MATLAB: How to find center position of image?

Question

Answer 1

Depends on how you define the center of the image. If you mean the weighted centroid of the bright pattern, you can use 'WieghtedCentroid' in regionprops(). If you look at the whole image, the centroid is somewhat to the lower right of the bright blob's center. If you threshold it, it tends to go closer but it depends on what threshold you pick. By the way, your image is saturated (clipped) in the center which means you can't get the brightest of the image. Anyway, try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 22;
%--------------------------------------------------------------------------------------------------------

%    READ IN IMAGE
folder = pwd;
baseFileName = 'image.jpeg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% The file doesn't exist -- didn't find it there in that folder.
	% Check the entire search path (other folders) for the file by stripping off the folder.
	fullFileNameOnSearchPath = baseFileName; % No path this time.
	if ~exist(fullFileNameOnSearchPath, 'file')
		% Still didn't find it.  Alert user.
		errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
		uiwait(warndlg(errorMessage));
		return;
	end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
	grayImage = rgb2gray(grayImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	% grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the image.
imshow(grayImage, []);
axis('on', 'image');
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
% Get a mask that is the entire image.
% mask = true(size(grayImage));
% Alternative : get a mask that is the thresholded part of the image.
mask = bwconvhull(grayImage > 75);
% Get the boundary of the mask
b = bwboundaries(mask);
b = b{1};
% Plot boundary over image.
xb = b(:, 2);
yb = b(:, 1);
hold on;
plot(xb, yb, 'r-', 'LineWidth', 2);
% Get the area of each blob.
props = regionprops(mask, grayImage, 'WeightedCentroid');
xCenter = props.WeightedCentroid(1);
yCenter = props.WeightedCentroid(2);
% Show centroid on image.
xline(xCenter, 'LineWidth', 2, 'Color', 'r');
yline(yCenter, 'LineWidth', 2, 'Color', 'r');
caption = sprintf('Weighted Centroid at (x,y) = (%.2f, %.2f)', xCenter, yCenter);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
msgbox('Done');