Comparing clustering methods for color image segmentation

% This code implemented a comparison of clustering methods for color image segmentation

% This code implemented a comparison of clustering methods for color image segmentation

% Tested methods include:
% Slope difference distribution based clustering
% Otsu clustering
% Expectation Maximization clustering
% Fuzzy Cmeans clustering
% Kmeans clustering

%%%The segmentation purpose is to distinguish the object from the background by
%%%two-label segmentation

% by Zhenzhou Wang;2018-11-1
% For questions, please contact me at: [e-mail]
%This code is only for qualitative comparisons

%For quantitative comparisons,please refer to the following publications
%[1] ZZ Wang, Image segmentation by combining the global and local properties, Expert Systems with Applications 87, 30-40
%%[2] Z Wang, Y Yang, A non-iterative clustering based soft segmentation approach for a class of fuzzy images
%%Applied Soft Computing 70, 988-999
%%[3] Z wang. Determining the clustering center by slope difference
%%distribution, IEEE access, Vol. 5, 10995 - 11002