You don't need to enhance the contrast. 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 = '64882.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)
% Crop off screenshot stuff
% rgbImage = rgbImage(132:938, 352:1566, :);
% Display image.
subplot(2, 3, 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;
% Take one of the color channels, whichever one seems to have more contrast..
colorChannelToUse = 3;
grayImage = rgbImage(:, :, colorChannelToUse);
% Display the color segmentation mask image.
subplot(2, 3, 2);
imshow(grayImage, []);
caption = sprintf('Color Channel %d', colorChannelToUse)
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
axis('on', 'image');
drawnow;
%=======================================================================================
% Show the histogram
subplot(2, 3, [3, 6]);
imhist(grayImage);
grid on;
caption = sprintf('Histogram of Color Channel %d', colorChannelToUse)
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
xlabel('Gray Level', 'FontSize', fontSize)
ylabel('Count', 'FontSize', fontSize)
%=======================================================================================
% Threshold the image to get the disk.
lowThreshold = 96;
highThreshold = 255;
% Use interactive File Exchange utility by Image Analyst to to the interactive thresholding.
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image?s_tid=srchtitle
% [lowThreshold, highThreshold] = threshold(114, 255, grayImage);
mask = grayImage >= lowThreshold & grayImage <= highThreshold;
% Now do clean up by hole filling, and getting rid of small blobs.
mask = imfill(mask, 'holes');
mask = bwareafilt(mask, 1); % Take largest blob only.
% Display the color segmentation mask image.
subplot(2, 3, 4);
imshow(mask, []);
title('Final Mask', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
axis('on', 'image');
drawnow;
% Get x and y
boundary = bwboundaries(mask);
x = boundary{1}(:, 2);
y = boundary{1}(:, 1);
subplot(2, 3, 1);
%=======================================================================================
% Find the area and equivalent circular diameter.
props = regionprops(mask, 'Centroid', 'EquivDiameter', 'Area');
% Display image with blob outlined over it.
subplot(2, 3, 5);
imshow(rgbImage, []);
impixelinfo;
axis on;
caption = sprintf('Area = %d pixels. ECD = %.1f pixels.', props.Area, props.EquivDiameter);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Display boundary
hold on;
plot(x, y, 'r-', 'LineWidth', 2);
% Plot centroid.
plot(props.Centroid(1), props.Centroid(2), 'r+', 'LineWidth', 2, 'MarkerSize', 20);
%=======================================================================================
findBoundingCircle = false;
if findBoundingCircle
% Find the minimum bounding circle using John D'Errico's File Exchange
% https://www.mathworks.com/matlabcentral/fileexchange/34767-a-suite-of-minimal-bounding-objects?s_tid=srchtitle
% Get the minimum bounding circle.
hullflag = true;
[center,radius] = minboundcircle(x,y,hullflag)
% Show circle
viscircles(center, radius, 'color', 'r');
caption = sprintf('With Boundary and Bounding Circle');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
end
uiwait(helpdlg('Done!'));
I don't know what you want to do after that. You said something vague about "the details I need to extract" but didn't say what those were.
