A. C. Bovik, M. Clark, and W. S. Geisler, Multichannel texture analysis using localized spatial filters, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, issue.1, pp.55-73, 1990.
DOI : 10.1109/34.41384

S. Bres, ContributionsàContributions`Contributionsà la quantification des critères de transparence et d'anisotropie par une approche globale: application au contrôle de qualité de matériaux composites, 1994.

C. H. Chen, L. F. Pau, and P. Wang, Texture analysis in The Handbook of Pattern Recognition and Computer Vision, 1998.

J. Chen, H. Cao, R. Prasad, A. Bhardwaj, and P. Natarajan, Gabor features for offline Arabic handwriting recognition, Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, DAS '10, pp.53-58, 2010.
DOI : 10.1145/1815330.1815337

K. Ding, Z. Liu, L. Jin, and X. Zhu, A comparative study of Gabor feature and gradient feature for handwritten chinese character recognition, ICWAPR, pp.1182-1186, 2007.

V. Eglin, S. Bres, and C. Rivero, Hermite and Gabor transforms for noise reduction and handwriting classification in ancient manuscripts, International Journal of Document Analysis and Recognition (IJDAR), vol.33, issue.3, pp.101-122, 2007.
DOI : 10.1007/s10032-007-0039-z

E. B. Fowlkes and C. L. Mallows, A Method for Comparing Two Hierarchical Clusterings, Journal of the American Statistical Association, vol.66, issue.383, pp.553-569, 1983.
DOI : 10.1080/01621459.1983.10478008

D. Gabor, Theory of communication Part 1: The analysis of information Journal of the Institution of Electrical Engineers -Part III: Radio and Communication Engineering, pp.429-441, 1946.

R. Haralick, K. Shanmugam, and I. Dinstein, Textural Features for Image Classification, SMC, pp.610-621, 1973.
DOI : 10.1109/TSMC.1973.4309314

A. K. Jain and S. Bhattacharjee, Text segmentation using gabor filters for automatic document processing, Machine Vision and Applications, vol.26, issue.6, pp.169-184, 1992.
DOI : 10.1007/BF02626996

A. K. Jain and Y. Zhong, Page segmentation using texture analysis, Pattern Recognition, vol.29, issue.5, pp.743-770, 1996.
DOI : 10.1016/0031-3203(95)00131-X

N. Journet, J. Ramel, R. Mullot, and V. Eglin, Document image characterization using a multiresolution analysis of the texture: application to old documents, International Journal of Document Analysis and Recognition (IJDAR), vol.52, issue.6, pp.9-18, 2008.
DOI : 10.1007/s10032-008-0064-6

URL : https://hal.archives-ouvertes.fr/hal-00480087

B. Julesz, Visual Pattern Discrimination, Information Theory, pp.84-92, 1962.
DOI : 10.1109/TIT.1962.1057698

L. Kaufman and P. J. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis, 1990.
DOI : 10.1002/9780470316801

D. J. Ketchen and C. L. Shook, THE APPLICATION OF CLUSTER ANALYSIS IN STRATEGIC MANAGEMENT RESEARCH: AN ANALYSIS AND CRITIQUE, Strategic Management Journal, vol.17, issue.6, pp.441-458, 1996.
DOI : 10.1002/(SICI)1097-0266(199606)17:6<441::AID-SMJ819>3.0.CO;2-G

S. Khedekar, V. Ramanaprasad, S. Setlur, and V. Govindaraju, Text -image separation in Devanagari documents, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings., pp.1265-1269, 2003.
DOI : 10.1109/ICDAR.2003.1227861

D. E. Knuth, The art of computer programming) sorting and searching, 1997.

H. P. Lai, M. Visani, A. Boucher, and J. M. Ogier, An experimental comparison of clustering methods for content-based indexing of large image databases, Pattern Analysis and Applications, vol.78, issue.336, pp.345-366, 2012.
DOI : 10.1007/s10044-011-0261-7

URL : https://hal.archives-ouvertes.fr/hal-00859304

F. Lalys, C. Haegelen, M. Mehri, S. Drapier, M. Vérin et al., Anatomo-clinical atlases correlate clinical data and electrode contact coordinates: Application to subthalamic deep brain stimulation, Journal of Neuroscience Methods, vol.212, issue.2, pp.297-307, 2013.
DOI : 10.1016/j.jneumeth.2012.11.002

URL : https://hal.archives-ouvertes.fr/inserm-00750921

G. N. Lance and W. T. Williams, A General Theory of Classificatory Sorting Strategies: 1. Hierarchical Systems, The Computer Journal, vol.9, issue.4, pp.373-380, 1967.
DOI : 10.1093/comjnl/9.4.373

