MATLAB: How can i apply conditional dilation on the input image so that i can get the shown output image.

digital image processingdilationImage Processing Toolbox

Best Answer

I don't think the neckline/chest below the chin is important, especially because it will vary a lot depending on what kind of shirt the subject is wearing. Therefore I'd find just the head. To do that I'd scan only the bottom half of the image, where I assume the narrowest part of the neck will be, and find the line (row) in the image that has the greatest percentage of black in it, just looking at the black from 1 to the first white pixel and from the last white pixel to the end - use find() for that computation.

Then I'd draw a white line across at that line and fill just between the half way point and the line with imfill(). Let us know if you can't figure it out.

Related Solutions

MATLAB: Draw pixels within threshold interval

Try this demo. It uses the thresholds to get a mask than erases outside that mask. Then it makes a colormap and applies it only within the threshold range. Adapt as needed.

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 = 'cameraman.tif';
grayImage = imread(baseFileName);
% 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 with the original, linear colormap.
subplot(2, 2, 1);
cmap = jet(256);
imshow(grayImage, 'Colormap', cmap);
axis('on', 'image');
title('Original Color Map', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
colorbar;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
set(gca,'ColorScale','log')
%--------------------------------------------------------------------------------------------------------
% Show the histogram:
subplot(2, 2, 2);
imhist(grayImage);
grid on;
title('Histogram', 'FontSize', fontSize, 'Interpreter', 'None');
minGL = 150;
maxGL = 190;
xline(minGL, 'Color', 'r', 'LineWidth', 2);
xline(maxGL, 'Color', 'r', 'LineWidth', 2);
%--------------------------------------------------------------------------------------------------------
% BINARIZE THE IMAGE
mask = grayImage >= minGL & grayImage <= maxGL;
%--------------------------------------------------------------------------------------------------------
% Display the mask.
subplot(2, 2, 3);
imshow(mask);
axis('on', 'image');
title('Mask', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
colorbar;
drawnow;
%--------------------------------------------------------------------------------------------------------
% Apply the mask
maskedImage = grayImage; % Initialize
maskedImage(~mask) = 0; % Erase outside of mask
subplot(2, 2, 4);
imshow(maskedImage, 'Colormap', cmap);
axis('on', 'image');
caption = sprintf('Masked Image with color map applied between %d and %d', minGL, maxGL);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
colorbar;
caxis([minGL, maxGL]);
drawnow;

MATLAB: Crop dark area and display the face only

Convert to grayscale and then threshold and find the bounding box

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
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 the color image.
folder = pwd;
baseFileName = 'm2.bmp';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 3, 1);
imshow(rgbImage, []);
axis on;
title('Original Color Image', 'FontSize', fontSize);
drawnow;
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Histogram the red channel, but there is a huge spike at 255 so let's not count those.
subplot(2, 3, 2);
grayImage = rgb2gray(rgbImage);
imshow(grayImage, []);
title('Gray Scale version', 'FontSize', fontSize);
subplot(2, 3, 3);
histogram(grayImage(grayImage<255))
grid on;
title('Histogram of Gray Scale Image', 'FontSize', fontSize);
someThresholdValue = 150;
binaryImage = grayImage > someThresholdValue;
% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);
subplot(2, 3, 4);
imshow(binaryImage);
grid on;
title('Binary Image', 'FontSize', fontSize);
% Label the binary image.
labeledImage = bwlabel(binaryImage);
props = regionprops(labeledImage, 'BoundingBox');
bbox = props.BoundingBox
croppedImageRGB = imcrop(rgbImage, bbox);
subplot(2, 3, 5);
imshow(croppedImageRGB);
grid on;
title('Cropped RGB Image', 'FontSize', fontSize);
% Gray scale version of cropped image
croppedImageGray = imcrop(grayImage, bbox);
subplot(2, 3, 6);
imshow(croppedImageGray);
grid on;
title('Cropped Gray Scale Image', 'FontSize', fontSize);

Best Answer

Related Solutions

MATLAB: Draw pixels within threshold interval

MATLAB: Crop dark area and display the face only

Related Question