BIRD: Watershed Based IRis Detection for mobile devices, Pattern Recognition Letters, vol.57, pp.43-51, 2015. ,
DOI : 10.1016/j.patrec.2014.10.017
SLIC Superpixels Compared to State-of-the-Art Superpixel Methods, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.11, pp.2274-2282, 2012. ,
DOI : 10.1109/TPAMI.2012.120
Physiologie of the Eye. London : The C.V. Mosby Company, 1965. ,
A Multichannel Markov Random Field Framework for Tumor Segmentation With an Application to Classification of Gene Expression-Based Breast Cancer Recurrence Risk, IEEE Transactions on Medical Imaging, vol.32, issue.4, pp.637-648, 2013. ,
DOI : 10.1109/TMI.2012.2219589
Medical image retrieval and analysis by Markov random fields and multi-scale fractal dimension, Physics in Medicine and Biology, vol.60, issue.3, p.1125, 2015. ,
DOI : 10.1088/0031-9155/60/3/1125
An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology, Bulletin of the American Mathematical Society, vol.73, issue.3 ,
DOI : 10.1090/S0002-9904-1967-11751-8
A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. The annals of mathematical statistics, pp.164-171, 1970. ,
Unsupervised segmentation of random discrete data using triplet Markov chains, International Symposium on Applied Stochastic Models and Data Analysis. Citeseer, 2007. ,
Challenging eye segmentation using Triplet Markov spatial models, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.1927-1931, 2013. ,
DOI : 10.1109/ICASSP.2013.6637989
URL : https://hal.archives-ouvertes.fr/hal-01277855
Estimation des paramètres dans les cha??nescha??nes de Markov cachées et segmentation d'images, TS. Traitement du signal, vol.12, issue.5, pp.433-454, 1995. ,
La couleur de l'iris, Annales de demographie internationnale, 1886. ,
Statistical analysis of dirty pictures*, Journal of Applied Statistics, vol.6, issue.5-6, pp.259-302, 1986. ,
DOI : 10.1016/0031-3203(83)90012-2
An online em algorithm in hidden (semi-)Markov models for audio segmentation and clustering, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1881-1885, 2015. ,
DOI : 10.1109/ICASSP.2015.7178297
URL : https://hal.archives-ouvertes.fr/hal-01115826
Triplet Markov Fields for the Classification of Complex Structure Data, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.6, pp.1055-1067, 2008. ,
DOI : 10.1109/TPAMI.2008.27
URL : https://hal.archives-ouvertes.fr/inria-00168621
A human identification technique using images of the iris and wavelet transform, IEEE Transactions on Signal Processing, vol.46, issue.4, pp.1185-1188, 1998. ,
DOI : 10.1109/78.668573
Modèles graphiquesévidentielsgraphiques´graphiquesévidentiels. Theses, Institut National des Télécommunications, 2014. ,
Unsupervised Segmentation of Random Discrete Data Hidden With Switching Noise Distributions, IEEE Signal Processing Letters, vol.19, issue.10, pp.19619-622, 2012. ,
DOI : 10.1109/LSP.2012.2209639
URL : https://hal.archives-ouvertes.fr/hal-00738142
Phasic Triplet Markov Chains, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.36, issue.11, pp.2310-2316, 2014. ,
DOI : 10.1109/TPAMI.2014.2327974
URL : https://hal.archives-ouvertes.fr/hal-01262461
Dempster???Shafer Fusion of Evidential Pairwise Markov Chains, IEEE Transactions on Fuzzy Systems, vol.24, issue.6, pp.1-1, 2016. ,
DOI : 10.1109/TFUZZ.2016.2543750
URL : https://hal.archives-ouvertes.fr/hal-01426916
Unsupervised segmentation of non stationary data hidden with non stationary noise, International Workshop on Systems, Signal Processing and their Applications, WOSSPA, pp.255-258, 2011. ,
DOI : 10.1109/WOSSPA.2011.5931466
URL : https://hal.archives-ouvertes.fr/hal-01354693
Analysis of the retinex theory of color vision, Journal of the Optical Society of America A, vol.3, issue.10, pp.1651-1661, 1986. ,
DOI : 10.1364/JOSAA.3.001651
MS Lesion Segmentation based on Hidden Markov Chains. Grand Challenge Work, Mult. Scler. Lesion Segm. Challenge, pp.1-9, 2008. ,
Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains, Medical Image Analysis, vol.12, issue.6, pp.639-652, 2008. ,
DOI : 10.1016/j.media.2008.03.001
Reconnaissance de mélanges de densités par un algorithme d'apprentissage probabiliste. Data analysis and informatics, BIBLIOGRAPHIE, vol.3, pp.359-373, 1983. ,
Hidden Markov Models : Applications in Computer Vision, World Scientific, vol.45, 2001. ,
DOI : 10.1142/4648
Reliable and fast eye finding in close-up images, Object recognition supported by user interaction for service robots, pp.389-394, 2002. ,
DOI : 10.1109/ICPR.2002.1044732
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.84.7226
Unsupervised change detection on SAR images using fuzzy hidden Markov chains, IEEE Transactions on Geoscience and Remote Sensing, vol.44, issue.2, pp.432-441, 2006. ,
DOI : 10.1109/TGRS.2005.861007
URL : https://hal.archives-ouvertes.fr/hal-00082617
ENCARA2: Real-time detection of multiple faces at different resolutions in video streams, Journal of Visual Communication and Image Representation, vol.18, issue.2, pp.130-140, 2007. ,
DOI : 10.1016/j.jvcir.2006.11.004
Stochastic versions of the em algorithm: an experimental study in the mixture case, Journal of Statistical Computation and Simulation, vol.67, issue.4, pp.287-314, 1996. ,
DOI : 10.1214/aos/1176346060
URL : https://hal.archives-ouvertes.fr/hal-00693519
The SEM algorithm : a probabilistic teacher algorithm derived from the EM algorithm for the mixture problem, Computational statistics quarterly, vol.2, issue.1, pp.73-82, 1985. ,
L'algorithme SEM : un algorithme d'apprentissage probabiliste pour la reconnaissance de mélange de densités, pp.35-52, 1986. ,
A random imputation principle : the stochastic EM algorithm, 1988. ,
URL : https://hal.archives-ouvertes.fr/inria-00075655
A highly accurate and computationally efficient approach for unconstrained iris segmentation, Image and Vision Computing, vol.28, issue.2 ,
DOI : 10.1016/j.imavis.2009.04.017
A hierarchical approach to color image segmentation using homogeneity, IEEE Transactions on image processing, vol.9, issue.12, pp.2071-2082, 2000. ,
Salient object detection and segmentation, Image, vol.2, issue.3, p.9, 2011. ,
Human Identification in Information Systems, Information Technology & People, vol.7, issue.4, pp.6-37, 1994. ,
DOI : 10.1108/09593849410076816
Vertebra segmentation based on two-step refinement, Journal of Computational Surgery, vol.39, issue.397, 2016. ,
DOI : 10.1007/978-3-642-33454-2_63
URL : http://doi.org/10.1186/s40244-016-0018-0
High confidence visual recognition of persons by a test of statistical independence, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.15, issue.11, pp.1148-1161, 1993. ,
DOI : 10.1109/34.244676
Biometric personal identification system based on iris analysis, US Patent, vol.5, p.291560, 1994. ,
How iris recognition works IEEE Transactions on circuits and systems for video technology, pp.21-30, 2004. ,
DOI : 10.1016/b978-0-12-374457-9.00025-1
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.570.8548
New Methods in Iris Recognition, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.37, issue.5, pp.1167-1175, 2007. ,
DOI : 10.1109/TSMCB.2007.903540
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.119.7028
Unsupervised image segmentation using triplet Markov fields, Computer Vision and Image Understanding, vol.99, issue.3, pp.476-498, 2005. ,
DOI : 10.1016/j.cviu.2005.04.003
URL : https://hal.archives-ouvertes.fr/hal-01347961
Relations entre les algorithmes d'estimation iteratives EM et ICE avec exemples d'application, 15 Colloque sur le traitement du signal et des images, 1995. ,
Maximum Likelihood from Incomplete Data via the EM Algorithm, Journal of the Royal Statistical Society. Series B (Methodological), pp.1-38, 1977. ,
Signal and Image Segmentation Using Pairwise Markov Chains, IEEE Transactions on Signal Processing, vol.52, issue.9, pp.2477-2489, 2004. ,
DOI : 10.1109/TSP.2004.832015
URL : https://hal.archives-ouvertes.fr/hal-01346595
Signal and Image Segmentation Using Pairwise Markov Chains, IEEE Transactions on Signal Processing, vol.52, issue.9, pp.2477-2489, 2004. ,
