, A battle of three descriptors: SURF, FREAK, and BRISK

R. Alahi, P. Ortiz, and . Vandergheynst, FREAK: Fast Retina Keypoint, IEEE Conference on Computer Vision and Pattern Recognition, 2012.

A. E. Abdel-hakim and A. A. Farag, CSIFT: A-SIFT descriptor with color invariant characteristics, Computer Vision and Pattern Recognition, 2006.

, IEEE, vol.2, pp.1978-1983, 2006.

A. M. Eskicioglu and P. S. Fisher, Image Quality Measures and Their Performance, IEEE Transactions on Communication, vol.43, issue.12, pp.2959-2965, 1995.

, Akhloufi Moulay abdellatif. Reconnaissance des visages par imagerie

. Multispectrale, Thèse présentée à l'université de Laval, 2013.

M. Akhloufi, . Bendada, . Abdelhakim, . Batsale, and . Jean-christophe, State of the art in infrared face recognition, Quantitative InfraRed Thermography Journal, vol.5, issue.1, pp.3-26, 2008.

H. Bay, T. Tuytelaars, and L. V. Gool, SURF: Speeded up robust features, Computer Vision -ECCV 2006: 9th European Conference on Computer Vision, vol.II, pp.404-417, 2006.

. Bay, . Herbert, . Fasel, . Beat, and L. Van-gool, Interactive museum guide: Fast and robust recognition of museum objects, 2006.

D. Bekele, . Teutsch, . Michael, and T. Schuchert, Evaluation of binary keypoint descriptors, 20th IEEE International Conference on. IEEE, pp.3652-3656, 2013.

A. Bendada, . Akhloufi, and A. Moulay, Multispectral face recognition in texture space, CRV 2010 -7th Canadian Conference on Computer and Robot Vision, pp.101-106, 2010.

B. Bhanu, . Govindaraju, and . Venu, Multibiometrics for Human Identification

K. W. Bowyer, K. Chang, and P. Flynn, A survey of approaches to three-dimensional face recognition, Proceedings of the 17th International Conference on. IEEE, pp.358-361, 2004.

. Brodatz, Textures: A Photographic Album for Artists and Designers, 1966.

V. Bruce and A. Young, Understanding face recognition, British journal of psychology, vol.77, pp.305-327, 1986.

P. Buddharaju and I. Pavlidis, Multispectral face recognition: fusion of visual imagery with physiological information. Face biometrics for personal identification, pp.91-108, 2007.

M. J. Burge, . Monaco, and K. Matthew, Multispectral iris fusion for enhancement, interoperability, and cross wavelength matching, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, pp.73341-73341, 2009.

C. Harris and M. Stephens, Alvey Vision Conference, pp.147-151, 1988.

H. Chang, A. Koschan, B. Abidi, and M. Abidi, Fusing continuous spectral images for face recognition under indoor and outdoor illuminants, Mach Vis Appl, vol.21, issue.2, pp.201-215, 2010.

K. I. Chang, K. W. Bowyer, . Et-flynn, and J. Patrick, An evaluation of multimodal 2D+ 3D face biometrics, IEEE transactions on pattern analysis and machine intelligence, vol.27, pp.619-624, 2005.

L. Chen, H. Zheng, L. Li, P. Xie, and S. Liu, Near-infrared dorsal hand vein image segmentation by local thresholding using grayscale morphology, 1st international conference bioinformatics and biomedical engineering, 2007.

R. M. Cormack, A review of classification, Journal of the Royal Statistical Society. Series A (General), pp.321-367, 1971.

D. Zhang, Multispectral Biometrics, 2016.

N. Dalal and B. Triggs, Histograms of oriented gradients for human detection, Computer Vision and Pattern Recognition, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548512

, IEEE Computer Society Conference on. IEEE, pp.886-893, 2005.

P. Dalka and A. Czyzewski, Lip movement and gesture recognition for a multimodal human-computer interface, Computer Science and Information Technology, pp.451-455, 2009.

S. C. Dass, . Nandakumar, . Karthik, . Jain, and K. Anil, A principled approach to score level fusion in multimodal biometric systems, pp.1049-1058, 2005.

J. G. Daugman, Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters, JOSA A, vol.2, issue.7, pp.1160-1169, 1985.

K. Delac and M. Grgic, A survey of biometric recognition methods, Proceedings Elmar. 46th International Symposium. IEEE, pp.184-193, 2004.

