T. Ng, s o nb e t w e e nd i ff e r e n td e s c r i p t o r so, p.2

Y. Rui, T. S. Huang, and S. Chang, Image Retrieval: Current Techniques, Promising Directions, and Open Issues, Journal of Visual Communication and Image Representation, vol.10, issue.1, pp.39-62, 1999.
DOI : 10.1006/jvci.1999.0413

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

H. Tamura and N. Yokoya, Image database systems: A survey, Pattern Recognition, vol.17, issue.1, pp.29-43, 1984.
DOI : 10.1016/0031-3203(84)90033-5

S. Chang and A. Hsu, Image information systems: where do we go from here?, IEEE Transactions on Knowledge and Data Engineering, vol.4, issue.5, pp.431-442, 1992.
DOI : 10.1109/69.166986

J. Z. Wang, N. Boujemaa, A. Del-bimbo, D. Geman, A. G. Hauptmann et al., Diversity in multimedia information retrieval research, Proceedings of the 8th ACM international workshop on Multimedia information retrieval , MIR '06, pp.5-12, 2006.
DOI : 10.1145/1178677.1178681

J. Smith and S. Chang, Visually searching the Web for content, IEEE Multimedia, vol.4, issue.3, pp.12-20, 1997.
DOI : 10.1109/93.621578

S. Sclaroff, L. Taycher, and M. Lacascia, ImageRover: a content-based image browser for the World Wide Web, 1997 Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries, 1997.
DOI : 10.1109/IVL.1997.629714

. Google, Google image search

I. Ahmad, S. Abdullah, S. Kiranyaz, and M. Gabbouj, Content-based image retrieval on mobile devices, Proc. SPIE 5684, Multimedia on Mobile Devices, pp.255-264, 2005.

M. L. Cascia, M. Morana, and S. Sorce, Mobile Interface for Content-Based Image Management, 2010 International Conference on Complex, Intelligent and Software Intensive Systems, 2010.
DOI : 10.1109/CISIS.2010.172

M. Ortega, Y. Rui, K. Chakrabarti, S. Mehrotra, and T. S. Huang, Supporting similarity queries in MARS, Proceedings of the fifth ACM international conference on Multimedia , MULTIMEDIA '97, pp.403-413, 1997.
DOI : 10.1145/266180.266394

A. Lumini and D. Maio, Haruspex: an image database system for query-byexamples, Pattern Recognition Proceedings. 15th International Conference on, pp.258-261, 2000.

H. Müller, N. Michoux, D. Bandon, and A. Geissbuhler, A review of content-based image retrieval systems in medical applications???clinical benefits and future directions, International Journal of Medical Informatics, vol.73, issue.1, pp.1-23, 2004.
DOI : 10.1016/j.ijmedinf.2003.11.024

H. Cho, L. Hadjiiski, B. Sahiner, H. Chan, C. Paramagul et al., Interactive content-based image retrieval (CBIR) computer-aided diagnosis (CADx) system for ultrasound breast masses using relevance feedback, Medical Imaging 2012: Computer-Aided Diagnosis
DOI : 10.1117/12.912164

P. M. Kelly, T. M. Cannon, and D. R. Hush, Query by image example: the comparison algorithm for navigating digital image databases (candid) approach, Proc

S. Aksoy and R. Haralick, Probabilistic vs. geometric similarity measures for image retrieval, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), pp.357-362, 2000.
DOI : 10.1109/CVPR.2000.854847

H. Peng and S. Chen, Trademark shape recognition using closed contours, Pattern Recognition Letters, vol.18, issue.8, pp.791-803, 1997.
DOI : 10.1016/S0167-8655(97)00050-0

P. Yin and C. Yeh, Content-based retrieval from trademark databases, Pattern Recognition Letters, vol.23, issue.1-3, pp.113-126, 2002.
DOI : 10.1016/S0167-8655(01)00091-5

J. Schietse, J. P. Eakins, and R. C. Veltkamp, Practice and challenges in trademark image retrieval An effective solution for trademark image retrieval by combining shape description and feature matching, Proceedings of the 6th ACM international conference on Image and video retrieval, pp.518-524, 2007.

