Hi Thomas,
I understand that you want to address the following issues in your MATLAB bubble detection workflow:
- Some bubbles have double boundaries
- Some bubbles have their ends disconnected from the frame base
- Some closely located bubbles are detected as a single unit instead of individual bubbles
To improve the results, I preprocessed the given image to detect vertical lines between the bubbles and filled the holes in the shiny parts within the bubbles. This preprocessing step significantly enhanced the results.
Here is the preprocessing code
% Load the image
img = imread('CAM1_C001H001S0014001202.png');
% Convert the image to a binary format
img = ~imbinarize(img);
% Detect edges using the Sobel operator
edges = edge(img, 'sobel');
% Apply the Hough transform to detect lines
[H, T, R] = hough(edges);
% Find peaks in the Hough transform
P = houghpeaks(H, 1000, 'threshold', ceil(0.1 * max(H(:))));
% Extract lines based on the detected peaks
lines = houghlines(edges, T, R, P, 'FillGap', 5, 'MinLength', 3);
% Fill holes in the binary bubble image and modify background
img = imfill(img, 'holes');
img =imclose(img,strel('disk',8));
img =imopen(img,strel('disk',8));
imshow(img);
title('After Pre-Processing')
hold on;
% Initialize an array to store x-coordinates of vertical lines
vertical_lines = [];
% Iterate through the detected lines to find vertical ones
for k = 1:length(lines)
% Get the endpoints of the line
xy = [lines(k).point1; lines(k).point2];
% Calculate the angle of the line
angle = atan2d(diff(xy(:, 2)), diff(xy(:, 1)));
xy(:, 2) = [0, 1024];
if abs(angle) > 80 && abs(angle) < 100
% Store the x-coordinate of the vertical line
vertical_lines = [vertical_lines; xy(1, 1)];
end
end
% Sort the x-coordinates of the vertical lines
vertical_lines = sort(vertical_lines);
goodFilteredLines = [];
% Plot vertical lines that are at least 25 pixels apart
last_x = -inf;
for k = 1:length(vertical_lines)
if vertical_lines(k) - last_x >= 25
goodFilteredLines = [goodFilteredLines, vertical_lines(k)];
last_x = vertical_lines(k);
end
end
% Manually exclude certain false lines from being plotted
% (this step can be avoided by tweaking the line detection parameters appropriately)
for k = 1:length(goodFilteredLines)
if k == 3 || k == 9 || k == 21
continue;
end
plot([goodFilteredLines(k), goodFilteredLines(k)], [0, 1024], 'LineWidth', 1, 'Color', 'k');
end
hold off;
frame = getframe(gca);
capturedImage = frame.cdata;
imgGray = (rgb2gray(capturedImage));
imwrite(imgGray, 'processedImage.png');
Here are the results after preprocessing the image and after applying your algorithm on the preprocessed image:
Hope this helps
Regards,
Vinayak
