Remove image region inside another region

Hello!

Does anyone have an idea of how can I remove some regions surrounded by another region? I would like to set the value of these pixels to 0. Both are already segmented and labelled.

This is an example imagesc:

Thank you very much in advanced!

Maria

Answer 1

[Image Analyst]

You could just fill holes in the binarized labeled image, then relabel if you want

binaryImage = imfill(labeledImage > 0, 'holes');
[binaryImage, numberOfBlobs] = bwlabel(binaryImage);

Change connectivity from 4 to 8 or vice versa to see what effect that has.

Attach your labeled image in a .mat file if you need more help.

[Image Analyst]

Your edges seem to be their own unique regions, but that's okay as long as they're inside the blob, not outside it.

This is what I have so far. Tell me why it's no good. And be specific, like the final blob at location (row, column) is not good for some reason.

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 = 18;

s2 = load('labelled.mat')
s1 = load('original.mat')

imagen_2d_aj = s1.imagen_2d_aj;
subplot(2, 2, 1);
imshow(imagen_2d_aj, []);
axis('on', 'image');
title('Original Image', 'fontSize', fontSize);

labeledImage = s2.mito_fill;
subplot(2, 2, 2);
imshow(labeledImage, []);
axis('on', 'image');
title('Labeled Image', 'fontSize', fontSize);
message = sprintf('Before filling, there are %d blobs.', max(labeledImage(:)));
fprintf('%s\n', message);


% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0.05, 1, 0.95]);

% Let's assign each blob a different color to visually show the user the distinct blobs.
coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle'); % pseudo random color labels
% coloredLabels is an RGB image.  We could have applied a colormap instead (but only with R2014b and later)
subplot(2, 2, 3);
imshow(coloredLabels);
axis('on', 'image'); % Make sure image is not artificially stretched because of screen's aspect ratio.
title(message, 'FontSize', fontSize);

% Fill holes.
binaryImage = imfill(labeledImage > 0, 'holes');
% Relabel
[binaryImage, numberOfBlobs] = bwlabel(binaryImage);
caption = sprintf('After filling, there are %d blobs', numberOfBlobs);
fprintf('%s\n', caption);

% Let's assign each blob a different color to visually show the user the distinct blobs.
coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle'); % pseudo random color labels
% coloredLabels is an RGB image.  We could have applied a colormap instead (but only with R2014b and later)
subplot(2, 2, 4);
imshow(coloredLabels);
axis('on', 'image'); % Make sure image is not artificially stretched because of screen's aspect ratio.
title(caption, 'FontSize', fontSize);

[MARIA RODRIGUEZ SANZ]

Dear Image Analyst,

Thank you again for your interest and efforts

I attach some region captions of ' acceptable' and 'unacceptable' results (skeletonization) in this image when filling holes.

In summary, I want the holes (at least the biggest ones) of the original image to be represented in the labelled image.

I don't know if I'm making myself clear.

Thanks!

Maria

[Image Analyst]

Do you just want to remove nested blobs?

[Raul Benitez]

Yes... That would be ok.

Thanks!

[Image Analyst]

Then use bwboundaries() and look at all outputs. One of them has to do with whether or not a boundary is nested inside any others.

[MARIA RODRIGUEZ SANZ]

No way! I tried 'holes' and 'noholes' options, but none of them gives the expected output. :(

I can not believe that there is no option for what I'm looking for...it seems so simple...it would give me an excellent ouptput for my study.

Just to remember, I just want to set the child blobs of bwboundaries (blobs inside blobs) to black. Or, what is the same, fill them with zeros!.

Any other ideas? Please...

[MARIA RODRIGUEZ SANZ]

Answer 2

[MARIA RODRIGUEZ SANZ]

Dear Image Analyst,

First of all, thanks a lot for your reply!

In fact, I don't want to fill these holes, but quite the opposite.

In my original grayscale image these subregions correspond -in general- to low intensity regions.

First, I find the edges (The best method I have found to segment adjacent objects in my images. It produces really good results!). Then I delimitate objects by bwboundaries(). (That's because I haven't found any method to fill edges regions...), but it's ok.... The resulting image contains lots of subregions that difficult a lot the subsequent steps (My final purpose is to skeletonize the image and I'm getting messy results because of these undesireable subregions.)

I have to be vey careful playing with thresholds, because I have objects with low intensities that I don't want to loose. That's why it is also complicated to remove those regions with a certain intensity in the original image... (bwpropfilt...).

I know it would not be perfect! but just setting this subregions to 0 would help me a lot!

I attach both my original and labbeled image!

Thank you in advanced again!

Answer 3

[Image Analyst]

I've take your simple blob and made a demo image with some similar ones with different numbers of nested blobs and different levels of nesting. I then made a demo specially for you that removes all inner blobs and leaves only the outermost blob. See attached demo.

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;

%===============================================================================
% Read in gray scale demo image.
folder = pwd; % Determine where demo folder is (works with all versions).
baseFileName = 'index.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	fullFileNameOnSearchPath = baseFileName; % No path this time.
	if ~exist(fullFileNameOnSearchPath, 'file')
		% Still didn't find it.  Alert user.
		errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
		uiwait(warndlg(errorMessage));
		return;
	end
end
rgbImage = imread(fullFileName);
% Display the image.
subplot(2, 3, 1);
imshow(rgbImage, []);
title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();

% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(rgbImage)
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
	% 		grayImage = rgb2gray(rgbImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	grayImage = rgbImage(:, :, 2); % Take green channel.
else
	grayImage = rgbImage; % It's already gray scale.
end
% Now it's gray scale with range of 0 to 255.

% Display the histogram of the image.
subplot(2, 3, 2);
[counts, binLocations] = imhist(grayImage);
% Suppress bin 1 because it's so tall
counts(1) = 0;
bar(binLocations, counts);
grid on;
title('Histogram of Image', 'FontSize', fontSize, 'Interpreter', 'None');

%------------------------------------------------------------------------------
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
drawnow;

% Binarize the image
% Get the mask where the region is solid.
binaryImage1 = grayImage > 210;

% Display the image.
subplot(2, 3, 3);
imshow(binaryImage1, []);
title('Initial Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
drawnow;

% Clear borders
binaryImage2 = imclearborder(~binaryImage1);
% Fill holes.
binaryImage2 = imfill(binaryImage2, 'holes');
% Display the image.
subplot(2, 3, 4);
imshow(binaryImage2, []);
title('Filled Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
drawnow;

% Get the background color from the upper left pixel
backgroundIntensity = grayImage(1,1);

% Get the final binary image by erasing the first binary image with the latest mask.
finalMask = binaryImage1 & ~binaryImage2;
% Display the image.
subplot(2, 3, 5);
imshow(finalMask, []);
title('Final Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
drawnow;

% Use it to mask the original image.
finalImage = grayImage; % Initialize
finalImage(~finalMask) = backgroundIntensity; % Erase outside the mask.
% Display the image.
subplot(2, 3, 6);
imshow(finalImage, []);
title('Final, Masked Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');

[MARIA RODRIGUEZ SANZ]

Thank you very much Image Analyst!

It helped me a lot! The secret was in imclearborder!. I love this function! hehe!

thanks! thanks! thanks!