W. Wang, C. Wei, L. Zhang, and X. Wang, Traffic-signs recognition system based on multi-features, 2012 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings, pp.120-123, 2012.
DOI : 10.1109/CIMSA.2012.6269599

Z. Geradts, Content-based information retrieval from forensic image databases, 2002.

Y. Lee, U. Park, A. K. Jain, and S. Lee, Pill-ID: Matching and retrieval of drug pill images, Pattern Recognition Letters, vol.33, issue.7, pp.904-910, 2012.
DOI : 10.1016/j.patrec.2011.08.022

A. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, Content-based image retrieval at the end of the early years Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.22, pp.1349-1380, 2000.

M. S. Lew, N. Sebe, C. Djeraba, and R. Jain, Content-based multimedia information retrieval, ACM Transactions on Multimedia Computing, Communications, and Applications, vol.2, issue.1
DOI : 10.1145/1126004.1126005

Y. Liu, D. Zhang, G. Lu, and W. Ma, A survey of content-based image retrieval with high-level semantics, Pattern Recognition, vol.40, issue.1, pp.262-282, 2007.
DOI : 10.1016/j.patcog.2006.04.045

R. Datta, D. Joshi, J. Li, and J. Z. Wang, Image retrieval, ACM Computing Surveys, vol.40, issue.2, pp.1-560, 2008.
DOI : 10.1145/1348246.1348248

G. Rafiee, S. Dlay, and W. Woo, A review of content-based image retrieval, Communication Systems Networks and Digital Signal Processing (CSNDSP), 2010 7th International Symposium on, pp.775-779, 2010.

M. Yang, Shaped-based feature extraction and similarity matching.T h e s e ,I N S Ad e Rennes, 2008.

T. Mäenpää and M. Pietikäinen, Classification with color and texture: jointly or separately?, Pattern Recognition, vol.37, issue.8, pp.1629-1640, 2004.
DOI : 10.1016/j.patcog.2003.11.011

T. Deselaers, D. Keysers, and H. Ney, Features for image retrieval: an experimental comparison, Information Retrieval, vol.3, issue.2, pp.77-107, 2008.
DOI : 10.1007/s10791-007-9039-3

O. A. Penatti, E. Valle, R. Da, and S. Torres, Comparative study of global color and texture descriptors for web image retrieval, Journal of Visual Communication and Image Representation, vol.23, issue.2, pp.359-380, 2012.
DOI : 10.1016/j.jvcir.2011.11.002

G. Strang, The Discrete Cosine Transform, SIAM Review, vol.41, issue.1, pp.135-147, 1999.
DOI : 10.1137/S0036144598336745

B. Shen, From 8-tap dct to 4-tap integer-transform for mpeg to h.264/avc transcoding, Image Processing International Conference on, pp.115-118, 2004.

I. Daubechies, Ten lectures on wavelets, 1992.

S. Mallat, APPLIED MATHEMATICS MEETS SIGNAL PROCESSING, Challenges for the 21st Century, pp.319-338, 1998.
DOI : 10.1142/9789812811264_0006

S. W. James, A Primer on Wavelets and their scientific Appliactions Second edition, 2007.

A. Cohen, I. Daubechies, and J. Feauveau, Biorthogonal bases of compactly supported wavelets, Communications on Pure and Applied Mathematics, vol.10, issue.5, pp.485-560, 1992.
DOI : 10.1002/cpa.3160450502

M. Unser and T. Blu, Mathematical properties of the jpeg2000 wavelet filters, IEEE Transactions on Image Processing, vol.12, issue.9, pp.1080-1090, 2003.
DOI : 10.1109/TIP.2003.812329