L. J. Denes, . Metes, . Peter, and Y. Liu, Hyperspectral face database

, The Robotics Institute, 2002.

E. Deza and M. M. Deza, Dictionary of Distances, 2006.

E. Rublee, . Rabaud, . Vincent, K. Konolige, and G. Bradski, ORB: An efficient alternative to SIFT or SURF, Computer Vision (ICCV), 2011 IEEE international conference on, pp.2564-2571, 2011.

E. Tola, V. Lepetit, and P. Fua, A fast local descriptor for dense matching, IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.

M. Eskandari, Ö. Toygar, . Demirel, and . Hasan, A New Approach for FaceIris Multimodal Biometric Recognition Using Score Fusion, International Journal of Pattern Recognition and Artificial Intelligence, vol.27, p.3, 2013.

G. Prasanna, K. Anandakumar, and A. Bharathi, Multi Modal Biometric Systems: A State of the Art Survey, International Research Journal of Engineering and Technology (IRJET), p.4, 2016.

G. Amirthalingam, R. Radhamani, and . Scholar, A Multimodal Approach for Face and Ear Biometric System, IJCSI International Journal of Computer Science Issues, vol.10, issue.2, 2013.

R. Ghiass, . Shoja, . Arandjelovi?, . Ognjen, . Bendada et al., Infrared face recognition: A comprehensive review of methodologies and databases, Pattern Recognition, vol.47, pp.2807-2824, 2014.

M. Grgic, . Delac, . Kresimir, and S. Grgic, SCface-surveillance cameras face database. Multimedia tools and applications, vol.51, pp.863-879, 2011.

M. Gudavalli, S. Raju, . Viswanadha, A. Babu, and . Vinaya, Multimodal Biometrics--Sources, Architecture and Fusion Techniques: An Overview, Biometrics and Security Technologies (ISBAST), International Symposium on

, IEEE, pp.27-34, 2012.

H. Moravec, Towards automatic visual obstacle avoidance, International Joint Conferences on Arti_cial Intelligence, p.584, 1977.

H. Li, Z. Lin, X. Shen, J. Brandt, and G. Hua, A Convolutional Neural Network Cascade for Face Detection, IEE Conference on Computer Vision and Patern Recognition (CVPR), pp.5325-5334, 2015.

J. Heinly, E. Dunn, and J. Frahm, Comparative evaluation of binary features, Computer Vision-ECCV 2012, pp.759-773, 2012.

H. Chang, A. Koschan, M. Abidi, G. Seong, and . Kong, Chang-Hee Won. Multispectral Visible and Infrared Imaging for Face recognition

, Computer Vision and Pattern Recognition Workshops (CVPRW 08), IEEE Computer Society conference, pp.1-6, 2008.

M. Husken, . Brauckmann, . Michael, . Gehlen, and . Stefan, Strategies and benefits of fusion of 2D and 3D face recognition, Computer Vision and Pattern Recognition-Workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on. IEEE, pp.174-174, 2005.

J. Heo, B. Abidi, S. G. Kong, and M. Abidi, Performance Comparison of Visual and Thermal Signatures for Face Recognition, Biometric Consortium Conference, vol.164, 2003.

A. K. Jain and S. Z. Li, Handbook of face recognition, 2011.

A. K. Jain and U. Park, Facial marks: Soft biometric for face recognition, 16th IEEE International Conference on, 2009.

, IEEE, pp.37-40, 2009.

A. K. Jain, . Dass, C. Sarat, and K. Et-nandakumar, Soft biometric traits for personal recognition systems, Biometric Authentication, pp.731-738, 2004.

A. K. Jain, A. Ross, . Prabhakar, and . Salil, An introduction to biometric recognition, IEEE Transactions on circuits and systems for video technology, vol.14, pp.4-20, 2004.

J. Lu, K. N. Plataniotis, and A. N. Venetsanopoulos, Face Recognition Using LDA Based Algorithms, IEEE transactions on neural networks, 2002.

