M. Sezgin and B. Sankur, Survey over image thresholding techniques and quantitative performance evaluation, Journal of Electronic Imaging, vol.13, issue.1, pp.146-165, 2004.

S. Sahasrabudhe and K. Gupta, A valley-seeking threshold selection technique, Computer Vision and Image Understanding, pp.55-65, 1992.

R. Guo and S. Pandit, Automatic threshold selection based on histogram modes and a discriminant criterion, Machine Vision and Applications, pp.331-338, 1998.
DOI : 10.1007/s001380050083

J. Kittler and J. Illingworth, Minimum error thresholding, Pattern Recognition, vol.19, issue.1, pp.41-47, 1986.
DOI : 10.1016/0031-3203(86)90030-0

S. Kwon, Threshold selection based on cluster analysis, Pattern Recognition Letters, vol.25, issue.9, pp.1045-1050, 2004.
DOI : 10.1016/j.patrec.2004.03.001

N. Otsu, A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol.9, issue.1, pp.62-66, 1979.
DOI : 10.1109/TSMC.1979.4310076

M. Krinidis and I. Pitas, Color Texture Segmentation Based on the Modal Energy of Deformable Surfaces, IEEE Transactions on Image Processing, vol.18, issue.7, pp.1613-1622, 2009.
DOI : 10.1109/TIP.2009.2018002

S. Krinidis and V. Chatzis, Fuzzy Energy-Based Active Contours, IEEE Transactions on Image Processing, vol.18, issue.12, pp.2747-2755, 2009.
DOI : 10.1109/TIP.2009.2030468

URL : https://hal.archives-ouvertes.fr/hal-01521387

P. Sahoo, C. Wilkins, and J. Yeaget, Threshold selection using Renyi's entropy, Pattern Recognition, vol.30, issue.1, pp.71-84, 1997.
DOI : 10.1016/S0031-3203(96)00065-9

J. Yen, F. Chang, and S. Chang, A new criterion for automatic multilevel thresholding, IEEE Transactions on Image Processing, vol.4, issue.3, pp.370-378, 1995.

L. Huang and M. Wang, Image thresholding by minimizing the measures of fuzziness, Pattern Recognition, vol.28, issue.1, pp.41-51, 1995.
DOI : 10.1016/0031-3203(94)E0043-K

A. Pikaz and A. Averbuch, Digital image thresholding, based on topological stable-state, Pattern Recognition, vol.29, issue.5, pp.829-843, 1996.
DOI : 10.1016/0031-3203(95)00126-3

H. Cheng and Y. Y. Chen, Fuzzy partition of two-dimensional histogram and its application to thresholding, Pattern Recognition, vol.32, issue.5, pp.825-843, 1999.
DOI : 10.1016/S0031-3203(98)00080-6

S. Krinidis and V. Chatzis, A Robust Fuzzy Local Information C-Means Clustering Algorithm, IEEE Transactions on Image Processing, vol.19, issue.5, pp.1328-1337, 2010.
DOI : 10.1109/TIP.2010.2040763

J. Sauvola and M. Pietikainen, Adaptive document image binarization, Pattern Recognition, vol.33, issue.2, pp.225-236, 2000.
DOI : 10.1016/S0031-3203(99)00055-2

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

M. Aghagolzadeh, H. Soltanian-zadeh, B. Araabi, and A. Aghagolzadeh, A Hierarchical Clustering Based on Mutual Information Maximization, 2007 IEEE International Conference on Image Processing, pp.277-280, 2007.
DOI : 10.1109/ICIP.2007.4378945

F. X. Yu, Y. Q. Lei, Y. G. Wang, and Z. M. Lu, Robust image hashing based on statistical invariance of dct coefficients, Journal of Information Hiding and Multimedia Signal Processing, vol.1, issue.4, pp.286-291, 2010.

N. Huang, Z. Shen, S. Long, M. Wu, E. Shih et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.454, issue.1971, pp.903-995, 1998.
DOI : 10.1098/rspa.1998.0193

Z. Wu and N. Huang, ENSEMBLE EMPIRICAL MODE DECOMPOSITION: A NOISE-ASSISTED DATA ANALYSIS METHOD, Advances in Adaptive Data Analysis, vol.46, issue.01, pp.1-41, 2009.
DOI : 10.1073/pnas.0701020104

J. Tohka, Surface Extraction from Volumetric Images Using Deformable Meshes: A Comparative Study, Proceedings of 7th European Conference on Computer Vision, pp.350-364, 2002.
DOI : 10.1007/3-540-47977-5_23

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