S. Siggelkow, Feature histograms for content based image retrieval.P h D t h e s i s, 2002.

A. K. Jain, Data clustering: 50 years beyond K-means, Pattern Recognition Letters, vol.31, issue.8, pp.651-666, 2010.
DOI : 10.1016/j.patrec.2009.09.011

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

P. Andritsos, Data clustering techniques, Dep. of Computer Science, vol.1, issue.1, pp.3-5, 2002.

P. Drineas, A. Frieze, R. Kannan, S. Vempala, V. Vinay et al., Clustering Large Graphs via the Singular Value Decomposition, Machine Learning, vol.56, issue.1-3, pp.9-33, 1985.
DOI : 10.1023/B:MACH.0000033113.59016.96

C. A. Sugar, L. A. Lenert, and R. A. Olshen, An application of cluster analysis to health services research: Empirically defined health states for depression from the sf-12, 1999.

R. Tibshirani, G. Walther, and T. Hastie, Estimating the number of clusters in a data set via the gap statistic, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.2, pp.411-423, 2001.
DOI : 10.1111/1467-9868.00293

J. Wright, Y. Ma, J. Mairal, G. Sapiro, T. Huang et al., Sparse Representation for Computer Vision and Pattern Recognition, Proceedings of the IEEE, vol.98, issue.6, pp.1031-1044, 2010.
DOI : 10.1109/JPROC.2010.2044470

D. Lee and H. Seung, Learning the parts of objects by nonnegative matrix factorization, Nature, vol.401, pp.788-791, 1999.

R. Tibshirani, Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society. Series B, pp.267-288, 1996.

J. Mairal, F. Bach, J. Ponce, and G. Sapiro, Online learning for matrix factorization and sparse coding, Journal of Machine Learning Research, vol.11, pp.19-60, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00408716

B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, Least angle regression, Annals of Statistics, vol.32, pp.407-499, 2004.

J. Mairal, F. Bach, and J. Ponce, SPArse Modeling Software, 2011.

Y. Rubner, Perceptual Metrics For Image Database Navigation, 1999.
DOI : 10.1007/978-1-4757-3343-3

M. Swain and D. Ballard, Color indexing, International Journal of Computer Vision, vol.31, issue.1, pp.11-32, 1991.
DOI : 10.1007/BF00130487

S. Kullback, Information theory and statistics, 1968.

C. Faloutsos, R. Barber, M. Flickner, J. Hafner, W. Niblack et al., Efficient and effective Querying by Image Content, Journal of Intelligent Information Systems, vol.2, issue.6, pp.231-262, 1994.
DOI : 10.1007/BF00962238

Y. Rubner and C. Tomasi, Perceptual Metrics for Image Database Navigation.N o r well, 2001.

Y. Rubner, C. Tomasi, and L. J. Guibas, The earth mover's distance as a metric for image retrieval, International Journal of Computer Vision, vol.40, issue.2, pp.99-121, 2000.
DOI : 10.1023/A:1026543900054

R. Picard, T. Kabir, and F. Liu, Real-time recognition with the entire Brodatz texture database, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp.638-639, 1993.
DOI : 10.1109/CVPR.1993.341050

S. Krishnamachari and M. , Color compact descriptor for fast image and video segment retrieval, Storage and Retrieval for Media Databases'00, pp.581-589, 2000.

R. Bolle, S. Pankanti, and N. Ratha, Evaluation techniques for biometrics-based authentication systems (FRR), Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, pp.831-837, 2000.
DOI : 10.1109/ICPR.2000.906204

Z. M. Hafed and M. D. Levine, Face recognition using the discrete cosine transform, International Journal of Computer Vision, vol.43, issue.3, pp.167-188, 2001.
DOI : 10.1023/A:1011183429707

D. Ramasubramanian and Y. Venkatesh, Encoding and recognition of faces based on the human visual model and DCT, Pattern Recognition, vol.34, issue.12, pp.2447-2458, 2001.
DOI : 10.1016/S0031-3203(00)00172-2

S. Dabbaghchian, M. P. Ghaemmaghami, and A. Aghagolzadeh, Feature extraction using discrete cosine transform and discrimination power analysis with a face recognition technology, Pattern Recognition, vol.43, issue.4, pp.1431-1440, 2010.
DOI : 10.1016/j.patcog.2009.11.001

M. Shneier and M. , Exploiting the jpeg compression scheme for image retrieval Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.18, pp.849-853, 1996.