K. Mikolajczyk and C. Schmid, A performance evaluation of local descriptors, IEEE Pattern Analysis and Machine Intelligence, vol.27, issue.10, pp.1615-630, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548227

K. Mikolajczyk and C. Schmid, Scale & affine invariant interest point detectors, International Journal of Computer Vision, vol.1, issue.60, pp.63-69, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00548554

I. A. Kakadiaris, . Passalis, . Georgios, . Toderici, and . George, 3D Face Recognition. In : BMVC. pp, pp.869-878, 2006.
URL : https://hal.archives-ouvertes.fr/hal-01339319

Y. Ke and R. Sukthankar, PCA-SIFT: A more distinctive representation for local image descriptors, Computer Vision and Pattern Recognition, 2004.

, IEEE, vol.2, pp.506-513, 2004.

M. S. Khalil, D. Muhammad, and Q. Al-nuzaili, Fingerprint verification using the texture of fingerprint image, Second international conference, 2009.

S. G. Kong, . Heo, . Jingu, . Boughorbel, and . Faysal, Multiscale fusion of visible and thermal IR images for illumination-invariant face recognition, International Journal of Computer Vision, vol.71, issue.2, pp.215-233, 2007.

A. Koschan, Y. Yao, H. Chang, and M. Abidi, Multispectral face imaging and analysis. Handbook of face recognition, pp.401-428, 2011.

K. Rao-kakkirala, S. Rao-chalamala, and S. Jami, Thermal Infrared Face Recognition: A review: UKSim-AMSS 19th International Conference on Modelling & Simulation, 2017.

R. Kusum-rani1 and . Sharma, Study of Different Image fusion, Algorithm International Journal of Emerging Technology and Advanced Engineering, vol.3, issue.5, 2013.

C. Le and R. Jain, A survey of biometrics security systems, 2009.

I. Lerman and P. Peter, Indice probabiliste de vraisemblance du lien entre objets quelconques: analyse comparative entre deux approches, vol.51, pp.5-36, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00442578

S. Z. Li and A. Jain, Encyclopedia of biometrics, 2015.

S. Z. Li, R. Chu, . Feng, S. Liao, and . Cai, Illumination invariant face recognition using near-infrared images, IEEE Transactions, vol.29, pp.627-639, 2007.

T. Lindeberg, Detecting salient blob-like image structures and their scales with a scale-space primal sketch: A method for focus-of-attention, International Journal of Computer Vision, vol.11, pp.283-318, 1993.

C. Liton, A. A. Paul, and . Sumam, Face Recognition Using Principal Component Analysis Method, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), vol.1, issue.9, 2012.

L. J. Denes, P. Metes, and Y. Liu, Hyperspectral Face Database, 2002.

M. Calonder, V. Lepetit, C. Strecha, and P. Fua, Brief: Binary robust independent elementary features, Computer Vision-ECCV 2010, pp.778-792, 2010.

M. Kowalski, A. Grudzien, N. Palka, and M. Szustakowski, Face recgnition in termal infrared domain, Proc. SPIE 10441, Counterterrorisme, Crime Fighting, Forensics, and Surveillance technologies 1044109, 2017.

M. Petrou and P. G. Sevilla, Image Processing: Dealing with Texture, 2006.

M. Smith and J. Brady, Susan -a new approach to low level image processing, International Journal of Computer Vision, vol.23, pp.45-78, 1997.

M. Tuceryan and K. Jain, Texture analysis

. Pau, The handbook of pattern recognition and Computer vision, 1998.

E. Mair, G. D. Hager, and D. Burschka, Adaptive and generic corner detection based on the accelerated segment test, European conference on Computer vision, pp.183-196, 2010.

S. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.7, pp.674-693, 1989.

M. Ahlawat and C. Kant, An Introduction to Multimodal Biometric System: An Overview, IJSRD -International Journal for Scientific Research & Development|, vol.3, 2015.

B. B. Mandelbrot and . Fractals, , 1977.

S. Manhal, . Almohammad, I. Gouda, T. A. Salama, and . Mahmoud, Face and Gait Fusion Methods: A Survey, International Journal of Computer Science and Telecommunications, vol.4, issue.4, 2013.

M. Mustikasari and S. Madenda, Texture Based Image Retrieval Using GLCM and Image Sub-Block, IJARCSSE, vol.5, 2015.

R. Miezianko, Terravic research infrared database, IEEE OTCBVS WS Series Bench, 2005.

K. Mikolajczyk and C. Schmid, A performance evaluation of local descriptors, IEEE transactions on pattern analysis and machine intelligence, vol.27, pp.1615-1630, 2005.
URL : https://hal.archives-ouvertes.fr/inria-00548227

K. Mikolajczyk and C. Schmid, Scale & affine invariant interest point detectors, International journal of computer vision, vol.60, issue.1, pp.63-86, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00548554

A. H. Mir, S. Rubab, and Z. A. Et-jhat, Biometrics verification: a literature survey, International Journal of Computing and ICT Research, vol.5, issue.2, pp.67-80, 2011.

