Hey All
I am working on a project involving photos from a live feed of quantum wire dots and I was wondering what might be the best approach for isolating the circles and the excited laser properly. My current code can sometimes lead to mistakes and non-circular formations. Any help would be much appreciated. I have shared my current code as well as an image comparison below!
I = "QD.jpg"
%loads image from a file into an array
Img = imread(I);

%grayscales image for easier analysis
ImgGray = im2gray(Img);

%makes a clear contrast between foreground and background
adjustedImg = imadjust(ImgGray);

%binarizing image into 0(black) and 1(white)
BwImg = imbinarize(adjustedImg, ‘adaptive’, ‘ForegroundPolarity’, ‘dark’, ‘Sensitivity’, 0.4);

%inverting it so that foreground appears as white and background as black
invertedBwImg = ~BwImg;

%morpholigically changing the image by opening and closing, in this case removing small white
%objects from black background and removing the remaining black spots from
%the white patches
se = strel("disk",15);
openedImg = imopen(invertedBwImg,se);
closedImg = imclose(openedImg,se);

% Apply a threshold to keep only pixels above the threshold value
thresholdedImg = ImgGray > 120;

% Multiply the original grayscale image by the threshold mask to keep pixel values
excitedimg = uint8(thresholdedImg) .* ImgGray;

% Label connected components
labeledImg = bwlabel(closedImg);

% Measure properties of image regions
stats = regionprops(labeledImg, ‘Eccentricity’);

% Define an eccentricity threshold
eccentricityThreshold = 0.76;

% Initialize a mask for the filtered image
filteredImg = ismember(labeledImg, find([stats.Eccentricity] < eccentricityThreshold));

% Convert logical image(filterImg) to uint8 image in order to comebine with
% excitedimage
uint8Img = uint8(filteredImg) * 255;

%final image with excited light and quantum wires
finalImg = uint8Img + excitedimg;

% Create a new figure for displaying images
figure;

% Display the original image
subplot(1, 2, 1);
imshow(Img);
title(‘Original Image’);

% Display the filtered binary image
subplot(1, 2, 2);
imshow(finalImg);
title(‘Updated Result’);

% Return the figure handle as the result
result = gcf;Hey All
I am working on a project involving photos from a live feed of quantum wire dots and I was wondering what might be the best approach for isolating the circles and the excited laser properly. My current code can sometimes lead to mistakes and non-circular formations. Any help would be much appreciated. I have shared my current code as well as an image comparison below!
I = "QD.jpg"
%loads image from a file into an array
Img = imread(I);

%grayscales image for easier analysis
ImgGray = im2gray(Img);

%makes a clear contrast between foreground and background
adjustedImg = imadjust(ImgGray);

%binarizing image into 0(black) and 1(white)
BwImg = imbinarize(adjustedImg, ‘adaptive’, ‘ForegroundPolarity’, ‘dark’, ‘Sensitivity’, 0.4);

%inverting it so that foreground appears as white and background as black
invertedBwImg = ~BwImg;

%morpholigically changing the image by opening and closing, in this case removing small white
%objects from black background and removing the remaining black spots from
%the white patches
se = strel("disk",15);
openedImg = imopen(invertedBwImg,se);
closedImg = imclose(openedImg,se);

% Apply a threshold to keep only pixels above the threshold value
thresholdedImg = ImgGray > 120;

% Multiply the original grayscale image by the threshold mask to keep pixel values
excitedimg = uint8(thresholdedImg) .* ImgGray;

% Label connected components
labeledImg = bwlabel(closedImg);

% Measure properties of image regions
stats = regionprops(labeledImg, ‘Eccentricity’);

% Define an eccentricity threshold
eccentricityThreshold = 0.76;

% Initialize a mask for the filtered image
filteredImg = ismember(labeledImg, find([stats.Eccentricity] < eccentricityThreshold));

% Convert logical image(filterImg) to uint8 image in order to comebine with
% excitedimage
uint8Img = uint8(filteredImg) * 255;

%final image with excited light and quantum wires
finalImg = uint8Img + excitedimg;

% Create a new figure for displaying images
figure;

% Display the original image
subplot(1, 2, 1);
imshow(Img);
title(‘Original Image’);

% Display the filtered binary image
subplot(1, 2, 2);
imshow(finalImg);
title(‘Updated Result’);

% Return the figure handle as the result
result = gcf; Hey All
I am working on a project involving photos from a live feed of quantum wire dots and I was wondering what might be the best approach for isolating the circles and the excited laser properly. My current code can sometimes lead to mistakes and non-circular formations. Any help would be much appreciated. I have shared my current code as well as an image comparison below!
I = "QD.jpg"
%loads image from a file into an array
Img = imread(I);

%grayscales image for easier analysis
ImgGray = im2gray(Img);

%makes a clear contrast between foreground and background
adjustedImg = imadjust(ImgGray);

%binarizing image into 0(black) and 1(white)
BwImg = imbinarize(adjustedImg, ‘adaptive’, ‘ForegroundPolarity’, ‘dark’, ‘Sensitivity’, 0.4);

%inverting it so that foreground appears as white and background as black
invertedBwImg = ~BwImg;

%morpholigically changing the image by opening and closing, in this case removing small white
%objects from black background and removing the remaining black spots from
%the white patches
se = strel("disk",15);
openedImg = imopen(invertedBwImg,se);
closedImg = imclose(openedImg,se);

% Apply a threshold to keep only pixels above the threshold value
thresholdedImg = ImgGray > 120;

% Multiply the original grayscale image by the threshold mask to keep pixel values
excitedimg = uint8(thresholdedImg) .* ImgGray;

% Label connected components
labeledImg = bwlabel(closedImg);

% Measure properties of image regions
stats = regionprops(labeledImg, ‘Eccentricity’);

% Define an eccentricity threshold
eccentricityThreshold = 0.76;

% Initialize a mask for the filtered image
filteredImg = ismember(labeledImg, find([stats.Eccentricity] < eccentricityThreshold));

% Convert logical image(filterImg) to uint8 image in order to comebine with
% excitedimage
uint8Img = uint8(filteredImg) * 255;

%final image with excited light and quantum wires
finalImg = uint8Img + excitedimg;

% Create a new figure for displaying images
figure;

% Display the original image
subplot(1, 2, 1);
imshow(Img);
title(‘Original Image’);

% Display the filtered binary image
subplot(1, 2, 2);
imshow(finalImg);
title(‘Updated Result’);

% Return the figure handle as the result
result = gcf; image processing, image segmentation, quantum dot MATLAB Answers — New Questions

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