1 簡介

以圖像分割為研究內(nèi)容,分析了圖像的空頻域特征,并在此基礎(chǔ)之上提出了一種基于模糊局部信息C均值聚類的分割算法.由于FLICM算法充分利用局部空間信息和局部灰度信息,能夠很好地描述模糊性,對于邊界不清晰的太赫茲圖像有很好地效果.采用不同成像條件下的多類太赫茲圖像進行實驗,結(jié)果表明此方法能夠很好地克服邊緣模糊,隨機噪聲,條紋噪聲等干擾,分割所得目標(biāo)輪廓完整,準(zhǔn)確,有較高的精度,為進一步的圖像目標(biāo)識別打下了良好的基礎(chǔ).

2 部分代碼

clear ; clc ; data = randn ( 310 , 2 ); [ center , U , obj_fcn ] = fcm ( data , 2 ); plot ( data (:, 1 ), data (:, 2 ), ’o’ ); hold on ; maxU = max ( U ); % Find the data points with highest grade of membership in cluster 1 index1 = find ( U ( 1 ,:) == maxU ); % Find the data points with highest grade of membership in cluster 2 index2 = find ( U ( 2 ,:) == maxU ); %line(data(index1,1),data(index1,2),’marker’,’*’,’color’,’g’); %line(data(index2,1),data(index2,2),’marker’,’*’,’color’,’r’); % Plot the cluster centers plot ([ center ([ 1 2 ], 1 )],[ center ([ 1 2 ], 2 )], ’*’ , ’color’ , ’k’ ); hold off ; % I = imread(’lena.jpg’); %I = imread(’eight.tif’); % I = imread(’romantic.jpg’); I = imread ( ’bacteria.jpg’ ); I = rgb2gray ( I ); figure , imshow ( I ,[]); title ( ’原圖’ ); g = imnoise ( I , ’salt & pepper’ , 0.02 ); % 給圖像添加高斯噪聲 figure , imshow ( g ,[]); title ( ’添加高斯噪聲后的圖像’ ); g = double ( g ); [ m , n ] = size ( g ); k = 2 ; % ---------fcm---------------- fcm_label = zeros ( m * n , 1 ); [ O , U , obj_fcn1 ] = fcm ( g (:), k ); maxU = max ( U ); for j = 1 : k     index = find ( U ( j , :) == maxU );     fcm_label ( index ) = j ;     end fcm_result = reshape ( fcm_label ,[ m n ]); figure , imshow ( fcm_result ,[]); title ( ’fcm分割結(jié)果’ ); % ------------------------ FLICM法------------------------ r = 3 ; % 求G時，鄰域窗的大小 [ neighbor_pos , window_d ]= FLICM_find_neighbor ( g , r ); FLICM_label = zeros ( m * n , 1 ); t = cputime ; X = g (:); [ O10 , U10 , obj_fcn10 ] = FLICM ( X , k , neighbor_pos , window_d ); time_FLICM = cputime - t ; maxU10 = max ( U10 ); for j = 1 : k     index = find ( U10 ( j , :) == maxU10 );     FLICM_label ( index ) = j ;     end labels10 = reshape ( FLICM_label ,[ m n ]); figure , imshow ( labels10 ,[]); title ( ’flicm分割結(jié)果’ );

3 仿真結(jié)果

4 參考文獻

[1]雷萌, 黃志堅, and 馬芳粼. "一種基于局部信息模糊聚類的太赫茲圖像分割算法." 制造業(yè)自動化 37.12(2015):3.

部分理論引用網(wǎng)絡(luò)文獻，若有侵權(quán)聯(lián)系博主刪除。

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