A. Mishra, Multimodal biometrics it is: need for future systems, International Journal of Computer Applications, vol.3, pp.28-33, 2010.

M. Soltane, N. Doghmane, and N. Guersi, Face and Speech Based Multi-Modal Biometric Authentication, International Journal of Advanced Science and Technology, vol.21, issue.8, pp.41-46, 2010.

P. Montesinos, . Gouet, . Valérie, and R. Deriche, Differential invariants for color images, Proceedings. Fourteenth International Conference on. IEEE, pp.838-840, 1998.

J. M. Morel and G. Yu, ASIFT: A new framework for fully affine invariant image comparison, SIAM Journal on Imaging Sciences, vol.2, issue.2, pp.438-469, 2009.

E. N. Mortensen, H. Deng, and L. Shapiro, A SIFT descriptor with global context, Computer Vision and Pattern Recognition (CVPR 2005, vol.1, pp.184-190, 2005.

R. Muhammad-imran-razzak, M. Yusof, and . Khalid, Multimodal face and finger veins biometric authentication, Scientific Research and Essays, vol.5, issue.17, pp.2529-2534, 2010.

N. Prakash and D. Singh, Support Vector Machines for Face Recognition, International Research Journal of Engineering and Technology (IRJET), pp.1517-1529, 2015.

A. V. Nefian, . Hayes, and H. Monson, Hidden Markov models for face recognition, Proceedings of the 1998 IEEE International Conference on, pp.2721-2724, 1998.

S. Noushath, M. Imran, K. Jetly, A. Rao, and G. Hemantha-kumar, Multimodal biometric fusion of face and palmprint at various levels, Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013, pp.1793-1798, 2013.
DOI : 10.1109/icacci.2013.6637453

T. Ojala, M. Pietikäinen, and D. Harwood, A comparative study of texture measures with classification based on featured distributions, Pattern recognition, vol.29, issue.1, pp.51-59, 1996.

P. Orssén, Maximally stable colour regions for recognition and matching, Computer Vision and Pattern Recognition, pp.1-8, 2007.

P. Latha, .. L. Dr, .. S. Ganesan-&-dr, and . Annadurai, Face Recognition using Neural Networks, Signal Processing: An International Journal (SPIJ), issue.3, pp.153-160, 2009.

S. Palanivel, . Jain, K. Anil, L. Hong, and Y. Kulkarni, A multimodal biometric system using fingerprint, face and speech, Proceedings of 2nd Int'l Conference on Audio-and Video-based Biometric Person Authentication, pp.182-187, 1999.

P. Buyssens and M. Revenu, IR and visible face identification via sparse representation, Biometrics Theory Applications and Systems (BTAS), pp.1-6, 2010.
DOI : 10.1109/btas.2010.5634466
URL : https://hal.archives-ouvertes.fr/hal-00805773

C. Pohl and J. L. Et-van-genderen, Review article multisensor image fusion in remote sensing: concepts, methods and applications, International journal of remote sensing, vol.19, issue.5, pp.823-854, 1998.
DOI : 10.1080/014311698215748
URL : https://www.tandfonline.com/doi/pdf/10.1080/014311698215748?needAccess=true

P. Database,

R. Galloway and M. M. , Texture analysis using grey level run lengths, vol.75, 1974.
DOI : 10.1016/s0146-664x(75)80008-6

R. M. Haralick, K. Shanmugam, and I. Dinstein, Textural features for image classification, IEEE Trans. System Man. Cybernetics, vol.3, pp.610-621, 1973.
DOI : 10.1109/tsmc.1973.4309314
URL : http://www.cis.rit.edu/~cnspci/references/dip/segmentation/haralick1973.pdf

R. Gross, Face Databases. The Robotics Inistitute, Carnegie Mellon University, 2005.
DOI : 10.1007/0-387-27257-7_14

R. Kimmel, C. Zhang, A. M. Bronstein, and M. M. ,

. Bronstein, Are MSER features really interesting?, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, pp.2316-2320, 2011.

