How to plot a subset of triangles after DelaunayTri

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Amani 2013-12-9

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评论： Amani 2013-12-23

I have computed a Delaunay triangulation using DelaunayTri(). Then I extracted big triangles based on a threshold, how can I reconstruct these triangles and plot it in a figure ?

thanks

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Simon 2013-12-9

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Hi!

If you have a triangulation you can of course plot specific triangles (if you know them) with

TRI = dt.Triangulation;
X = dt.X;
ind = [1,2,3,4,5];
triplot(TRI(ind, :), X(:, 1), X(:, 2));

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Amani 2013-12-9

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how can I calculate the distance between two connected vertices (only Y coordinate) TRI = dt.Trangulation for q=1:size(dt,1) for u=1:size(dt,1) j = isConnected(k,q,u); if (j == true) % retrive q and u (y coordinate) and calculate the distance between them end

end

thanks

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Simon 2013-12-18

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Hi!

Now I see what you are doing ;-)

What is the reason that you are using triangulations for this? I did something similar a while ago (not for text, but other images). I found the script and adapted it for your image. Try it and see if it is useful for you.

% file with handwritten text
filename = 'ARA_D01_W0001.jpg';
% read in
A = imread(filename);
% and show
figure(1); cla;
image(A)
% make combined color value
Amode = double(A(:,:,1)) * 2^16 + double(A(:,:,2)) * 2^8 + double(A(:,:,3));
% color most often used -> background
BackColor = mode(Amode(:));
% find RGBs of background
ind = find(Amode == BackColor, 1);
[x,y] = ind2sub(size(Amode), ind);
% background RGB
BackRGB = squeeze(A(x, y, :));
% threshold for background detection
BackThreshold = 20;
% image mask, everything that is background is set to true
ImageMask = ...
    (A(:, :, 1) > (BackRGB(1) - BackThreshold)) & ...
    (A(:, :, 1) < (BackRGB(1) + BackThreshold)) & ...
    (A(:, :, 2) > (BackRGB(2) - BackThreshold)) & ...
    (A(:, :, 2) < (BackRGB(2) + BackThreshold)) & ...
    (A(:, :, 3) > (BackRGB(3) - BackThreshold)) & ...
    (A(:, :, 3) < (BackRGB(3) + BackThreshold));
% threshold of line/paragraph detection (number of background pixel in y-direction)
BackYThreshold = 1;
% image mask for background lines in image
LineMask = false(size(ImageMask));
for y = (1+BackYThreshold):(size(A, 1)-BackYThreshold)
    for x = 1:size(A, 2)
        %R check y-range
        if ImageMask(y, x)
            if all(ImageMask((y-BackYThreshold):(y+BackYThreshold), x))
                LineMask(y, x) = true;
            end
        end
    end
end
% find lines with only background
LineMask = all(LineMask, 2);
figure(2); cla;
image(LineMask*255);

Simon 2013-12-19

I used gimp for conversion. But I think you should not divide by 255. Images in matlab are uint8 with values between 0 and 255, in contrast to color values for e.g plotting with values between 0 and 1.

Amani 2013-12-23