Extracting points for sharp curvature from signed distance function array
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I have a signed distance array, extracted from a black-and-white bitmap. The shape described by the bitmap is arbitrary, and could contain concave or convex curvature of varying scales. I am interested in extracting the position of corners that are sharper than a certain amount. I'm frankly not sure how to define that sharpness here; what I care about is 'shoving' a circle of a defined radius into that corner, and for the corner in total to be larger than that circle (in other words, I don't want it reporting every single rasterisation of the bitmap):
- identifying if any convex curvatures' radius is less a code-defined radius of curvature limit
- calculating what coordinate in the bitmap represents the centrepoint of the code-defined radius of curvature limit for that corner, and then
- to list any and all found sets of centerpoint coordinates in an array of format T= [x1, y1; x2, y2; .... xn, yn].
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1359983/image.png)
I'm obtaining my distance array and interpolation function as follows.
X = imread("MeshTest01.bmp"); %load logical (1 or 0) bitmap
A = imrotate(X,-90);
E=edge(A); % Edge finding of bitmap
DistE = bwdist(E, "euclidean"); % signed distance function from edge
DistA = bwdist(A, "euclidean"); % signed distance function from whitespace
D = DistE-2*DistA % Pixel-enumerative distance for signed distance function from material (outside is positive)
D = double(D); %make array forced to Double so interpolation works correctly
Fi = griddedInterpolant(D,'linear')
fd=@(p) Fi(p); %defining the interpolation function call
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Supraja
el 5 de Mayo de 2023
You can use ‘ischange()’ function which detects abrupt changes in data.
The detailed documentation link for the same is given here: https://www.mathworks.com/help/matlab/ref/ischange.html?searchHighlight=ischange%20function&s_tid=srchtitle_ischange%20function_1
The sample code to use this function is as shown below:
f = @(x) 1-(x./sqrt(1+x.^2)); % Create Function
x = linspace(-10, 10);
y = f(x);
changes = ischange(y, 'linear', 'SamplePoints', x);
plot(x, y, '-', x(changes), y(changes), 'gp')
grid on
axis('equal')
xlim([-2.5 2.5])
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