Matlab操纵边缘(Matlab manipulate edges)

 这取决于允许的成本密集程度。 一个简单的方法是： 
 
 （1）使用Sobel-Filters对图像进行卷积（给出Dx，Dy）。 
 
 对于每个canny-edge-pixel： 
 
 （2）标准化（Dx，Dy），st在您拥有边缘方向的每个像素中。 
 
 （3）用你想要移除的方向计算内积（在你的情况下为（0,1））。 
 
 （4）如果内积的绝对值小于某个阈值，则移除像素。 
 
 例： 
 
img = ...;
canny_img = ...;
removeDir = [0;1];
% convolute with sobel masks
sobelX = [1, 0, -1; 2, 0, -2; 1, 0, -1];
sobelY = sobelX';
DxImg = conv2(img,sobelX,'same');
DyImg = conv2(img,sobelY,'same');
% for each canny-edge-pixel:
for lin = 1:size(img,1) % <-> y
    for col = 1:size(img,2) % <-> x
        if canny_img(lin,col)
            % normalize direction
            normDir = [DxImg(lin,col); DyImg(lin,col)];
            normDir = normDir / norm(normDir,2);
            % inner product
            innerP = normDir' * removeDir;
            % remove edge?
            if abs(innerP) < cos(45/180*pi) % 45° threshold
                canny_img(lin,col) = 0;
            end
        end
    end
end
 
 根据您的要求，您可以对其进行大量优化。 

It depends on how cost-intensive it is allowed to be. One easy way to do would be:
 
(1) Convolute your image with Sobel-Filters (gives Dx, Dy).
 
For each canny-edge-pixel:
 
(2) Normalize (Dx, Dy), s.t. in every pixel you have the direction of your edge.
 
(3) Compute the inner products with the direction you want to remove (in your case (0,1)).
 
(4) If the absolut value of the inner product is smaller than some threshold remove the pixel.
 
Example:
 
img = ...;
canny_img = ...;
removeDir = [0;1];
% convolute with sobel masks
sobelX = [1, 0, -1; 2, 0, -2; 1, 0, -1];
sobelY = sobelX';
DxImg = conv2(img,sobelX,'same');
DyImg = conv2(img,sobelY,'same');
% for each canny-edge-pixel:
for lin = 1:size(img,1) % <-> y
    for col = 1:size(img,2) % <-> x
        if canny_img(lin,col)
            % normalize direction
            normDir = [DxImg(lin,col); DyImg(lin,col)];
            normDir = normDir / norm(normDir,2);
            % inner product
            innerP = normDir' * removeDir;
            % remove edge?
            if abs(innerP) < cos(45/180*pi) % 45° threshold
                canny_img(lin,col) = 0;
            end
        end
    end
end
 
You can optimize it a lot due to your requirements.