Artur Ferreira, André Lourenço, Bárbara Pinto, Jorge Tendeiro


Iris recognition is a well-known biometric technique. John Daugman has proposed a method for iris recognition, which is divided into four steps: segmentation, normalization, feature extraction and matching. In this paper, we evaluate, modify and extend John Daugman’s method. We study the images of CASIA and UBIRIS databases to establish some modifications and extensions on Daugman’s algorithm. The major modification is on the computationally demanding segmentation stage, for which we propose a template matching approach. The extensions on the algorithm address the important issue of pre-processing, that depends on the image database, being especially important when we have a non infra-red red camera (e.g. a WebCam). For this typical scenario, we propose several methods for reflexion removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images, show that our template matching based segmentation method is accurate and faster than the one proposed by Daugman. Our fast pre-processing algorithms efficiently remove reflections on images taken by non infra-red cameras.


  1. Arvacheh, E. M. (2006). A study of segmentation and normalization for iris recognition systems. Master's thesis, University of Waterloo.
  2. Boles, W. (1997). A security system based on iris identification using wavelet transform. In L.C.Jain, editor, First Int Conf on Knowledge-Based Intelligent Electronic Systems, pages 533-541, Adelaide, Australia.
  3. Daugman, J. (1993). High confidence visual recognition of persons by a test of statistical independence. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(11):1148-1161.
  4. Daugman, J. (2004). How iris recognition works. IEEE Transactions on Circuits and Systems for Video Technology, 14(1):21-30.
  5. Greco, J., Kallenborn, D., and Nechyba, M. C. (2004). Statistical pattern recognition of the iris. In 17th annual Florida Conference on the Recent Advances in Robotics (FCRAR).
  6. Jain, A. K., Ross, A., and Prabhakar, S. (2004). An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology, 14(1).
  7. J.Huang, Y.Wang, T.Tan, and J.Cui (2004). A new iris segmentation method for recognition. In 17th Int Conf on Pattern Recognition (ICPR'04).
  8. Joung, B. J., Kim, J. O., Chung, C. H., Lee, K. S., Yim, W. Y., and Lee, S. H. (2005). On improvement for normalizing iris region for a ubiquitous computing. Computational Science and Its Applications ICCSA 2005, pages 1213-1219.
  9. Lim, J. (1990). Two-dimensional Signal and Image Processing. Prentice Hall.
  10. Maltoni, D., Maio, D., Jain, A. K., and Prabhakar, S. (2005). Handbook of Fingerprint Recognition. Springer, 1th edition.
  11. Masek, L. (2003). Recognition of human iris patterns for biometric identification. Master's thesis, University of Western Australia.
  12. Proenc¸a, H. (2007). Towards Non-Cooperative Biometric Iris Recognition. PhD thesis, Universidade da Beira Interior.
  13. Proenc¸a, H. and Alexandre, L. A. (2005). UBIRIS: a noisy iris image database. Lecture Notes in Computer Science ICIAP 2005 - 13th International Conference on Image Analysis and Processing, 1:970-977.
  14. Vatsa, M., Singh, R., and Gupta, P. (2004). Comparison of iris recognition algorithms. In Proceedings of International Conference on Intelligent Sensing and Information Processing, pages 354- 358.
  15. Wildes, R. (1997). Iris recognition: an emerging biometric technology. Proceedings of the IEEE, 85(9):1348- 1363.
  16. Yao, P., Li, J., Ye, X., Zhuang, Z., and Li, B. (2006). Analysis and improvement of an iris identification algorithm. In 18th International Conference on Pattern Recognition (ICPR'06).

Paper Citation

in Harvard Style

Ferreira A., Lourenço A., Pinto B. and Tendeiro J. (2009). MODIFICATIONS AND IMPROVEMENTS ON IRIS RECOGNITION . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009) ISBN 978-989-8111-65-4, pages 72-79. DOI: 10.5220/0001536100720079

in Bibtex Style

author={Artur Ferreira and André Lourenço and Bárbara Pinto and Jorge Tendeiro},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)},

in EndNote Style

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)
SN - 978-989-8111-65-4
AU - Ferreira A.
AU - Lourenço A.
AU - Pinto B.
AU - Tendeiro J.
PY - 2009
SP - 72
EP - 79
DO - 10.5220/0001536100720079