DOI : 10.1109/TSP.2004.832015
URL : https://hal.archives-ouvertes.fr/hal-01346595
Unsupervised data classification using pairwise Markov chains with automatic copulas selection, Computational Statistics & Data Analysis, vol.63, pp.81-98, 2013. ,
DOI : 10.1016/j.csda.2013.01.027
URL : https://hal.archives-ouvertes.fr/hal-00830221
Baum's forward-backward algorithm revisited, Pattern Recognition Letters, vol.3, issue.6, pp.369-373, 1985. ,
DOI : 10.1016/0167-8655(85)90023-6
Discrete circles, rings and spheres. Computers and Graphics, pp.695-706, 1994. ,
Improving Offline Handwritten Text Recognition with Hybrid HMM/ANN Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.4, pp.767-779, 2011. ,
DOI : 10.1109/TPAMI.2010.141
Fusing the line intensity profile and support vector machine for removing reflections in frontal {RGB} color eye images, Information Sciences, vol.276, pp.104-122, 2014. ,
A low lighting or contrast ratio visible iris recognition using iso-contrast limited adaptive histogram equalization. Knowledge-Based Systems, pp.40-48, 2015. ,
Unsupervised Classification of Radar Images Using Hidden Markov Chains and Hidden Markov Random Fields. Geoscience and Remote Sensing, IEEE Transactions on, vol.41, issue.3, pp.675-686, 2003. ,
URL : https://hal.archives-ouvertes.fr/hal-01347239
Watershed Based Iris SEgmentation, pp.204-212, 2013. ,
DOI : 10.1007/978-3-642-38989-4_21
WIRE: Watershed based iris recognition, Pattern Recognition, vol.52, pp.148-159, 2016. ,
DOI : 10.1016/j.patcog.2015.08.017
A region-level motion-based graph representation and labeling for tracking a spatial image partition, Pattern Recognition, vol.33, issue.4, pp.725-740, 2000. ,
DOI : 10.1016/S0031-3203(99)00083-7
URL : https://hal.archives-ouvertes.fr/hal-00442736
Stochastic Relaxation, Gibbs Distributions and the Bayesian Restoration of Images, IEEE Transactions on pattern analysis and machine intelligence, issue.6, pp.721-741, 1984. ,
Random Walks for Image Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.11, pp.1768-1783, 2006. ,
DOI : 10.1109/TPAMI.2006.233
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.375.3389
Non-iris occlusions detection, 2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp.1-6, 2013. ,
DOI : 10.1109/BTAS.2013.6712729
Unsupervised detection of non-iris occlusions, Pattern Recognition Letters, vol.57, pp.60-65, 2015. ,
DOI : 10.1016/j.patrec.2015.02.012
Toward Accurate and Fast Iris Segmentation for Iris Biometrics, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.9, pp.1670-1684, 2009. ,
Ueber die stetige Abbildung einer Line auf ein Fl???chenst???ck, Mathematische Annalen, vol.38, issue.3, pp.459-460, 1891. ,
DOI : 10.1007/BF01199431
Improving colour iris segmentation using a model selection technique, Pattern Recognition Letters, vol.57, pp.24-32, 2015. ,
DOI : 10.1016/j.patrec.2014.12.012
An Introduction to Biometric Recognition, IEEE Transactions on Circuits and Systems for Video Technology, pp.4-20, 2004. ,
DOI : 10.1109/TCSVT.2003.818349
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.69.3028
Binary Morphology and Local Statistics Applied to Iris Segmentation for Recognition, 2006 International Conference on Image Processing, pp.293-296, 2006. ,
DOI : 10.1109/ICIP.2006.313183
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.1270
Deep Sign: Hybrid CNN-HMM for Continuous Sign Language Recognition, Procedings of the British Machine Vision Conference 2016, 2016. ,
DOI : 10.5244/C.30.136
Unsupervised segmentation of triplet Markov chains hidden with long-memory noise, Signal Processing, vol.88, issue.5, pp.1134-1151, 2008. ,
DOI : 10.1016/j.sigpro.2007.10.015
URL : https://hal.archives-ouvertes.fr/hal-01106546
Unsupervised non stationary image segmentation using triplet Markov chains Advanced Concepts for Intelligent Vision Systems, 2004. ,
Fuzzy pairwise Markov chain to segment correlated noisy data, Signal Processing, vol.88, issue.10, pp.2526-2541, 2008. ,
Iris recognition system, US Patent, vol.4641, p.349, 1987. ,
Markov Random Field Modeling in Computer Vision, 2012. ,
DOI : 10.1007/978-4-431-66933-3
Accurate iris segmentation in non-cooperative environments using fully convolutional networks, 2016 International Conference on Biometrics (ICB), pp.1-8, 2016. ,
DOI : 10.1109/ICB.2016.7550055
Experiments with An Improved Iris Segmentation Algorithm, Automatic Identification Advanced Technologies, pp.118-123, 2005. ,
Personal identification based on iris texture analysis, IEEE transactions on pattern analysis and machine intelligence, vol.25, issue.12, pp.1519-1533, 2003. ,
Probabilistic Solution of Ill-Posed Problems in Computational Vision, Journal of the American Statistical Association, vol.18, issue.397, pp.76-89, 1987. ,
DOI : 10.1109/TIT.1972.1054786
Recognition of Human Iris Patterns for Biometric Identification, 2003. ,
Wiley Series in Probability and Statistics. The EM Algorithm and Extensions, pp.361-369, 2000. ,
Three-Class Markovian Segmentation of High-Resolution Sonar Images, Computer Vision and Image Understanding, vol.76, issue.3, pp.191-204, 1999. ,
DOI : 10.1006/cviu.1999.0804
Sonar image segmentation using an unsupervised hierarchical MRF model, IEEE Transactions on Image Processing, vol.9, issue.7, pp.1216-1231, 2000. ,
DOI : 10.1109/83.847834
URL : http://www.irisa.fr/vista/Papers/2000_ieeeip_mignotte.pdf
An Effective Approach for Iris Recognition Using Phase-Based Image Matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.10, pp.1741-1756, 2008. ,
DOI : 10.1109/TPAMI.2007.70833
Estimation de mélanges généralisés dans les arbres de Markov cachés, applicationàapplicationà la segmentation des images de cartons d'orgue de barbarie, 2005. ,
DCT-Based Iris Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, issue.4, 2007. ,
DOI : 10.1109/TPAMI.2007.1002
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.498.2235
Toward More Accurate Iris Recognition Using Cross-Spectral Matching, IEEE Transactions on Image Processing, vol.26, issue.1, pp.208-221, 2017. ,
DOI : 10.1109/TIP.2016.2616281
OSIRIS: An open source iris recognition software, Pattern Recognition Letters, vol.82, 2015. ,
DOI : 10.1016/j.patrec.2015.09.002
URL : https://hal.archives-ouvertes.fr/hal-01390870
Circular Hough Transform. Aalborg University, Vision, Graphics, and Interactive Systems, 2007. ,
Robust and accurate iris segmentation in very noisy iris images Segmentation of Visible Wavelength Iris Images Captured At-a-distance and On-the-move, Image and Vision Computing, vol.28, issue.2, pp.246-253, 2010. ,
An introduction evaluating biometric systems, Computer, vol.33, issue.2, pp.56-63, 2000. ,
DOI : 10.1109/2.820040
Statistical image segmentation. Machine graphics and vision, pp.261-268, 1992. ,
Pairwise Markov Chains. Pattern Analysis and Machine Intelligence, BIBLIOGRAPHIE IEEE Transactions on, vol.25, issue.5, pp.634-639, 2003. ,
DOI : 10.1109/tpami.2003.1195998
URL : https://hal.archives-ouvertes.fr/hal-01346583
Multisensor triplet Markov chains and theory of evidence, International Journal of Approximate Reasoning, vol.45, issue.1, pp.1-16, 2007. ,
DOI : 10.1016/j.ijar.2006.05.001
URL : https://hal.archives-ouvertes.fr/hal-01347975
Sur la convergence de l'estimation conditionnelle it??rative, Comptes Rendus Mathematique, vol.346, issue.7-8, pp.457-460, 2008. ,
DOI : 10.1016/j.crma.2008.02.023
Triplet Markov Chains in hidden signal restoration, International Symposium on Remote Sensing International Society for Optics and Photonics, pp.58-68, 2003. ,
DOI : 10.1117/12.463183
Pairwise Markov random fields and segmentation of textured images. Machine graphics and vision, pp.705-718, 2000. ,
UBIRIS : A noisy iris image database. Image Analysis and Processing?ICIAP, pp.970-977, 2005. ,
Iris segmentation methodology for non-cooperative recognition, IEE Proceedings-Vision, Image and Signal Processing, pp.199-205, 2006. ,
DOI : 10.1049/ip-vis:20050213
Iris recognition: Analysis of the error rates regarding the accuracy of the segmentation stage, Image and Vision Computing, vol.28, issue.1, pp.202-206, 2010. ,
DOI : 10.1016/j.imavis.2009.03.003
Iris Recognition : On the Segmentation of Degraded Images Acquired in the Visible Wavelength. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.32, issue.8, pp.1502-1516, 2010. ,
The UBIRIS.v2: A Database of Visible Wavelength Iris Images Captured On-the-Move and At-a-Distance, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.8 ,
DOI : 10.1109/TPAMI.2009.66
Iris segmentation in non-ideal images using graph cuts, Image and Vision Computing, vol.28, issue.12, pp.1671-1681, 2010. ,
DOI : 10.1016/j.imavis.2010.05.004
On the use of Gibbs Markov chain models in the analysis of images based on second-order pairwise interactive distributions, Journal of Applied Statistics, vol.2, issue.2, pp.267-281, 1989. ,
DOI : 10.1109/TPAMI.1984.4767596
Pairwise Markov Model Applied to Unsupervised Image Separation, Signal Processing, Pattern Recognition, and Applications / 722: Computer Graphics and Imaging, pp.16-18, 2011. ,
DOI : 10.2316/P.2011.721-044
URL : https://hal.archives-ouvertes.fr/hal-00714717
Smartphone based visible iris recognition using deep sparse filtering, Pattern Recognition Letters, vol.57, pp.33-42, 2015. ,
DOI : 10.1016/j.patrec.2014.09.006
Iris-biometric comparators: Exploiting comparison scores towards an optimal alignment under Gaussian assumption, 2012 5th IAPR International Conference on Biometrics (ICB), pp.297-302, 2012. ,
DOI : 10.1109/ICB.2012.6199823
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.653.6568
Iris Biometrics : From Segmentation to Template Security, 2012. ,
DOI : 10.1007/978-1-4614-5571-4
The Human Iris as a Biometric Identifier, pp.3-6 ,
DOI : 10.1007/978-1-4614-5571-4_1
The Watershed Transform : Definitions, Algorithms and Parallelization Strategies, Fundamenta informaticae, vol.41, issue.1 2, pp.187-228, 2000. ,
Segmenting Non-Ideal Irises Using Geodesic Active Contours, 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, pp.1-6, 2006. ,
DOI : 10.1109/BCC.2006.4341625
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.101.8440
Towards nonideal iris recognition based on level set method, genetic algorithms and adaptive asymmetrical SVMs, Engineering Applications of Artificial Intelligence, vol.24, issue.3, pp.458-475, 2011. ,
DOI : 10.1016/j.engappai.2010.06.014
Iris-based biometric recognition using dyadic wavelet transform, IEEE Aerospace and Electronic Systems Magazine, vol.17, issue.10, pp.3-6, 2002. ,
DOI : 10.1109/MAES.2002.1044509
Iris-based biometric recognition using dyadic wavelet transform, IEEE Aerospace and Electronic Systems Magazine, vol.17, issue.10, pp.3-6, 2002. ,
DOI : 10.1109/MAES.2002.1044509
Reliable algorithm for iris segmentation in eye image, Image and Vision Computing, vol.28, issue.2, pp.231-237, 2010. ,
DOI : 10.1016/j.imavis.2009.05.014
On Techniques for Angle Compensation in Nonideal Iris Recognition, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.37, issue.5, pp.1176-1190, 2007. ,
DOI : 10.1109/TSMCB.2007.904831
Iris Segmentation Using Geodesic Active Contours, IEEE Transactions on Information Forensics and Security, vol.4, issue.4, pp.824-836, 2009. ,
DOI : 10.1109/TIFS.2009.2033225
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.204.3948
Generalized Hilbert scan in image printing, Proceedings of the 6th Workshop on Theoretical Foundations of Computer Vision, 1992. ,
Prior parameter estimation for Ising-MRFbased sonar image segmentation by local center-encoding, OCEANS 2015-Genova, pp.1-5, 2015. ,
DOI : 10.1109/oceans-genova.2015.7271429
The Viterbi algorithm at different resolutions for enhanced iris segmentation, 2012 5th IAPR International Conference on Biometrics (ICB), pp.310-316, 2012. ,
DOI : 10.1109/ICB.2012.6199825
URL : https://hal.archives-ouvertes.fr/hal-00746644
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
Efficient iris segmentation using Grow-Cut algorithm for remotely acquired iris images, 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp.99-104, 2012. ,
DOI : 10.1109/BTAS.2012.6374563
