Hello Abdullah,
To calculate fiber orientation angles from fluorescence images, you can use image processing techniques to detect and analyze the fibers. MATLAB provides powerful image processing tools that can be helpful for this task. Here’s a general approach to achieve this:Steps to Calculate Fiber Orientation Angles
- Preprocessing:
- Convert the image to grayscale if it's not already.
- Apply filters to enhance the fibers and reduce noise (e.g., Gaussian, median filtering).
2. Edge Detection:
- Use edge detection algorithms like Canny, Sobel, or Prewitt to detect the edges of the fibers.
3. Skeletonization:
- Thin the detected edges to a single-pixel width using skeletonization. This helps in accurately determining the orientation.
4. Hough Transform:
- Use the Hough Transform to detect lines in the image, which correspond to the fibers.
- Extract the orientation angle of each line detected.
5. Analysis:
- Analyze the angles to understand the distribution of fiber orientations.
img = imread('your_fluorescence_image.jpg');
filteredImg = imgaussfilt(grayImg, 2);
edges = edge(filteredImg, 'Canny');
skeleton = bwmorph(edges, 'skel', Inf);
[H, theta, rho] = hough(skeleton);
peaks = houghpeaks(H, 5, 'threshold', ceil(0.3 * max(H(:))));
lines = houghlines(skeleton, theta, rho, peaks);
figure, imshow(img), hold on
xy = [lines(k).point1; lines(k).point2];
plot(xy(:,1), xy(:,2), 'LineWidth', 2, 'Color', 'green');
angle = atan2d(diff(xy(:,2)), diff(xy(:,1)));
fprintf('Fiber %d: Angle = %.2f degrees\n', k, angle);
I hope it helps!