MATLAB: How to remove unnecessary pixels on a line on a binary image

#edgeanalyze#lineanalyze#morphologicalimagebinaryImage Processing Toolboxskeleton

Hello guys, I need to remove (change the color to black) unnecessary pixels like I showed in red border in order to analyze the boundary of morphological image conveniently. My point is, there can only be 1 or 2 white neighbours (pixels) of a white pixel around it on such a line on the image.

Best Answer

bwmorph(BW,'skel',Inf); should do the trick.

Related Solutions

MATLAB: Avoiding unnecessary for loops

These are a few lines already. The mos expensive is the exp call, so you save the most time with using the symmetry (as mentioned by Jos already):

S = zeros(100,100);
sig = 0.05;
for i = 1:100
   for j = i+1:100
      S(i,j) = exp(-norm(D(i,:) - D(j,:)) / sig);
      S(j,i) = S(i,j);
   end
end

You can try if it is faster to replace norm by:

for i = 1:100
   v = D(i, :);
   for j = i+1:100
      w = v - D(j, :);
      S(i,j) = exp(-sqrt(w * w.') / sig);
      S(j,i) = S(i,j);
   end
end

Operating on columns is faster than on rows:

DT = D.';
for i = 1:100
   v = DT(:, i);
   for j = i+1:100
      w = v - DT(:, j);
      S(i,j) = exp(-sqrt(w.' * w) / sig);
      S(j,i) = S(i,j);
   end
end

Please post the timings you get.

MATLAB: Unnecessary rounding when reading an xlsx

Thanks for providing the raw data.

I'm not seeing what you're seeing. My data exporation steps are below.

% Read-in the data
x = readmatrix('U238Elastic.xlsx'); 
% Check out the first few rows
x(1:10,:)
% RESULT (format: shortg)
%     ans =
%             1e-05       35.398
%        1.0625e-05       34.404
%         1.125e-05       33.496
%        1.1875e-05       32.662
%          1.25e-05       31.893
%         1.375e-05        30.52
%           1.5e-05       29.326
%         1.625e-05       28.277
%          1.75e-05       27.345
%         1.875e-05       26.512

Clearly the precision is greater than 4dp.

Are there any duplicate rows?

% Produce index of unique rows of x
[~, unqIdx] = unique(x,'rows');
isUnq = ismember(1:size(x,1), unqIdx); 
% Compute the percentage of rows that are unique
percentUnq = sum(isUnq)/size(x,1)*100
% RESULT
%     percentUnq =
%        100

It seems that all of the coordinates are unique. Maybe you're reading in the data differently or perhaps you're looking at a different pair of values than this.

Best Answer

Related Solutions

MATLAB: Avoiding unnecessary for loops

MATLAB: Unnecessary rounding when reading an xlsx

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