Looking for a matlab script that extracts data from a plot figure ( here 2D contours from Covariance matrix or Markov chains) and reproduce the original figure

I am looking for a script which is able for example to extract data from a 2D contours plot like below :

I tried to apply the method in Matlab with the script below from this post :

%// Import the data:
imdata = importdata('Omega_L_Omega_m.png');
Gray = rgb2gray(imdata.cdata);
colorLim = [-1 1]; %// this should be set manually
%// Get the area of the data:
f = figure('Position',get(0,'ScreenSize'));
imshow(imdata.cdata,'Parent',axes('Parent',f),'InitialMagnification','fit');
%// Get the area of the data:
title('Click with the cross on the most top left area of the *data*')
da_tp_lft = round(getPosition(impoint));
title('Click with the cross on the most bottom right area of the *data*') 
da_btm_rgt = round(getPosition(impoint));
dat_area = double(Gray(da_tp_lft(2):da_btm_rgt(2),da_tp_lft(1):da_btm_rgt(1)));
%// Get the area of the colorbar:
title('Click with the cross within the upper most color of the *colorbar*')
ca_tp_lft = round(getPosition(impoint));
title('Click with the cross within the bottom most color of the *colorbar*')
ca_btm_rgt = round(getPosition(impoint));
cmap_area = double(Gray(ca_tp_lft(2):ca_btm_rgt(2),ca_tp_lft(1):ca_btm_rgt(1)));
close(f)
%// Convert the colormap to data:
data = dat_area./max(cmap_area(:)).*range(colorLim)-abs(min(colorLim));

It seems that I get data in "data" array but I don't know how to exploit it to reproduce the original figure from these data.

Could anyone see how to plot with Matlab this kind of plot with the data I have normally extracted (not sure the Matlab. script has generated all the data for green , orange and blue contours, with each confidence level, that is to say, 68%, 95%, 99.7%) ?

Any help is welcome to reproduce this figure with extracted values.

Thanks in advance

[petit]

Isn't really no one who could help me ?

Answer 1

[Joseph Cheng]

your graph is a bit messy with text and lines that denote items. here is a quick example that may push you along. It'll need a lot of work to fill in holes created by text and the dotted boundary lines but here is a start.

clc
clear all;
imdata = imread('https://www.mathworks.com/matlabcentral/answers/uploaded_files/642495/image.png');
close all;
Gray = rgb2gray(imdata);
yax=sum(conv2(single(Gray),[-1 -1 -1;0 0 0; 1 1 1],'valid'),2);
xax=sum(conv2(single(Gray),[-1 -1 -1;0 0 0; 1 1 1]','valid'),1);
figure(1),subplot(211),plot(xax),subplot(212),plot(yax)

ROIy = find(abs(yax)>1e5);
    ROIyinner = find(diff(ROIy)>5);
    ROIybounds = ROIy([ROIyinner ROIyinner+1]);
ROIx = find(abs(xax)>1e5);
    ROIxinner = find(diff(ROIx)>5);
    ROIxbounds = ROIx([ROIxinner ROIxinner+1]);
PLTregion = Gray(ROIybounds(1):ROIybounds(2),ROIxbounds(1):ROIxbounds(2));

PLTregion(PLTregion==255)=nan;
figure(2),imagesc(PLTregion)

[N X]=hist(single(PLTregion(:)),0:255);
figure(3),plot(X,N),set(gca,'yscale','log')

PLTitems = find(N>2000)% %limit "color" of interest to items with >1000 pixels

PLTitems = 1×10

1 67 90 101 129 132 144 167 180 194

PLTvalues = X(PLTitems);
PLTvalues(1)=[]; %ignore black?

%test out region 1
for ind = 1:numel(PLTvalues)
    temp = zeros(size(PLTregion)); 
    temp(PLTregion==PLTvalues(ind) | (PLTregion<=50 & PLTregion>10))=255; 
%     figure(100), imagesc(temp)
    temp = bwareaopen(temp,1000);
    temp = imfill(temp,'holes');
    figure(100), subplot(3,3,ind),imagesc(temp)
    figure(101), subplot(3,3,ind),imagesc(single(PLTregion).*temp,[0 255])
end

Answer 2

[petit]

@Joseph Cheng

Thanks for your detailled answer. I realize there is a lot of work to do more to extract these covariance matrices from this image.

Which track do you suggest me to go deeper in this analysis ?

By chance, do you know external tools which could allow to perform easily this extraction ? Maybe similar functionality in the File exchange forum has been done ?

Best regards