotated Complex Wavelet and Complex Wavelet for Iris Recognition System", 2009 Seventh International Conference on Advances in Pattern Recognition, pp. 449-452, 2009.
  10. Zhiping Zhou, Huijun Wu and Qianxing Lv, "A New Iris Recognition Method Based on Gabor Wavelet Neural Network", International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 1101-1104, 2009.
  11. Chang-Soo Choi, Jong-Cheon Park and Byoung-Min Jun, "A Iris Recognition Using Zernike Moment and Wavelet", Korea Academia-industrial cooperation Society, vol. 11 no. 11, pp.4568-4575, 2010 https://doi.org/10.5762/KAIS.2010.11.11.4568
  12. Alireza Khotanzad and YawHua Hong, "On Image Analysis by the Methods of Moments," IEEE Trans. Pattern Anal. Machine Intell., vol. 12, pp. 489-497, May 1990. https://doi.org/10.1109/34.55109
  13. http://www.sinobiometrics.com
  14. Chang-Soo Choi, Byoung-Min Jun, "Robust-to-r otation Iris Recognition Using Local Gradient Orientation Histogram", Korea Information and Communications Society, vol. 34, no. 3, pp. 268-273, 2009.