MATLAB: How to get the threshold automatically when converting image from hsv to bw

image processingImage Processing Toolbox

Hi! I have to convert my image from HSV to BW to do all the analysis. But I have a lot of images and I can't adjust the threshold one by one. I have checked some of my images, and the threshold change from 0.1 to 0.4. SO the change is quite large and I can't use a single threshold for all the image.

So does somebody know how can I generate the threshold for each image without manually checking the histogram? I need to choose the threshold after the first pick in the histgram.

I asked a question related to this one before. More info: https://stackoverflow.com/questions/47024527/how-to-segment-the-colony-when-i-cant-use-bw-image

Some of my codes are here:

b=imread('test4.jpg')
hsvIm = rgb2hsv(b) % convert the image to hsv format
imshow(hsvIm)
histogram(hsvIm(:,:,1))
%thresholding on the hue space
bwIm = hsvIm(:,:,1) < 0.3 % the threshold can change from 0.1 to 0.4

I also attach some pictures here:

Thank you in advance!!!

Best Answer

Hmm, I just want to update my question here.

Finally, I don't need to set the threshold separately for each image. I just converted the image from RGB to HSV and then to YCBCR. After the second conversion, the threshold for YCBCR to BW is more or less the same for every image, no matter how different the colony color and size. I'm not really sure whether it is proper to do two conversions. But at least it works.

I also tried to convert RGB directly to YCBCR, but the result is not as good as through two conversions.

The only problem that I still have is that imfindcircles() on bw image doesn't really work well even though I played with the sensitivity and EdgeThreshold, and I don't know why. Do somebody know the possible reason?

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MATLAB: How to separate the whole lip image into upper and lower part using code

Do you mean like 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 = 15;
%===============================================================================

% Get the name of the image the user wants to use.
baseFileName = 'originalimage.jpg';
% Get the full filename, with path prepended.
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.
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    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
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end
%===============================================================================
% Read in demo image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[imageRows, imageColumns, numberOfColorChannels] = size(rgbImage);
% Display the original image.
subplot(3, 3, 1);
imshow(rgbImage, []);
axis on;
caption = sprintf('Original Color Image, %s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% 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;
hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Crop the image
rgbImage = rgbImage(29:391, 87:762, :);
% Convert to HSV color space so we can segment the saturation channel.
hsvImage = rgb2hsv(rgbImage);
sImage = hsvImage(:, :, 2);
% Display the image.





subplot(3, 3, 2);
imshow(sImage, []);
axis on;
caption = sprintf('Saturation Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Display the histogram
subplot(3, 3, 3);
histogram(sImage);
grid on;
title('Histogram of Saturation Image', 'FontSize', fontSize);
% Threshold the image
saturationThreshold = 0.15;
mask = sImage > saturationThreshold;
% Fill holes.
mask = imfill(mask, 'holes');
% Extract the two largest blobs only.
mask = bwareafilt(mask, 2);
% Put a red line at the threshold.
line([saturationThreshold, saturationThreshold], ylim, 'Color', 'r', 'LineWidth', 3);
% Display the image.
subplot(3, 3, 4);
imshow(mask, []);
axis on;
caption = sprintf('Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Give each blob an ID number.
labeledImage = bwlabel(mask);
% Get the top and bottom mask
topMask = ismember(labeledImage, 1);
bottomMask = ismember(labeledImage, 2);
% Display the image.
subplot(3, 3, 5);
imshow(topMask, []);
axis on;
caption = sprintf('Top Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Display the image.
subplot(3, 3, 6);
imshow(bottomMask, []);
axis on;
caption = sprintf('Bottom Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Mask the original RGB image and display.
% Mask the image using bsxfun() function
topMaskedRgbImage = bsxfun(@times, rgbImage, cast(topMask, 'like', rgbImage));
bottomMaskedRgbImage = bsxfun(@times, rgbImage, cast(bottomMask, 'like', rgbImage));
% Display the image.
subplot(3, 3, 7);
imshow(topMaskedRgbImage, []);
axis on;
caption = sprintf('Top Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
% Display the image.
subplot(3, 3, 8);
imshow(bottomMaskedRgbImage, []);
axis on;
caption = sprintf('Bottom Mask Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;

MATLAB: Binary Image – Black region detection

Mohsina, 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 short g;
format compact;
fontSize = 25;
%===============================================================================

% Get the name of the image the user wants to use.
baseFileName = 'image1.png';
% Get the full filename, with path prepended.
folder = []; % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);
%===============================================================================
% Read in a demo image.
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, []);
axis on;
axis image;
caption = sprintf('Original Gray Scale Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0, 1, 1]);
% 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;
% Create binary image of the black blobs from grayscale image.
binaryImage = grayImage == 0;
% Get rid of the background.
binaryImage = imclearborder(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Label the blobs
[labeledImage, numBlobs] = bwlabel(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% 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;
axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
caption = sprintf('Pseudo colored labels, from label2rgb().');
title(caption, 'FontSize', fontSize);
drawnow;
% Make measurements of bounding box.
props = regionprops(labeledImage, 'BoundingBox');
% Display the image.
subplot(2, 2, 4);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image with Boxes', 'FontSize', fontSize, 'Interpreter', 'None');
% Display the bounding boxes around them.
hold on;
for k = 1 : numBlobs
  thisBoundingBox = props(k).BoundingBox
  rectangle('Position', thisBoundingBox, ...
    'EdgeColor', 'c', 'LineWidth', 2);
end

Best Answer

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MATLAB: How to separate the whole lip image into upper and lower part using code

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