Highlight peaks/dents in a heatmap imagesc()
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Konvictus177
on 15 Jan 2022
Commented: Oliver Tolfts
on 2 Mar 2023
Hi,
I am creating an image based on laser distance data (z) that I am collecting using imagesc(x,y,z). This gives me a heatmap/surface map of my object.
How can I automatically highlight the peaks/dents in this map or areas where z is higher/lower than a user defined threshold? I would like to create a circle around that area that has values higher or lower than a threshold or highlight those areas in any other way.
Thanks!
2 Comments
Accepted Answer
Mathieu NOE
on 18 Jan 2022
hello
a very simple code that combines surf and contour (will not draw a circle but maybe it's still a valuable solution)
[X,Y,Z] = peaks(100);
figure(1),hold on
s = surf(X,Y,Z,'Facealpha',0.75,'Edgecolor','none');
view(2);
colorbar('vert');
threshold = 0.3*max(Z,[],'all');
[c,h] = contour(X,Y,Z,[threshold threshold],'-k','Linewidth',5);
hold off
5 Comments
Image Analyst
on 19 Jan 2022
Use App Designer to make a GUI. I'm sure there is a tutorial on that somewhere.
More Answers (1)
Image Analyst
on 17 Jan 2022
Use imregionalmax():
Z = mat2gray(peaks);
x = linspace(0,2*pi);
y = linspace(0,2*pi);
subplot(2, 2, 1);
imagesc(x,y,Z)
axis('on', 'image')
% get regional max:
peaks = imregionalmax(Z);
subplot(2, 2, 2);
imshow(peaks, []);
% Overlay it on the original
rgbImage = imoverlay(Z, peaks, 'r');
subplot(2, 2, 3);
imshow(rgbImage);
Now that you have the locations, you can get the values at those locations and set up thresholded images, one for each peak. Then use bwboundaries() to get all the contours and use inpolygon to figure out which contours contain each point. Not hard at all, so I imagine you can do that part yourself, right? Here's my version:
% Initialization steps.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
Z = mat2gray(peaks);
x = linspace(0,2*pi);
y = linspace(0,2*pi);
subplot(2, 2, 1);
imagesc(x,y,Z)
impixelinfo;
axis('on', 'image')
% get regional max:
peaks = imregionalmax(Z);
% Some may have flat tops, so get down to a single point on each peak.
peaks = bwulterode(peaks);
subplot(2, 2, 2);
imshow(peaks, []);
% Overlay it on the original
rgbImage = imoverlay(Z, peaks, 'r');
subplot(2, 2, 3);
imshow(rgbImage);
impixelinfo;
% Get values of the peaks.
values = unique(Z(peaks))
% Get locations of the peaks.
[yp, xp] = find(peaks)
% Get contours
deltaz = 0.05;
subplot(2, 2, 4);
imshow(peaks, []);
hold on;
for k = 1 : length(values)
mask = Z > (values(k) - deltaz);
% imshow(mask);
boundaries = bwboundaries(mask);
thisx = xp(k);
thisy = yp(k);
plot(thisx, thisy, 'r+', 'MarkerSize', 20)
if ~isempty(boundaries)
for k2 = 1 : length(boundaries)
thisBoundary = boundaries{k2};
x = thisBoundary(:, 2);
y = thisBoundary(:, 1);
pointIsInside = inpolygon(thisx, thisy, x, y);
if pointIsInside
plot(x, y, '-', 'LineWidth', 2);
end
end
end
end
2 Comments
yanqi liu
on 18 Jan 2022
yes,sir,it is great idea,use imregionalmax to get region max and clear boarder,may be use to watermark segment
Oliver Tolfts
on 2 Mar 2023
@Image Analyst, >20% of the graphs of my Ph.D were plotted using your help. Thank you for sharing all your knowledge of Matlab.
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