Serendipity
b8a8ff2bc6
实现内容： - 网格划分：投影分析 + 自相关估周期 + 白顶帽去背景 + 质心提取 - 三种阈值分割：人工阈值、Otsu自动阈值、迭代阈值 - TV去噪（Chambolle投影算法） - 后处理：去小连通域 + 保留最大连通域 - 完整可视化：网格叠加、阈值对比、收敛曲线、分割结果 参考MATLAB代码：NewGridAndCV/demo_GriddingAndCV.m
75 lines
2.0 KiB
Matlab
75 lines
2.0 KiB
Matlab
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function m = maskcircle2(I,type)
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% auto pick a circular mask for image I
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% built-in mask creation function
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% Input: I : input image
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% type: mask shape keywords
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% Output: m : mask image
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% Copyright (c) 2009,
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% Yue Wu @ ECE Department, Tufts University
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% All Rights Reserved
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if size(I,3)~=3
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temp = double(I(:,:,1));
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else
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temp = double(rgb2gray(I));
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end
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h = [0 1 0; 1 -4 1; 0 1 0];
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T = conv2(temp,h);
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T(1,:) = 0;
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T(end,:) = 0;
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T(:,1) = 0;
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T(:,end) = 0;
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thre = max(max(abs(T)))*.5;
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idx = find(abs(T) > thre);
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[cx,cy] = ind2sub(size(T),idx);
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cx = round(mean(cx));
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cy = round(mean(cy));
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[x,y] = meshgrid(1:min(size(temp,1),size(temp,2)));
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m = zeros(size(temp));
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[p,q] = size(temp);
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switch lower (type)
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case 'small'
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r = 10;
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n = zeros(size(x));
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n((x-cx).^2+(y-cy).^2<r.^2) = 1;
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m(1:size(n,1),1:size(n,2)) = n;
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%m((x-cx).^2+(y-cy).^2<r.^2) = 1;
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case 'medium'
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r = min(min(cx,p-cx),min(cy,q-cy));
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r = max(2/3*r,25);
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n = zeros(size(x));
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n((x-cx).^2+(y-cy).^2<r.^2) = 1;
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m(1:size(n,1),1:size(n,2)) = n;
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%m((x-cx).^2+(y-cy).^2<r.^2) = 1;
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case 'large'
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r = min(min(cx,p-cx),min(cy,q-cy));
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r = max(2/3*r,60);
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n = zeros(size(x));
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n((x-cx).^2+(y-cy).^2<r.^2) = 1;
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m(1:size(n,1),1:size(n,2)) = n;
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%m((x-cx).^2+(y-cy).^2<r.^2) = 1;
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case 'whole'
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r = 9;
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m = zeros(round(ceil(max(p,q)/2/(r+1))*3*(r+1)));
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siz = size(m,1);
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sx = round(siz/2);
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i = 1:round(siz/2/(r+1));
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j = 1:round(0.9*siz/2/(r+1));
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j = j-round(median(j));
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m(sx+2*j*(r+1),(2*i-1)*(r+1)) = 1;
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se = strel('disk',r);
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m = imdilate(m,se);
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m = m(round(siz/2-p/2-6):round(siz/2-p/2-6)+p-1,round(siz/2-q/2-6):round(siz/2-q/2-6)+q-1);
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end
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tem(:,:,1) = m;
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M = padarray(m,[floor(2/3*r),floor(2/3*r)],0,'post');
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tem(:,:,2) = M(floor(2/3*r)+1:end,floor(2/3*r)+1:end);
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m = tem;
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return |