A. Abhyankar and S. Schuckers, Iris quality assessment and bi-orthogonal wavelet based encoding for recognition, Pattern Recognition, vol.42, issue.9, pp.1878-1894, 2009.
DOI : 10.1016/j.patcog.2009.01.004

B. Ait-el-fquih and F. Desbouvries, Kalman Filtering in Triplet Markov Chains, IEEE Transactions on Signal Processing, vol.54, issue.8, pp.2957-2963, 2006.
DOI : 10.1109/TSP.2006.877651

C. Filho, C. Pinheiro, C. Costa, M. , A. Pereira et al., Applying a novelty filter as a matching criterion to iris recognition for binary and real-valued feature vectors, Signal, Image and Video Processing, vol.29, issue.4, pp.287-296, 2013.
DOI : 10.1007/s11760-011-0237-5

J. Daugman, How Iris Recognition Works, IEEE Transactions on Circuits and Systems for Video Technology, vol.14, issue.1, pp.21-30818350, 2003.
DOI : 10.1109/TCSVT.2003.818350
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.570.8548

F. Desbouvries and W. Pieczynski, Triplet Markov models and Kalman filtering. Comptes Rendus de l'Académie des Sciences -Mathématique -Série I, pp.667-670, 2003.

M. A. Fischler and R. C. Bolles, Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, vol.24, issue.6, pp.381-395, 1981.
DOI : 10.1145/358669.358692

H. Ghodrati, M. Dehghani, and H. Danyali, A new accurate noise-removing approach for non-cooperative iris recognition, Signal, Image and Video Processing, vol.133, issue.1, pp.1-10, 2014.
DOI : 10.1007/s11760-012-0396-z

K. Hollingsworth, E. Ortiz, and K. Bowyer, The Best Bits in an Iris Code, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.6, pp.964-973185, 2008.
DOI : 10.1109/TPAMI.2008.185

K. Hollingsworth, E. Ortiz, and K. Bowyer, Improved Iris Recognition through Fusion of Hamming Distance and Fragile Bit Distance, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.12, pp.2465-247689, 2011.
DOI : 10.1109/TPAMI.2011.89

A. Jain, A. Ross, and K. Nandakumar, Introduction to Biometrics. SpringerLink : Bücher, 2011.
DOI : 10.1007/978-0-387-77326-1

A. Jain, A. Ross, and S. Prabhakar, An Introduction to Biometric Recognition, IEEE Transactions on Circuits and Systems for Video Technology, vol.14, issue.1, pp.4-20818349, 2003.
DOI : 10.1109/TCSVT.2003.818349

Y. K. Jang, B. J. Kang, and K. R. Park, A study on eyelid localization considering image focus for iris recognition, Pattern Recognition Letters, vol.29, issue.11, pp.1698-1704, 2008.
DOI : 10.1016/j.patrec.2008.05.001

B. Kang and K. Park, A Study on Iris Image Restoration, Lecture Notes in Computer Science, vol.3546, pp.31-40, 2005.
DOI : 10.1007/11527923_4

T. Lefevre, B. Dorizzi, S. Garcia-salicetti, N. Lemperiere, and S. Belardi, Effective elliptic fitting for iris normalization, Computer Vision and Image Understanding, vol.117, issue.6, pp.732-745, 2013.
DOI : 10.1016/j.cviu.2013.01.005
URL : https://hal.archives-ouvertes.fr/hal-00812580

P. Li, X. Liu, L. Xiao, and Q. Song, Robust and accurate iris segmentation in very noisy iris images, Image and Vision Computing, vol.28, issue.2, pp.246-253, 2010.
DOI : 10.1016/j.imavis.2009.04.010

L. Masek, Recognition of human iris patterns for biometric identification, 2003.

V. Némesin and S. Derrode, Robust Blind Pairwise Kalman Algorithms Using QR Decompositions, IEEE Transactions on Signal Processing, vol.61, issue.1, pp.5-9, 2013.
DOI : 10.1109/TSP.2012.2222383

V. Némesin, S. Derrode, and A. Benazza-benyahia, Gradual Iris Code Construction from Close-Up Eye Video, 14th Int. Conf. on Advanced Concepts for Intelligent Vision Systems (ACIVS'12), pp.12-23, 2012.
DOI : 10.1007/978-3-642-33140-4_2

K. Nguyen, C. Fookes, S. Sridharan, and S. Denman, Quality-Driven Super-Resolution for Less Constrained Iris Recognition at a Distance and on the Move, IEEE Transactions on Information Forensics and Security, vol.6, issue.4, pp.1248-1258, 2011.
DOI : 10.1109/TIFS.2011.2159597

K. Nguyen, C. Fookes, S. Sridharan, and S. Denman, Feature-domain super-resolution for iris recognition, Computer Vision and Image Understanding, vol.117, issue.10, pp.1526-1535, 2013.
DOI : 10.1016/j.cviu.2013.06.010

P. J. Phillips, P. J. Flynn, J. R. Beveridge, W. T. Scruggs, A. J. O-'toole et al., Overview of the Multiple Biometrics Grand Challenge, Proc. of the 3rd Int. Conf. on Advances in Biometrics, pp.705-714, 2009.

K. Roy, P. Bhattacharya, and C. Suen, Iris segmentation using game theory, Signal, Image and Video Processing, vol.38, issue.2, pp.301-315, 2012.
DOI : 10.1007/s11760-010-0193-5

K. Y. Shin, K. R. Park, B. J. Kang, and S. J. Park, Super-Resolution Method Based on Multiple Multi-Layer Perceptrons for Iris Recognition, Proceedings of the 4th International Conference on Ubiquitous Information Technologies & Applications, pp.1-5, 2009.
DOI : 10.1109/ICUT.2009.5405701

R. Szewczyk, K. Grabowski, M. Napieralska, W. Sankowski, M. Zubert et al., A reliable iris recognition algorithm based on reverse biorthogonal wavelet transform, Pattern Recognition Letters, vol.33, issue.8, pp.1019-1026, 2012.
DOI : 10.1016/j.patrec.2011.08.018

E. Tabassi, P. Grother, and W. Salamon, IREX II -IQCE -Iris Quality Calibration and Evaluation, Tech. rep., NIST Interagency Report, vol.7820, 2011.

L. Yooyoung, R. J. Micheals, and P. J. Phillips, Improvements in video-based automated system for iris recognition (VASIR) In: Workshop on Motion and Video Computing, pp.1-85399237, 2009.