Unified Framework for Automated Iris Segmentation Using Distantly Acquired Face Images, IEEE Transactions on Image Processing, vol.21, issue.9, pp.4068-4079, 2012. ,
DOI : 10.1109/TIP.2012.2199125
Towards Online Iris and Periocular Recognition Under Relaxed Imaging Constraints, Image Processing IEEE Transactions on, vol.22, issue.10, pp.3751-3765, 2013. ,
Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition, Image and Vision Computing, vol.28, issue.2, pp.223-230, 2010. ,
DOI : 10.1016/j.imavis.2009.05.008
Estimation of planar curves, surfaces, and nonplanar space curves defined by implicit equations with applications to edge and range image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.13, issue.11, pp.1115-1138, 1991. ,
DOI : 10.1109/34.103273
Improving Iris Recognition Performance Using Segmentation, Quality Enhancement, Match Score Fusion, and Indexing, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol.38, issue.4, pp.1021-1035, 2008. ,
DOI : 10.1109/TSMCB.2008.922059
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.409.7032
GrowCut : Interactive Multi-Label N-D Image Segmentation by Cellular Automata, In proc. of Graphicon, vol.1, pp.150-156 ,
Robust Real-time Object Detection, In International Journal of Computer Vision, 2001. ,
Robust Real-Time Face Detection, International Journal of Computer Vision, vol.57, issue.2, pp.137-154, 2004. ,
DOI : 10.1023/B:VISI.0000013087.49260.fb
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.9805
Unsupervised SAR Image Segmentation Using Higher Order Neighborhood-Based Triplet Markov Fields Model, IEEE Transactions on Geoscience and Remote Sensing, vol.52, issue.8 ,
DOI : 10.1109/TGRS.2013.2287273
Fast and accurate iris segmentation based on linear basis function and RANSAC, 2011 18th IEEE International Conference on Image Processing, pp.3205-3208, 2011. ,
DOI : 10.1109/ICIP.2011.6116350
Iris recognition: an emerging biometric technology, Proceedings of the IEEE, vol.85, issue.9, pp.1348-1363, 1997. ,
DOI : 10.1109/5.628669
On the Convergence Properties of the EM Algorithm. The Annals of statistics, pp.95-103, 1983. ,
Structure extraction from texture via relative total variation, ACM Transactions on Graphics, vol.31, issue.6, p.31139, 2012. ,
DOI : 10.1145/2366145.2366158
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.295.8478
Implementation of Unsupervised Statistical Methods for Low-Quality Iris Segmentation, 2014 Tenth International Conference on Signal-Image Technology and Internet-Based Systems, pp.566-573, 2014. ,
DOI : 10.1109/SITIS.2014.46
URL : https://hal.archives-ouvertes.fr/hal-01331567
Markov Chains for unsupervised segmentation of degraded NIR iris images for person recognition, Pattern Recognition Letters, vol.82, issue.P2, pp.116-123, 2016. ,
DOI : 10.1016/j.patrec.2016.05.025
URL : https://hal.archives-ouvertes.fr/hal-01390978
Unsupervised multiclass segmentation of SAR images using fuzzy triplet Markov fields model, Pattern Recognition, issue.11, pp.454018-4033, 2012. ,
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm, IEEE Transactions on Medical Imaging, vol.20, issue.1, pp.45-57, 2001. ,
DOI : 10.1109/42.906424
An Accurate Iris Segmentation Framework Under Relaxed Imaging Constraints Using Total Variation Model, 2015 IEEE International Conference on Computer Vision (ICCV), pp.3828-3836, 2015. ,
DOI : 10.1109/ICCV.2015.436
A Robust IRIS Segmentation Procedure for Unconstrained Subject Presentation, 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference, pp.1-6, 2006. ,
DOI : 10.1109/BCC.2006.4341623
33 TABLE DES FIGURES 2.1 Schéma général d'un système de segmentation de l'iris, p.37 ,
96 TABLE DES FIGURES 4.5 Exemples de transformation d'une image de l'iris segmentée en régions en une cha??necha??ne, p.97 ,
Comparaison d'segmentations des images dégradées de l'iris (ICE-2005) par les modèles, p.116 ,
129 TABLE DES FIGURES 5.9 Organigrammes de différents systèmes de reconnaissance de l'iris utilisés dans ce travail, p.132 ,
Segmentation, p.152 ,
Segmentation, p.153 ,