A. Nefian, I. Hayes, and M. H. , Hidden Markov models for face recognition, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), pp.2721-2724, 1998.
DOI : 10.1109/ICASSP.1998.678085

S. Eickeler, S. Müller, and G. , Recognition of JPEG compressed face images based on statistical methods, Image and Vision Computing, vol.18, issue.4, pp.279-287, 2000.
DOI : 10.1016/S0262-8856(99)00055-4

D. Zhong and I. Defee, Pattern recognition in compressed dct domain Bibliography [70] D. Zhong and I. Defée, " DCT histogram optimization for image database retrieval, Image Processing ICIP '04. 2004 International Conference on, pp.2031-2034, 2004.

G. Feng and J. Jiang, JPEG compressed image retrieval via statistical features, Pattern Recognition, vol.36, issue.4, pp.977-985, 2003.
DOI : 10.1016/S0031-3203(02)00114-0

T. Tsai, Y. Huang, and T. Chiang, Image Retrieval Based on Dominant Texture Features, 2006 IEEE International Symposium on Industrial Electronics, pp.441-446, 2006.
DOI : 10.1109/ISIE.2006.295635

P. Poursistani, H. Nezamabadi-pour, R. A. Moghadam, and M. Saeed, Image indexing and retrieval in JPEG compressed domain based on vector quantization, Mathematical and Computer Modelling, vol.57, issue.5-6, 2011.
DOI : 10.1016/j.mcm.2011.11.064

A. Vellaikal and C. Kuo, Joint spatial-spectral indexing for image retrieval, Proceedings of 3rd IEEE International Conference on Image Processing, pp.8-14, 1996.
DOI : 10.1109/ICIP.1996.560895

C. Ngo, T. Pong, and R. T. Chin, Exploiting image indexing techniques in DCT domain, Pattern Recognition, vol.34, issue.9, pp.1841-1851, 2001.
DOI : 10.1016/S0031-3203(00)00111-4

C. Theoharatos, V. Pothos, G. Economou, and S. Fotopoulos, Compressed Domain Image Indexing and Retrieval Based on the Minimal Spanning Tree, 2005 IEEE International Conference on Multimedia and Expo, pp.1516-1519, 2005.
DOI : 10.1109/ICME.2005.1521721

C. Theoharatos, V. Pothos, N. Laskaris, G. Economou, and S. Fotopoulos, Multivariate image similarity in the compressed domain using statistical graph matching, Pattern Recognition, vol.39, issue.10, pp.1892-1904, 2006.
DOI : 10.1016/j.patcog.2006.04.015

Z. Lu and H. Burkhardt, A content-based image retrieval scheme in jpeg compressed domain, International Journal of Innovative Computing, Information and Control, vol.2, pp.831-839, 2006.

D. Zhong, Image database retrieval methods based on feature histograms Tampereen teknillinen yliopisto, 2008.

G. Tech, GTF database

M. Do and M. Vetterli, Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance, IEEE Transactions on Image Processing, vol.11, issue.2, pp.146-158, 2002.
DOI : 10.1109/83.982822

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

M. Kokare, P. Biswas, and B. Chatterji, Texture Image Retrieval Using New Rotated Complex Wavelet Filters, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.35, issue.6, pp.1168-1178, 2005.
DOI : 10.1109/TSMCB.2005.850176

R. Kwitt and A. Uhl, Lightweight Probabilistic Texture Retrieval, IEEE Transactions on Image Processing, vol.19, issue.1, pp.241-253, 2010.
DOI : 10.1109/TIP.2009.2032313

P. Phillips, H. Moon, S. Rizvi, and P. Rauss, The FERET evaluation methodology for face-recognition algorithms Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.22, pp.1090-1104, 2000.

