How to crop square of size 100 X 100 around the centroid of an image?

I have a binary image with centroid and I want to crop 100 X 100 image patch from the centroid of the image. I tried using imrect command and imcrop command. But it does not give automatic extraction of that patch instead I need to drag and place the square. Please help with MATLAB code for this.

[Jose Marques]

Send the code! = D

[Manjiree Waikar]

if true
  % code
h = imrect(gca, [100 100 100 100]);                     %creates draggable rectangle on the object specified by gca
position = wait(h);                                 %blocks the MATLAB command line and waits until the timer stops running.
position = getPosition(h);
croppedImage = imcrop(binaryImage, position);
figure;
subplot(1,2,1)
imshow(binaryImage)
title('Region of Interest');
end

I don't know how to extract a patch with reference to centroid.

[Manjiree Waikar]

Sir I made some changes in the code but I am not getting desirable position. I have attached the input image for the above and my code too.

if true
  % code
clear all; %*bold*
close all;
clc;
fontSize = 13;
rgbImage = imread(imgetfile);
% Display the original color image.
subplot(2, 2, 1);
imshow(rgbImage);
title('Original Color Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0, 1, 1]);
grayImage = rgb2gray(rgbImage);
% Display the image.
subplot(2, 2, 2);
imshow(grayImage);
title('Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0, 1, 1]);
media = round(mean(mean(grayImage)));
% img_bin = imbinarize(grayImage,media);
% afterOpening = imopen(img_bin,se);
b = grayImage<media;
b = imfill(b, 'holes');
% Label the image
[rows, columns, numberOfColorBands] = size(grayImage);
circleCenterX = 120; 
circleCenterY =  120; % square area 0f 500*500 
circleRadius = 110;    % big circle radius 
circleImage = false(rows, columns); 
[x, y] = meshgrid(1:columns, 1:rows); 
circleImage((x - circleCenterX).^2 + (y - circleCenterY).^2 <= circleRadius.^2) = true;
b = and(circleImage,b);
labeledImage = bwlabel(b);
measurements = regionprops(labeledImage, 'BoundingBox', 'Area');
matrix = zeros(4,length(measurements));
vector = zeros(1,length(measurements));
for k = 1 : length(measurements)
thisBB = measurements(k).BoundingBox;
matrix(:,k) = thisBB(:);
vector(k) = thisBB(2);
rectangle('Position', [thisBB(1),thisBB(2),thisBB(3),thisBB(4)],...
'EdgeColor','g','LineWidth',2 )
end
vector = sort(vector);
% Let's extract the biggest blob - that will be the hand.
allAreas = [measurements.Area];
[sortedAreas, sortingIndexes] = sort(allAreas, 'descend');
handIndex1 = sortingIndexes(1);
% Use ismember() to extract the hand from the labeled image.
handImage1 = ismember(labeledImage, handIndex1);
% Now binarize
handImage1 = handImage1 > 0;
se = strel('disk',5);
handImage1 = imerode(handImage1,se);
% Display the binary image.
subplot(2, 2, 3);
imshow(handImage1);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
subplot(2,2,4);
imshow(handImage1);
title('binary image with border');
boundaries=bwboundaries(handImage1);
x = boundaries{1}(:, 2);
y = boundaries{1}(:, 1);
hold on;
plot(x, y, 'black', 'LineWidth', 2);
newImage = bwlabel(handImage1);
measurements = regionprops(newImage, 'Centroid', 'BoundingBox');
xCentroid = measurements.Centroid(1);
yCentroid = measurements.Centroid(2);
figure;
imshow(newImage);
title('Binary Image with Centroid Marked'); 
hold on;
plot(xCentroid, yCentroid, 'r*', 'MarkerSize', 10, 'LineWidth', 2);
h = imrect(gca, [100 100 100 100]);                     %creates draggable rectangle on the object specified by gca
% position = wait(h);                                 %blocks the MATLAB command line and waits until the timer stops running.
% position = getPosition(h);
croppedImage = imcrop(grayImage, [xCentroid-50 yCentroid-50 xCentroid yCentroid]);
figure;
imshow(croppedImage);
end

Answer 1

[Jose Marques]

