- you might match multiple local minima
- you are going to plot all the local minima adjacent to each other, not their original distance apart
- you are going to have trouble if the pattern is \__/ instead of \_/ i.e., if the local min is more than one point wide
- you might want to think about using diff()
- local min could occur at the endpoints -- with your current code, a continually-decreasing or -increasing set of data would not register any local min.
is this the right way to find local minima of histogram
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Muhammad Ali Qadar
le 8 Nov 2013
Commenté : Image Analyst
le 26 Août 2016
hi, I am trying to find the local minima value of image's histogram, I am filtering image from 1*3 filter and then finding minima, waiting for your suggestions
I = imread('eight.tif');I=I(:)';I=double(I);
x=[1 1 1]/3;
f=filter2(x,I,'same');
y = sin(5*f);
idx = [false, y(3:end)>y(2:end-1) & y(2:end-1)<y(1:end-2), false];
xmin = f(idx)
plot(xmin,'o-')
thanks in Advance.
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Walter Roberson
le 8 Nov 2013
Not so bad, but remember
7 commentaires
Image Analyst
le 26 Août 2016
"count <= 0 will give you the logical array" and that is what he calls L.
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Image Analyst
le 8 Nov 2013
Way too complicated for me. Actually I didn't even see you take the histogram, which you do with imhist(). I'm not sure what you're doing with the sine wave. Why not just use imhist() and imregionalmin()? It's much more straightforward and only 2 lines of code.
[counts, grayLevels] = imhist(I); % Get histogram into "counts"
minIndexes = imregionalmin(counts); % Find indexes of local mins in the histogram.
To get the gray levels instead of the indexes, you need to subtract 1 because index 1 is actually gray level 0.
grayLevelsAtLocalMins = minIndexes - 1;
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