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problem with centroid of binary image

Asked by nadia naji on 10 Feb 2013

hi i use bwconncomp and regionprob with centroid feature to find centroid of binary image but i cant understand one thing? if i use centroid feature, it return one point or a structure of points? when i use this i have a structure of point that i think it is wrong do you have any idea?

2 Comments

nadia naji on 10 Feb 2013

i need to consider the behavior of centroid of binary image (with several object in that image ) in sequential frame of video and show them the number of object can be different in each frame. how can i do it? pls help me?

nadia naji

2 Answers

Answer by Walter Roberson on 10 Feb 2013
Accepted answer

Note that if your "binary array" is a numeric datatype, with 0's and 1's, rather than a logical array (false and true's), then regionprops will treat the numeric array as if it is a labeled array that happens to contain only one label. To avoid that, call bwlabel() to separate out the blobls.

labelarray = bwlabel(not_really_binary_Image));
measurements = regionprops(labelarray, 'Centroid');

then measurements will be a struct array with the field 'Centroid' for each blob. Each of the 'Centroid' fields will be a vector whose length matches the dimension of the image (usually 2).

11 Comments

Image Analyst on 11 Feb 2013

Please post your image. I don't like working "blind."

nadia naji on 11 Feb 2013

thanks a lot it works by using double i really appreciate your help

Image Analyst on 11 Feb 2013

How did you end up with a double? That's not normally the case. Usually you process the image to a point where you can threshold it and get a binary image. You said you had a binary image (logical) but now you say you have a double image. Something's weird.

Walter Roberson
Answer by Image Analyst on 10 Feb 2013
Edited by Image Analyst on 10 Feb 2013

regionprops returns a structure array. Each element in the array is a structure with all the measurements for that one blob. Centroid or WeightedCentroid might be one of those measurements, if you asked regionprops to calculate it. It will be a 2 element array. For example, for blob #k,

measurements = regionprops(binaryImage, 'Centriod');
theCentroid = measurements(k).Centroid; % for blob #k only

Perhaps this demo will help:

