MATLAB: How to automatically crop only the region of face and neck from the front view and side view images of a person

image processingImage Processing ToolboxMATLAB

I have been able to convert the whole image into a binary image and do my processing further on the image but i specifically want to do something with the neck of a person. I have 30 people in my data set, I have to have a universal code that works for all 30 people's image in one go, I have been able to do everything just I want an automatic method in which I feed in the binary images of side view and front view of the person and it either returns me the cropped face+neck part or stores the cropped portion in some directory. Here's the code where I am manually cropping the image and going further with processing.
if true
  file2 = 'Dilfr.jpg';
  file2r = imread(file2);
  f2 = rgb2gray(file2r);
  f3 = imbinarize(f2,'adaptive');
  imcrop(f3); %%%I need an automatic replacement here
  f4 = 'dcrop2.jpg';
  F1 = imread(f4);
  F2 = im2bw(F1);
  filled = imfill(F2,'holes');
  holes = filled & ~F2;
  bigholes = bwareaopen(holes, 800);  
  F3 = bigholes;
    figure,
    imshow(F3);
  end

Best Answer

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 = 20;
%===============================================================================
% Read in gray scale demo image.
folder = pwd; % Determine where demo folder is (works with all versions).
baseFileName = 'dilfr.JPG';
% 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);
% 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 image.



subplot(2, 3, 1);
imshow(grayImage, []);
title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
%------------------------------------------------------------------------------
% 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;
% Show the histogram

subplot(2, 3, 2);
[counts, grayLevels] = histcounts(grayImage(:));
counts(counts == max(counts)) = 0; % Suppress spike

bar(grayLevels(1:end-1), counts);
grid on;
title('Histogram of Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Median Filter to get rid of seams in wall.
windowSize = 11;
mfImage = medfilt2(grayImage, [windowSize, windowSize]);
% Display the image.
subplot(2, 3, 3);
imshow(mfImage, []);
title('Median Filtered Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
windowSize = 13;
sdImage = stdfilt(mfImage, ones(windowSize));
% Display the image.
subplot(2, 3, 4);
imshow(sdImage, []);
title('Standard Deviation Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
% Show the histogram
subplot(2, 3, 5);
[counts, grayLevels] = histcounts(sdImage(:));
counts(counts == max(counts)) = 0; % Suppress spike
bar(grayLevels(1:end-1), counts);
grid on;
title('Histogram of Standard Deviation Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Binarize the image
binaryImage = sdImage >= 25;
% Remove blobs touching border.
binaryImage = imclearborder(binaryImage);
% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);
% Display the image.
subplot(2, 3, 6);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
% Get widths as a function of row
widths = zeros(rows, 1);
for row = 1 : rows
  col1 = find(binaryImage(row, :), 1, 'first');
  col2 = find(binaryImage(row, :), 1, 'last');
  if ~isempty(col1)
    widths(row) = col2 - col1 + 1;
  end
end
figure
subplot(2, 1, 1);
plot(widths, 'b-', 'LineWidth', 2);
xlabel('Row', 'FontSize', fontSize);
ylabel('Width', 'FontSize', fontSize);
% Find valleys byinverting and finding peaks
[peakValues, indexes] = findpeaks(-widths);
peakValues = -peakValues; % Negate to flip over.
grid on;
hold on;
plot(indexes, peakValues, 'r+', 'MarkerSize', 12, 'LineWidth', 2);
% The neck is the first peak.
neckRow = indexes(1);
% Display the original image again.
subplot(2, 1, 2);
imshow(grayImage, []);
axis('on', 'image');
title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
% Put a line up over the neck.
hold on;
line(xlim, [neckRow, neckRow], 'Color', 'r', 'LineWidth', 2);
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);
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