A. A. Ross, K. Et-nandakumar, and K. , Information fusion in biometrics. Handbook of Multibiometrics, pp.37-58, 2006.
DOI : 10.1007/3-540-45344-x_52

A. Ross, . Jain, and K. Anil, Multimodal biometrics: An overview, Signal Processing Conference, pp.1221-1224, 2004.

E. Rosten, R. Porter, and T. Drummond, Faster and better: A machine learning approach to corner detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.32, issue.1, pp.105-119, 2010.
DOI : 10.1109/tpami.2008.275
URL : http://arxiv.org/pdf/0810.2434

R. K. Rowe, U. Uludag, M. Demirkus, S. Parthasaradhi, and A. K. Jain, A multispectral whole-hand biometric authentication system, Biometrics Symposium, pp.1-6, 2007.
DOI : 10.1109/bcc.2007.4430532
URL : http://biometrics.cse.msu.edu/Publications/Multibiometrics/RoweEtalMultispectralHandBSYM2007.pdf

S. Leutenegger, M. Chli, and R. Siegwart, Brisk: Binary robust invariant scalable keypoints, 2011.
DOI : 10.1109/iccv.2011.6126542

S. Prabhakar, S. Pankanti, and A. K. Jain, Biometric Recognition: Security and Privacy Concerns, IEEE Security & Privacy Magazine, vol.1, issue.2, pp.33-42, 2003.

S. Sharma, Template Matching Approach for Face Recognition System, International Journal of Signal Processing Systems, vol.1, issue.2, 2013.

S. Santini and R. Et-jain, Similarity Measures, IEEE Trans. on PAMI, vol.12, issue.9, pp.871-883, 1999.

G. Seong, J. Kong, . Heo, R. Besma, J. Abidi et al., Recent advances in visual and infrared face recognition :a review, Computer Vision and Image Understanding, vol.97, pp.103-135, 2005.

M. K. Shahin, A. M. Badawi, and M. E. Rasmy, A multimodal hand vein, hand geometry, and fingerprint prototype design for high security biometrics, 2008.

, Cairo International Biomedical Engineering Conference, 2008.

S. Mitra, Gaussian Mixture Models for Human Face Recognition under Illumination Variations, Applied Mathematics, pp.2071-2079, 2012.

P. H. Sneath and R. R. Sokal, Numerical taxonomy. The principles and practice of numerical classification, 1973.

D. A. Socolinsky, Illumination invariant face recognition using thermal infrared imagery, Proceedings of the 2001 IEEE Computer Society Conference on, 2001.

A. Souhila-guerfi, Thèse : Authentification d'individus par reconnaissance de caractéristiques biométriques liées aux visages 2D/3D. Université d'Evry Val d'Essonne, pp.37-54, 2008.

S. Cha, Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions, vol.4, pp.300-307, 2007.

S. Nair, B. Elias, and V. Naidu, Pixel Level Image Fusion: A NeuroFuzzy Approach, International Journal of Computer Science and Business Informatics, vol.12, issue.1, pp.71-86, 2014.

T. Tuytelaars and L. Van-gool, IBR & EBR: Matching widely separated views based on affine invariant regions, In IJCV, vol.59, issue.1, pp.61-85, 2004.

V. P. Naidu, Image Fusion Technique using Multi-resolution Singular Value Decomposition, Defense Science Journal, vol.61, issue.5, pp.479-484, 2011.

V. P. Naidu and J. R. , Pixel-level Image Fusion using Wavelets and Principal Component Analysis, Defense Science Journal, vol.58, issue.3, pp.338-352, 2008.

. Wang, . Shangfei, . Liu, . Zhilei, . Lv et al., A natural visible and infrared facial expression database for expression recognition and emotion inference, IEEE Transactions on Multimedia, vol.12, issue.7, pp.682-691, 2010.

T. Wark and S. Et-sridharan, Adaptive fusion of speech and lip information for robust speaker identification, Digital Signal Processing, vol.11, pp.169-186, 2001.

J. Wilder, P. Phillips, . Jonathon, . Jiang, and . Cunhong, Comparison of visible and infra-red imagery for face recognition, Proceedings of the Second International Conference on, pp.182-187, 1996.

J. Wu, . Cui, . Zhiming, and V. S. Sheng, A Comparative Study of SIFT and its Variants, Measurement Science Review, vol.13, pp.122-131, 2013.

C. Yang, J. Zhang, X. Wang, and X. Liu, A Novel Similarity Based Quality Metric for Image Fusion, Inf. Fusion, vol.9, issue.2, pp.156-160, 2008.

C. You, Y. Liu, B. Zhao, and S. Yang, An Objective Quality Metric for Image Fusion based on Mutual Information and Muti-scale Structural Similarity, vol.9, pp.1050-1054, 2014.

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, Image quality assessment: from error visibility to structural similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004.

. Zhang, . Baochang, . Zhang, . Lei, . Zhang et al., Directional binary code with application to PolyU near-infrared face database, Pattern Recognition Letters, vol.31, pp.2337-2344, 2010.

W. Zhao, . Chellappa, . Rama, P. Phillips, and . Jonathon, Face recognition: A literature survey, ACM computing surveys (CSUR), vol.35, pp.399-458, 2003.

, Liste des tableaux, p.-IX

, Liste des figures, p.-X

, Liste des abréviations, pp.1-1

, 5-Organisation de la thèse, p.3

, 1.1. Fondamentaux de la, p.5

, 1.1.1. Architecture générale, p.6

, 2. Biométries monomodales, p.7

, 1.2.3.1. Avantages des systèmes mono-biométriques, p.8

, Limites des systèmes mono-biométriques, p.8

, Différentes modalités biométriques, p.9

, 1.2.1. Motivation de la biométrie de, p.10

, 2. Méthodes locales, p.11

, 3. Méthodes globales, p.13

, 1.4.1. Notion d'images multispectrales, p.16

, Notion de biométrie, p.18

, Applications de la biométrie multispectrale, p.19

, Bases de données multispectrales, p.21

, Reconnaissance de visage et biométrie multimodale, p.24

, Reconnaissance de visage, pp.3-27

, Mesure de performance d'un système biométrique, p.28

, Chapitre 2. Reconnaissance de visage multispectrale basée sur une extraction hybride de caractéristiques (MS-FRHF), p.31

, Notion d'extraction de caractéristiques, p.31

, 2.1.1. Points d'intérêt, p.32

, 2.2.1. Extraction de points d, Méthodes d'extraction de caractéristiques, p.33

, Méthodes d'extraction de points d'intérêt, p.34

, Extraction de texture basée sur les statistiques du second ordre, p.41

, Statistiques d'ordre supérieur, p.42

, Filtres de Gabor, p.43

, Local Binary Patern (LBP), p.43

M. S. Méthode, FRHF proposée pour l'extraction de caractéristiques en reconnaissance de visage, p.44

, 2.3.2. Reconnaissance de visage dans le visible et l'infrarouge thermique, p.45

, Fusion d'images, p.46

, Fusion d'images visible/infrarouge, p.47

, Processus de fusion d'images visible/infrarouge, p.47

, Description de la base de données, p.51

, Extraction de caractéristique par la méthode MS-FRHF, p.52

, Chapitre 3. Reconnaissance de visage multispectrale à l'aide de caractéristiques binaires, p.57

, Présentation de détecteurs et descripteurs binaires, p.58

, Méthodes basées sur les caractéristiques locales, p.58

, Fonctionnement des détecteurs et descripteurs binaires, p.58

, Méthode proposée pour la reconnaissance de visage multispectrale à l'aide de détecteurs et de descripteurs binaires, p.67

, Présentation de FREAK, p.71

, Présentation du détecteur Harris, p.73

, 5 Présentation de SURF, p.73

, Base de données d'images, p.75

, Fusion d'images, p.75

, Extraction de caractéristiques, p.76

, Reconnaissance de visage multispectrale à l'aide de score de similarité, p.82

, Approches de comparaison d'objets, p.83

, Motivation de l'utilisation des scores de similarité, p.83

, Mesures de similarité appliquées aux images, p.85

, Applications des mesures de similarité, p.86

, Introduction à la notion de similarité, p.88

, Famille des distances L p Minkowski, p.90

, Famille des distances L, pp.1-91

, Famille des distances d'intersections, p.91

, Famille des distances de produit, p.91

, Famille des distances de la corde au carré, p.92

, Famille des distances d'entropie de Shannon, p.93

, Méthode proposée pour l'étude de similarité, p.94

, Corrélation et fusion d'images, p.94

, Conclusion générale et perspectives, p.103

, Table des matières, p.117