fcmTest.zip_Fuzzy C Means_fcmtest_模糊C-均值聚类

function fcmTest(file, cluster_n) % fcmTest % fcmTest(file, cluter_n) segments a image named file using the algorithm % FCM. % [in] % file: the path of the image to be clustered. % cluster_n: the number of cluster for FCM. eval(['info=imfinfo(''',file, ''');']); switch info.ColorType case 'truecolor' eval(['RGB=imread(''',file, ''');']); % [X, map] = rgb2ind(RGB, 256); I = rgb2gray(RGB); clear RGB; case 'indexed' eval(['[X, map]=imread(''',file, ''');']); I = ind2gray(X, map); clear X; case 'grayscale' eval(['I=imread(''',file, ''');']); end; I = im2double(I); filename = file(1 : find(file=='.')-1); data = reshape(I, numel(I), 1); tic [center, U, obj_fcn]=fcm(data, cluster_n); elapsedtime = toc; %eval(['save(', filename, int2str(cluster_n),'.mat'', ''center'', ''U'', ''obj_fcn'', ''elapsedtime'');']); fprintf('elapsedtime = %d', elapsedtime); maxU=max(U); temp = sort(center, 'ascend'); for n = 1:cluster_n; eval(['cluster',int2str(n), '_index = find(U(', int2str(n), ',:) == maxU);']); index = find(temp == center(n)); switch index case 1 color_class = 0; case cluster_n color_class = 255; otherwise color_class = fix(255*(index-1)/(cluster_n-1)); end eval(['I(cluster',int2str(n), '_index(:))=', int2str(color_class),';']); end; filename = file(1:find(file=='.')-1); I = mat2gray(I); %eval(['imwrite(I,', filename,'_seg', int2str(cluster_n), '.bmp'');']); imwrite(I, 'temp\tu2_4.bmp','bmp'); imview(I);