阈值分割

Question:

将以下A4纸上的线条单独识别出来。

Answer:

function segmentation
img=imread('input.png');
f=im2double(img);
%ãÐÖµ·Ö¸îËã·¨¡ª¡ªµü´ú·¨
T=0.5*(min(f(:))+max(f(:))); 
done=false; 
while ~done 
    g=f>=T;
    Tn=0.5*(mean(f(g))+mean(f(~g)));
    done=abs(T-Tn)<0.1;
    T=Tn; 
end
threshold=im2bw(f,T);                                
subplot(121),imshow(img),title('ÔÍ¼');           
subplot(122),imshow(threshold),title('ãÐÖµ·Ö¸îËã·¨');

%ÂÖÀªÌáÈ¡       
% ±ß½ç¼ì²â  
%b=edge(r,'Canny',0.2);
%figure
%imshow(b);
%d=imfill(b,'hole');

%ÐÎÌ¬Ñ§Í¼Ïñ´¦Àí¡ª¡ª¸¯Ê´
se1=strel('disk',4);
bw1=imerode(threshold,se1);
figure
imshow(bw1), title('¸¯Ê´ºóµÄÍ¼Ïñ');

%ÂÖÀªÌáÈ¡
outline = bwperim(bw1); 
figure    
imshow(outline);    
title('ÂÖÀª') 
[l,m]=bwlabel(outline,8);
status=regionprops(l,'BoundingBox');
figure
imshow(outline), title('¾ØÐÎÂÖÀªÌáÈ¡');hold on;
for i=1:m
     rectangle('position',status(i).BoundingBox,'edgecolor','green');
end
%{
disp (m);
disp (status(1).BoundingBox);
disp (status(2).BoundingBox);
disp (status(3).BoundingBox);
disp (status(4).BoundingBox);
disp (status(5).BoundingBox);
disp (status(6).BoundingBox);
disp (status(7).BoundingBox);
disp (status(8).BoundingBox);
%}
output1 = imcrop(img,[status(2).BoundingBox(1),status(2).BoundingBox(2),status(2).BoundingBox(3),status(2).BoundingBox(4)]);
output2 = imcrop(img,[status(3).BoundingBox(1),status(3).BoundingBox(2),status(3).BoundingBox(3),status(3).BoundingBox(4)]);
output3 = imcrop(img,[status(4).BoundingBox(1),status(4).BoundingBox(2),status(4).BoundingBox(3),status(4).BoundingBox(4)]);
output4 = imcrop(img,[status(5).BoundingBox(1),status(5).BoundingBox(2),status(5).BoundingBox(3),status(5).BoundingBox(4)]);
output5 = imcrop(img,[status(6).BoundingBox(1),status(6).BoundingBox(2),status(6).BoundingBox(3),status(6).BoundingBox(4)]);
output6 = imcrop(img,[status(7).BoundingBox(1),status(7).BoundingBox(2),status(7).BoundingBox(3),status(7).BoundingBox(4)]);
output7 = imcrop(img,[status(8).BoundingBox(1),status(8).BoundingBox(2),status(8).BoundingBox(3),status(8).BoundingBox(4)]);
figure
imshow(output1);
figure
imshow(output2);
figure
imshow(output3);
figure
imshow(output4);
figure
imshow(output5);
figure
imshow(output6);
figure
imshow(output7);
end

Algorithm description:

1.阈值分割——迭代法
迭代法是基于逼近的思想，其步骤如下：
（1）求出图象的最大灰度值和最小灰度值，分别记为ZMAX和ZMIN，令初始阈值T0=(ZMAX+ZMIN)/2；
（2）根据阈值TK将图象分割为前景和背景，分别求出两者的平均灰度值ZO和ZB；
（3）求出新阈值TK+1=(ZO+ZB)/2；
（4）若TK=TK+1，则所得即为阈值；否则转2，迭代计算。
%阈值分割算法——迭代法
T=0.5*(min(f(:))+max(f(:))); 
done=false; 
while ~done 
    g=f>=T;
    Tn=0.5*(mean(f(g))+mean(f(~g)));
    done=abs(T-Tn)<0.1;
    T=Tn; 
end
threshold=im2bw(f,T); 

2.形态学图像处理——腐蚀
%形态学图像处理——腐蚀
se1=strel('disk',4);
bw1=imerode(threshold,se1);

3.轮廓检测与提取
outline = bwperim(bw1); 
figure    
imshow(outline);    
title('轮廓') 
[l,m]=bwlabel(outline,8);
status=regionprops(l,'BoundingBox');
figure
imshow(outline), title('矩形轮廓提取');hold on;
for i=1:m
     rectangle('position',status(i).BoundingBox,'edgecolor','green');
end

Result:

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