MATLAB: How to blend an image that is a non-rectangular mask with a background image

Image Processing Toolboximagesimmultiplyinfuse

Okay, I'm stumped.

I have a background image and I want to put a circular mask image on top of it, blended together 50-50 for everything within the circle. I want to stick with images and not use figures so that I can view the results with imagesc(image).

If pic1 is the full image that is cropped into the circle, and pC is a black circle on a white background with dimensions bCx, bCy, I use this to add in the image I want.

pzzc = imadd(pic1(bCx,bCy,:),pC);

I now have a circle with the original image in it and a white background. So far so good.

I now want to combine that image with the background image, such as this.

pzzz = imfuse(pzzz, pzzc,'blend');

The problem is that this doesn't work, as I can't get rid of the square bounding box around the circle image, since it's a mean of the 2 images, white and background.

immultiply doesn't work either. With this alternate approach:

pzz = immultiply(uint16(pzzz(bCx,bCy,:)), uint16(pzzc)); % IMAGE AND BACKGROUND
pzzz(bCx,bCy,:) = uint8(pzz);

pzz has the circle correct but is unblended, and the masked part of pzzz just comes out white.

If I have to I can live with the unblended image, but I don't understand why the masked part of the full image is white.

A full code example below:

clear all
pic1 = imread('visionteam.tif');
[x,y,z] = size(pic1);
pzzz = 20-uint8(zeros(x, y, z));
% ADD A DARK GRAY TO BACKGROUND IMAGE TO SEE IF CIRCLE LOSES BACKGROUND WHITE AREA
 
pC = imread('Circle1000x1000.tif'); % 1000 X 1000 BLACK CIRCLE WITH WHITE BACKGROUND
bbox = [86 52 70 70];    % X Y H W
 
pC = imresize(pC,[bbox(1,3), bbox(1,4)]); % RESIZE CIRCLE TO BB DIMENSIONS
bCx = bbox(1,1):bbox(1,1)+bbox(1,3)-1; % FIND X AND Y AREA OF BB
bCy = bbox(1,2):bbox(1,2)+bbox(1,3)-1;
 
mask = imadd(pic1(bCx,bCy,:),pC); % ADD Visionteam IMAGE INSIDE CIRCLE
mask = uint8(mask);
 
pzzz(bCx,bCy,:) = immultiply(uint16(pzzz(bCx,bCy,:)), uint16(mask))/255;
pzzz = uint8(pzzz);
imagesc(pzzz)

Best Answer

Please attach 'visionteam.tif' and 'Circle1000x1000.tif' or two similar images.

What I'd do is to make a mask and then convert to double, then add, and convert back to uint8. Untested code:

% Now sum with opacity factor
factor = 0.5;
sumImage = uint8(factor * double(backgroundImage) + (1 - factor) * teamImage);
% Mask the sum image using bsxfun() function to multiply the mask by each channel individually. 
maskedTeamImage = bsxfun(@times, sumImage, cast(circleMask, 'like', sumImage));
% Burn a black circle into the background so we can add them there.
maskedBackgroundImage = bsxfun(@times, backgroundImage, cast(~circleMask, 'like', teamImage));
% Now simply sum them up to fill in the circle with the 50/50 blended circle patch.
outputImage = maskedBackgroundImage + maskedTeamImage; % Initialize

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MATLAB: Obtain average image threshold without the background

Try this:

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 = 22;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'image.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
grayImage = imread(fullFileName);
% 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(grayImage);
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(grayImage);
	% 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 = grayImage(:, :, 2); % Take green channel.
end
% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image of just the blob and not including the black background or the white surround.
mask = grayImage > 0 & grayImage < 255;  %imbinarize(grayImage);
subplot(2, 2, 2);
imshow(mask, []);
impixelinfo;
title('Initial Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Display histogram of image but only the image within the mask
subplot(2, 3, 4);
histogram(grayImage(mask), 0:255);
grid on;
title('Histogram of gray image', 'FontSize', fontSize);
% Now get the threshold
thresh = 255 * graythresh(grayImage(mask))
% Put a red line there at the threshold
xline(thresh, 'Color', 'r', 'LineWidth', 2);
% Get a binary image of the bright stuff
brightStuff = grayImage >= thresh & mask;
subplot(2, 3, 5);
imshow(brightStuff, []);
impixelinfo;
title('Bright Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
subplot(2, 3, 6);
darkStuff = ~brightStuff & mask;
imshow(darkStuff, []);
impixelinfo;
title('Dark Pixels in Region', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;

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Try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'A1.jpg';
folder = pwd;
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
%=======================================================================================
% Read in demo image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage)
% Display image.
subplot(2, 2, 1);
imshow(rgbImage, []);
impixelinfo;
axis on;
caption = sprintf('Original Color Image\n%s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% 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;
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% get a mask for the red line.
mask = redChannel > greenChannel;
% Display the image.


subplot(2, 2, 2);
imshow(mask);
caption = sprintf('Color Segmentation Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
axis('on', 'image');
drawnow;
% fill holes.
mask = imfill(mask, 'holes');
% Take the largest blob only.
mask = bwareafilt(mask, 1);
% Shrink two layers of pixels to come inside the red lines.
mask = imerode(mask, true(5));
% Display the image.
subplot(2, 2, 3);
imshow(mask);
title('Final Mask', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
axis('on', 'image');
% Get a masked image.
% Mask the image using bsxfun() function to multiply the mask by each channel individually.
maskedRgbImage = bsxfun(@times, rgbImage, cast(mask, 'like', rgbImage));
% Display the image.
subplot(2, 2, 4);
imshow(maskedRgbImage);
title('Masked RGB Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
axis('on', 'image');
% Tell user the answer.
message = sprintf('Done!');
uiwait(helpdlg(message));

Best Answer

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