M. Lin, J. Tapamo, and B. Ndovie, A Texture-based Method for Document Segmentation and Classification, South African Computer Journal, pp.49-56, 2006.
URL : https://hal.archives-ouvertes.fr/hal-01262352

C. L. Liu, M. Koga, and H. Fujisawa, Gabor feature extraction for character recognition: comparison with gradient feature, Eighth International Conference on Document Analysis and Recognition (ICDAR'05), pp.121-125, 2005.
DOI : 10.1109/ICDAR.2005.119

H. Ma and D. Doermann, Gabor Filter Based Multi-class Classifier for Scanned Document Images, ICDAR, pp.968-972, 2003.

J. B. Macqueen, Some Methods for Classification and Analysis of Multivariate Observations, Berkeley Symposium on Mathematical Statistics and Probability, pp.281-297, 1967.

P. Mahalanobis, On the generalised distance in statistics, Proceedings of the National Institute of Sciences of India, pp.49-55, 1936.

M. Mehri, P. Gomez-krämer, P. Héroux, and R. Mullot, Old document image segmentation using the autocorrelation function and multiresolution analysis, Document Recognition and Retrieval XX, 2013.
DOI : 10.1117/12.2002365

URL : https://hal.archives-ouvertes.fr/hal-00787779

A. K. Mikkilineni, P. J. Chiang, G. N. Ali, G. T. Chiu, J. P. Allebach et al., Printer identification based on graylevel co-occurrence features for security and forensic applications, Security, Steganography, and Watermarking of Multimedia Contents VII, pp.430-440, 2005.
DOI : 10.1117/12.593796

G. Nguyen, M. Coustaty, and J. Ogier, Stroke feature extraction for lettrine indexing, 2010 2nd International Conference on Image Processing Theory, Tools and Applications, pp.355-360, 2010.
DOI : 10.1109/IPTA.2010.5586747

N. Otsu, A Threshold Selection Method from Gray-Level Histograms, Systems, Man, and Cybernetics, pp.62-66, 1979.
DOI : 10.1109/TSMC.1979.4310076

A. Ouji, Y. Leydier, and F. Lebourgeois, Chromatic / Achromatic Separation in Noisy Document Images, 2011 International Conference on Document Analysis and Recognition, pp.167-171, 2011.
DOI : 10.1109/ICDAR.2011.42

URL : https://hal.archives-ouvertes.fr/hal-01354444

J. S. Payne, T. J. Stonham, and D. Patel, Document segmentation using texture analysis, Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5), pp.380-382, 1994.
DOI : 10.1109/ICPR.1994.576947

J. S. Payne, T. J. Stonham, and D. Patel, Document segmentation using texture analysis, Proceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5), pp.380-382, 1994.
DOI : 10.1109/ICPR.1994.576947

G. Peake and T. Tan, Script and Language Identification from Document Images, DIA, pp.10-17, 1997.

M. Petrou and P. G. Sevilla, Image Processing : Dealing with texture, 2006.
DOI : 10.1002/047003534X

Y. Qiao, Z. Lu, C. Song, and S. Sun, Document image segmentation using Gabor wavelet and kernel-based methods, ISSCAA, pp.450-455, 2006.

P. Rousseeuw, Silhouettes: A graphical aid to the interpretation and validation of cluster analysis, Journal of Computational and Applied Mathematics, vol.20, pp.53-65, 1987.
DOI : 10.1016/0377-0427(87)90125-7

H. E. Said, T. N. Tan, and K. D. Baker, Personal identification based on handwriting, pp.149-160, 2000.

P. C. Saxena and K. Navaneetham, The Effect of Cluster Size, Dimensionality, and Number of Clusters on Recovery of True Cluster Structure Through Chernoff-Type Faces, The Statistician, vol.40, issue.4, pp.415-425, 1991.
DOI : 10.2307/2348731

F. Shahabi and M. Rahmati, A New Method for Writer Identification of Handwritten Farsi Documents, 2009 10th International Conference on Document Analysis and Recognition, pp.426-430, 2009.
DOI : 10.1109/ICDAR.2009.290

L. Shijian and C. L. Tan, Script and Language Identification in Noisy and Degraded Document Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.1, pp.14-24, 2008.
DOI : 10.1109/TPAMI.2007.1158

T. Simpson, J. Armstrong, and A. Jarman, Merged consensus clustering to assess and improve class discovery with microarray data, BMC Bioinformatics, vol.11, issue.1, pp.1471-1482, 2010.
DOI : 10.1186/1471-2105-11-590

J. Ward, Hierarchical Grouping to Optimize an Objective Function, Journal of the American Statistical Association, vol.58, issue.301, pp.236-244, 1963.
DOI : 10.1007/BF02289263

Y. Zhu, T. Tan, and Y. Wang, Font Recognition Based on Global Texture Analysis, pp.1192-1200, 2001.