% Demo to have the user freehand draw an irregular shape over
% a gray scale image, have it extract only that part to a new image,
% and to calculate the mean intensity value of the image within that shape.
% Also calculates the perimeter, centroid, and center of mass (weighted centroid).
% Change the current folder to the folder of this m-file.
if(~isdeployed)
	cd(fileparts(which(mfilename)));
end
clc;	% Clear command window.
clear;	% Delete all variables.
close all;	% Close all figure windows except those created by imtool.
imtool close all;	% Close all figure windows created by imtool.
workspace;	% Make sure the workspace panel is showing.
fontSize = 16;
% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'cameraman.tif';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
	% File doesn't exist -- didn't find it there.  Check the search path for it.
	fullFileName = baseFileName; % No path this time.
	if ~exist(fullFileName, '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);
imshow(grayImage, []);
axis on;
title('Original Grayscale Image', 'FontSize', fontSize);
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
message = sprintf('Left click and hold to begin drawing.\nSimply lift the mouse button to finish');
uiwait(msgbox(message));
hFH = imfreehand();
% Create a binary image ("mask") from the ROI object.
binaryImage = hFH.createMask();
xy = hFH.getPosition;
% Now make it smaller so we can show more images.
subplot(2, 3, 1);
imshow(grayImage, []);
axis on;
drawnow;
title('Original Grayscale Image', 'FontSize', fontSize);
% Display the freehand mask.
subplot(2, 3, 2);
imshow(binaryImage);
axis on;
title('Binary mask of the region', 'FontSize', fontSize);
% Label the binary image and computer the centroid and center of mass.
labeledImage = bwlabel(binaryImage);
measurements = regionprops(binaryImage, grayImage, ...
    'area', 'Centroid', 'WeightedCentroid', 'Perimeter');
area = measurements.Area
centroid = measurements.Centroid
centerOfMass = measurements.WeightedCentroid
perimeter = measurements.Perimeter
% Calculate the area, in pixels, that they drew.
numberOfPixels1 = sum(binaryImage(:))
% Another way to calculate it that takes fractional pixels into account.
numberOfPixels2 = bwarea(binaryImage)
% Get coordinates of the boundary of the freehand drawn region.
structBoundaries = bwboundaries(binaryImage);
xy=structBoundaries{1}; % Get n by 2 array of x,y coordinates.
x = xy(:, 2); % Columns.
y = xy(:, 1); % Rows.
subplot(2, 3, 1); % Plot over original image.
hold on; % Don't blow away the image.
plot(x, y, 'LineWidth', 2);
drawnow; % Force it to draw immediately.
% Burn line into image by setting it to 255 wherever the mask is true.
burnedImage = grayImage;
burnedImage(binaryImage) = 255;
% Display the image with the mask "burned in."
subplot(2, 3, 3);
imshow(burnedImage);
axis on;
caption = sprintf('New image with\nmask burned into image');
title(caption, 'FontSize', fontSize);
% Mask the image and display it.
% Will keep only the part of the image that's inside the mask, zero outside mask.
blackMaskedImage = grayImage;
blackMaskedImage(~binaryImage) = 0;
subplot(2, 3, 4);
imshow(blackMaskedImage);
axis on;
title('Masked Outside Region', 'FontSize', fontSize);
% Calculate the mean
meanGL = mean(blackMaskedImage(binaryImage));
% Put up crosses at the centriod and center of mass
hold on;
plot(centroid(1), centroid(2), 'r+', 'MarkerSize', 30, 'LineWidth', 2);
plot(centerOfMass(1), centerOfMass(2), 'g+', 'MarkerSize', 20, 'LineWidth', 2);
% Now do the same but blacken inside the region.
insideMasked = grayImage;
insideMasked(binaryImage) = 0;
subplot(2, 3, 5);
imshow(insideMasked);
axis on;
title('Masked Inside Region', 'FontSize', fontSize);
% Now crop the image.
leftColumn = min(x);
rightColumn = max(x);
topLine = min(y);
bottomLine = max(y);
width = rightColumn - leftColumn + 1;
height = bottomLine - topLine + 1;
croppedImage = imcrop(blackMaskedImage, [leftColumn, topLine, width, height]);
% Display cropped image.
subplot(2, 3, 6);
imshow(croppedImage);
axis on;
title('Cropped Image', 'FontSize', fontSize);
% Put up crosses at the centriod and center of mass
hold on;
plot(centroid(1)-leftColumn, centroid(2)-topLine, 'r+', 'MarkerSize', 30, 'LineWidth', 2);
plot(centerOfMass(1)-leftColumn, centerOfMass(2)-topLine, 'g+', 'MarkerSize', 20, 'LineWidth', 2);
% Report results.
message = sprintf('Mean value within drawn area = %.3f\nNumber of pixels = %d\nArea in pixels = %.2f\nperimeter = %.2f\nCentroid at (x,y) = (%.1f, %.1f)\nCenter of Mass at (x,y) = (%.1f, %.1f)\nRed crosshairs at centroid.\nGreen crosshairs at center of mass.', ...
meanGL, numberOfPixels1, numberOfPixels2, perimeter, ...
centroid(1), centroid(2), centerOfMass(1), centerOfMass(2));
msgbox(message);

2 Comments

nadia naji on 10 Feb 2013

excuse me i cant understand some things i need to have one centroid for objects in image not structure of several centroid because i need to consider the movement of centroids in sequential frame? do you understand what i need? i need centroid of whole image please help me

Image Analyst on 10 Feb 2013

Nadia, if this is in a loop over frames, just extract the centroids (x_centroids and y_centroids) from the structure. Make x_centroids and y_centroids arrays that depend on the frame. So if you have 300 frames, x_centroids is an array of 300 x centroids. Then you can do mean_x_centroid = mean(x_centroids). It becomes more complicated if there are different numbers of blobs in each frame - then it becomes essentially a tracking problem, which is more complicated because you have to account for blobs coming into the field of view and blobs leaving the field of view.

Image Analyst

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