下面是给出的图片,我还有很多类似的图片,处理起来需要返回圆圈的像素坐标,最后连接封闭图形的顺序坐标
大概写了一下不知道是否有帮助:
function redPnt
oriPic=imread('test1.png');
subplot(2,2,1)
imshow(oriPic)
% 删除红色外的部分并构造二值图
grayPic=rgb2gray(oriPic);
grayPic(oriPic(:,:,1)<255)=255;
grayPic(grayPic<250)=0;
subplot(2,2,2)
imshow(grayPic)
% 图像膨胀,使未连接边缘连接
SE=[0 1 0;1 1 1;0 1 0];
bwPic=imerode(grayPic,SE);
% 边缘清理:保留圆圈联通区域
bwPic=imclearborder(bwPic);
subplot(2,2,3)
imshow(bwPic)
% 获取每一个联通区域
LPic=bwlabel(bwPic);
labelNum=max(max(LPic));
% 计算每一个联通区域 坐标均值
pointSet=zeros(labelNum,2);
for i=1:labelNum
[X,Y]=find(LPic==i);
Xmean=mean(X);
Ymean=mean(Y);
pointSet(i,:)=[Xmean,Ymean];
end
subplot(2,2,4)
imshow(bwPic)
hold on
scatter(pointSet(:,2),pointSet(:,1),'r','LineWidth',1)
n=1;
while ~isempty(pointSet)
circleSetInd=1;
for j=1:length(pointSet)
disSet=sqrt(sum((pointSet-pointSet(circleSetInd(end),:)).^2,2));
[~,ind]=sort(disSet);
ind=ind(1:5);
[~,~,t_ind]=intersect(circleSetInd,ind);
ind(t_ind)=[];
if ~isempty(ind)
circleSetInd=[circleSetInd;ind(1)];
else
circleSet{n}=pointSet(circleSetInd,:);
pointSet(circleSetInd,:)=[];
n=n+1;
break
end
end
end
figure
imshow(oriPic)
hold on
for i=1:n-1
plot(circleSet{i}(:,2),circleSet{i}(:,1),'LineWidth',2)
end
end
没有用霍夫圆形检测之类算法,只是单纯的图像膨胀,边缘清理,寻找联通区域,计算联通区域坐标均值
大概过程如下图所示:
效果图如下: