I have the following code:
clc;
clear all;
% This part reads and shows the image selected
I = imread('115.2.jpg');
imshow(I)
% Ginput is used to select the Hinge position
[x,y] = ginput(1)
% drawpoint is used to mark the Hinge position
h = drawpoint('Position',[x y]);
% Convert the RGB image to a Grayscale image
G=im2gray(I);
level = graythresh(G)
% Binarize the grayscale image
BW = imbinarize(G,level);
% Display the Grayscale image
figure
title('Grayscale Image')
imshow(G)
% Display the Binarized image
figure
title('Binarized')
imshow(BW)
% Fill holes
BW2 = imfill(BW,'holes');
% Display the Image after filling holes
figure
imshow(BW2)
title('Filled Image')
% Mark the Hinge here as well
h = drawpoint('Position',[x y]);
imwrite(BW2, 'BW2.jpg')
% Find the centroid
measurements = regionprops(BW2, 'Centroid');
imshow(BW2);
centroids = cat(1,measurements.Centroid);
hold on;
plot(centroids(:,1), centroids(:,2), 'r+', 'MarkerSize', 30, 'LineWidth', 1);
hold off;
Kshitij Singh answered . 2024-05-18 12:06:27
Since you're working with a binary image here, BW2, you can use the bwpropfilt function to clean up the small areas.
BW2 = bwpropfilt(BW2, 'Area', 1);
The last input argument determines the largest # of regions to keep, so it can be lowered to just the one. From there regionprops would only detect the single centroid.
You could also pass area as an input to regionprops as it is and use the centroid of the largest area.
measurements = regionprops(BW2, 'Centroid', 'Area'); [~,ind] = max(cat(1,measurements.Area)); centroid = measurements(ind).Centroid;
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