matlab二值图像合并质心距离最近的邻域

以下是一种可能的解决方案：

1. 读入两幅二值图像并显示：

img1 = imread('image1.png');
img2 = imread('image2.png');
imshowpair(img1, img2, 'montage');

2. 使用bwlabel函数对两幅图像进行连通域分析，得到各个连通域的标记：

[L1, num1] = bwlabel(img1);
[L2, num2] = bwlabel(img2);

3. 对于每个连通域，在另一幅图像中寻找与之距离最近的连通域：

centers1 = regionprops(L1, 'Centroid');
centers2 = regionprops(L2, 'Centroid');
for i = 1:num1
    c1 = centers1(i).Centroid;
    min_dist = Inf;
    match_idx = -1;
    for j = 1:num2
        c2 = centers2(j).Centroid;
        dist = norm(c1 - c2);
        if dist < min_dist
            min_dist = dist;
            match_idx = j;
        end
    end
    % 将两个连通域合并
    if match_idx > 0
        L2(L2 == match_idx) = i + num1;
    end
end

4. 将合并后的标记转换为二值图像并显示：

merged = L2 > 0;
imshow(merged);

完整代码如下：

img1 = imread('image1.png');
img2 = imread('image2.png');
imshowpair(img1, img2, 'montage');

[L1, num1] = bwlabel(img1);
[L2, num2] = bwlabel(img2);

centers1 = regionprops(L1, 'Centroid');
centers2 = regionprops(L2, 'Centroid');
for i = 1:num1
    c1 = centers1(i).Centroid;
    min_dist = Inf;
    match_idx = -1;
    for j = 1:num2
        c2 = centers2(j).Centroid;
        dist = norm(c1 - c2);
        if dist < min_dist
            min_dist = dist;
            match_idx = j;
        end
    end
    if match_idx > 0
        L2(L2 == match_idx) = i + num1;
    end
end

merged = L2 > 0;
imshow(merged);