Y. Stitou, N. Lasmar, and Y. Berthoumieu, Copulas based multivariate gamma modeling for texture classification, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009.
DOI : 10.1109/ICASSP.2009.4959766

URL : https://hal.archives-ouvertes.fr/hal-00399615

L. Bombrun, Y. Berthoumieu, N. Lasmar, and G. Verdoolaege, Multivariate texture retrieval using the geodesic distance between elliptically distributed random variables, 2011 18th IEEE International Conference on Image Processing, pp.3637-3640, 2011.
DOI : 10.1109/ICIP.2011.6116506

URL : https://hal.archives-ouvertes.fr/hal-00661686

A. Jain and G. Healey, A multiscale representation including opponent color features for texture recognition, IEEE Transactions on Image Processing, vol.7, issue.1, pp.124-128, 1998.
DOI : 10.1109/83.650858

C. L. Xu and X. T. Zhen, Chromatic statistical landscape features for retrieval of color textured images Library-based coding: a representation for efficient video compression and retrieval, Internet Computing for Science and Engineering (ICI- CSE) Fourth International Conference on Data Compression Conference DCC '97. Proceedings, pp.98-101, 1997.

N. Vasconcelos and A. Lippman, A unifying view of image similarity, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, pp.38-41, 2000.
DOI : 10.1109/ICPR.2000.905271

N. Vasconcelos and A. Lippman, A probabilistic architecture for content-based image retrieval, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), 2000.
DOI : 10.1109/CVPR.2000.855822

G. Verdoolaege, S. De-backer, and P. Scheunders, Multiscale colour texture retrieval using the geodesic distance between multivariate generalized Gaussian models, 2008 15th IEEE International Conference on Image Processing, pp.169-172, 2008.
DOI : 10.1109/ICIP.2008.4711718

R. Kwitt, P. Meerwald, and A. Uhl, Efficient Texture Image Retrieval Using Copulas in a Bayesian Framework, IEEE Transactions on Image Processing, vol.20, issue.7, pp.2063-2077, 2011.
DOI : 10.1109/TIP.2011.2108663

T. Chen, K. Ma, and L. Chen, Discrete wavelet frame representations of color texture features for image query, Multimedia Signal Processing, pp.45-50, 1998.

T. Yumin and M. Lixia, Image retrieval based on multiple features using wavelet, Computational Intelligence and Multimedia Applications, 2003.

S. Liapis and G. Tziritas, Color and Texture Image Retrieval Using Chromaticity Histograms and Wavelet Frames, IEEE Transactions on Multimedia, vol.6, issue.5, pp.676-686, 2004.
DOI : 10.1109/TMM.2004.834858

Y. D. C-h-u-n, N. C. , and D. H. , C o n t e n t -b a s e di m a g er e t r i e v a lu s i n gm u l tiresolution color and texture features, Multimedia, IEEE Transactions on, vol.10, pp.1073-1084, 2008.

A. Vedaldi and B. Fulkerson, Vlfeat, Proceedings of the international conference on Multimedia, MM '10, 2008.
DOI : 10.1145/1873951.1874249

G. J. Burghouts and J. Geusebroek, Material-specific adaptation of color invariant features, Pattern Recognition Letters, vol.30, issue.3, pp.306-313, 2009.
DOI : 10.1016/j.patrec.2008.10.005

I. De, R. Service-des-formations, A. Du, R. Sur-la-reproduction-titre-de-la-thèse-philippe-monsieur, K. Joseph-monsieur et al., lmage analysis for content based image retrieval in transform domain Nom Prénom de l'auteur: BAI CONG Membres du jury : -Monsieur CARRE