Change x_cent and y_cent for your centroids; change the name of images variables

    x_cent = 120;
    y_cent = 150;
    size_of_cropped_img = 100;

    centroide = [x_cent y_cent];
    I = imread('circuit.tif');
    imshow(I);
    %I2 = imcrop(I,rect) crops the image I. rect is a four-element position vector of the
    %form [xmin ymin width height] that specifies the size and position of the crop rectangle. 
    %imcrop returns the cropped image, I2.
    xmin = x_cent-size_of_cropped_img/2;
    ymin = y_cent-size_of_cropped_img/2;
    I2 = imcrop(I,[xmin ymin size_of_cropped_img size_of_cropped_img]);
    figure();
    imshow(I2)

[Manjiree Waikar]

Change those values means where? I didn't get that sir.

[Jose Marques]

clear all; %*bold*
close all;
clc;
fontSize = 13;
rgbImage = imread(imgetfile);
% Display the original color image.
subplot(2, 2, 1);
imshow(rgbImage);
title('Original Color Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0, 1, 1]);
grayImage = rgb2gray(rgbImage);
% Display the image.
subplot(2, 2, 2);
imshow(grayImage);
title('Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0, 1, 1]);
media = round(mean(mean(grayImage)));
% img_bin = imbinarize(grayImage,media);
% afterOpening = imopen(img_bin,se);
b = grayImage<media;
b = imfill(b, 'holes');
% Label the image
[rows, columns, numberOfColorBands] = size(grayImage);
circleCenterX = 120;
circleCenterY =  120; % square area 0f 500*500
circleRadius = 110;    % big circle radius
circleImage = false(rows, columns);
[x, y] = meshgrid(1:columns, 1:rows);
circleImage((x - circleCenterX).^2 + (y - circleCenterY).^2 <= circleRadius.^2) = true;
b = and(circleImage,b);
labeledImage = bwlabel(b);
measurements = regionprops(labeledImage, 'BoundingBox', 'Area');
matrix = zeros(4,length(measurements));
vector = zeros(1,length(measurements));
for k = 1 : length(measurements)
    thisBB = measurements(k).BoundingBox;
    matrix(:,k) = thisBB(:);
    vector(k) = thisBB(2);
    rectangle('Position', [thisBB(1),thisBB(2),thisBB(3),thisBB(4)],...
        'EdgeColor','g','LineWidth',2 )
end
vector = sort(vector);
% Let's extract the biggest blob - that will be the hand.
allAreas = [measurements.Area];
[sortedAreas, sortingIndexes] = sort(allAreas, 'descend');
handIndex1 = sortingIndexes(1);
% Use ismember() to extract the hand from the labeled image.
handImage1 = ismember(labeledImage, handIndex1);
% Now binarize
handImage1 = handImage1 > 0;
se = strel('disk',5);
handImage1 = imerode(handImage1,se);
% Display the binary image.
subplot(2, 2, 3);
imshow(handImage1);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
subplot(2,2,4);
imshow(handImage1);
title('binary image with border');
boundaries=bwboundaries(handImage1);
x = boundaries{1}(:, 2);
y = boundaries{1}(:, 1);
hold on;
plot(x, y, 'black', 'LineWidth', 2);
newImage = bwlabel(handImage1);
measurements = regionprops(newImage, 'Centroid', 'BoundingBox');
xCentroid = measurements.Centroid(1);
yCentroid = measurements.Centroid(2);
figure;
imshow(newImage);
title('Binary Image with Centroid Marked');
hold on;
plot(xCentroid, yCentroid, 'r*', 'MarkerSize', 10, 'LineWidth', 2);
%h = imrect(gca, [100 100 100 100]);                     %creates draggable rectangle on the object specified by gca
% position = wait(h);                                 %blocks the MATLAB command line and waits until the timer stops running.
% position = getPosition(h);
croppedImage = imcrop(grayImage, [xCentroid-50 yCentroid-50 100 100]);
figure;
imshow(croppedImage);

[Jose Marques]

I changed the line:

croppedImage = imcrop(grayImage, [xCentroid-50 yCentroid-50 100 100]);

[Manjiree Waikar]

Oh I got it. Thank you sir but why did you take "x_cent = 120 and y_cent = 150;" those particular values only? Means how did you determined those values? Is there any method for this?

[Jose Marques]

It was random values. I take from my head.

[Manjiree Waikar]

Okay thank you so much sir for your valuable help.