Hi,
I understand that you want to remove the marked spots from the image.
You can follow these steps:
- Read the images using "imread".
- If the images are not already in grayscale, convert them using "rgb2gray".
- Apply a binary threshold using "imbinarize" with Otsu's method.
- Remove noise by filtering out small objects with "bwareaopen".
- Label the connected components with bwlabel or "bwconncomp".
- Identify the largest connected component which is likely to be the curve.
- Remove the largest connected component from the binary image.
- Display the results using "imshow".
Here's the MATLAB code for processing the images:
% Read the images
image1 = imread('path_to_your_first_image.jpg');
image2 = imread('path_to_your_second_image.jpg');
% Convert images to grayscale if they are in RGB
if size(image1, 3) == 3
image1 = rgb2gray(image1);
end
if size(image2, 3) == 3
image2 = rgb2gray(image2);
end
% Binarize images using Otsu's threshold
bw1 = imbinarize(image1);
bw2 = imbinarize(image2);
% Remove small objects (noise)
cleaned1 = bwareaopen(bw1, 50);
cleaned2 = bwareaopen(bw2, 50);
% Label connected components
[label1, num1] = bwlabel(cleaned1);
[label2, num2] = bwlabel(cleaned2);
% Find the largest component for each image
stats1 = regionprops(label1, 'Area');
stats2 = regionprops(label2, 'Area');
[~, largestIdx1] = max([stats1.Area]);
[~, largestIdx2] = max([stats2.Area]);
% Remove the largest component from the images
final1 = cleaned1;
final2 = cleaned2;
final1(label1 == largestIdx1) = 0;
final2(label2 == largestIdx2) = 0;
% Display the results
figure;
subplot(2,2,1), imshow(final1), title('Final Image 1');
subplot(2,2,2), imshow(final2), title('Final Image 2');
Hope this helps!
