distance between two centroids of objects in an image using image processing toolbox in matlab

From the image given I would like to find the distance of green dotted line.Where the direction line is to define path of objects which are placed on either side I would like to find centroids, from that would like to extract lengths of both blue and green dotted lines

[DGM]

Are you saying that you want to find the distance components relative to some arbitrary path? If so, how is the path defined? Is it known beforehand? Is it an object itself in the image, or does it have to be derived from the positions of the other objects?

[Jonas]

i guess he wants the City block distance

call regionprops and loc for delta x and y oft centroid coordinates

[DGM]

I suppose you have a point. If it's the simple sum of the component magnitudes, then the orientation of the path vector doesn't change the result. Either way, that's up to OP to clarify.

FWIW, pdist()/pdist2() support multiple distance metrics, though for single pair points, I don't know that it's justified.

[lahari K]

sir,suppose a person is walking in stride path so to find gait pattern value we need some parametres like step length,step width . How to find those values from an image in which footprints are placed with respect to direction line?

[DGM]

So the components are important independently. Can you provide an example image?

Answer 1

[Image Analyst]

Here is one way. I ignored the drawn centerline and I fit the blob centroids to a line, though there are other ways you could possibly define the centerline.

% Demo by Image Analyst
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;
markerSize = 40;
%--------------------------------------------------------------------------------------------------------
%    READ IN IMAGE
folder = [];
baseFileName = 'gait.png';
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.
    fprintf('It is not really gray scale like we expected - it is color\n');
    % Extract the blue channel.
    grayImage = rgb2gray(grayImage);
end
%--------------------------------------------------------------------------------------------------------
% Display the image.
subplot(2, 2, 1);
imshow(grayImage);
impixelinfo;
axis('on', 'image');
title('Original Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Update 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)
% Maximize window.
g = gcf;
g.WindowState = 'maximized';
drawnow;
%--------------------------------------------------------------------------------------------------------
% Show the histogram
subplot(2, 2, 2);
imhist(grayImage);
title('Histogram of Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
grid on;
%--------------------------------------------------------------------------------------------------------
% Interactively and visually set a threshold on a gray scale image.
% https://www.mathworks.com/matlabcentral/fileexchange/29372-thresholding-an-image?s_tid=srchtitle
lowThreshold = 0;
highThreshold = 200;
% [lowThreshold, highThreshold] = threshold(lowThreshold, highThreshold, grayImage)
%--------------------------------------------------------------------------------------------------------
% Create a mask
mask = grayImage >= lowThreshold & grayImage <= highThreshold;
% Fill blobs
mask = imfill(mask,"holes");
% Determine areas
% props = regionprops(mask, 'Area');
% allAreas = sort([props.Area])
% Take largest blobs only.
mask = bwareafilt(mask, [10000, inf]);
% Get rid of the vertical black line.
% Determine aspect ratios.  Vertical line will have a high aspect ratio.
props = regionprops(mask, 'Area', 'BoundingBox');
allAreas = sort([props.Area])
bb = vertcat(props.BoundingBox);
aspectRatios = [bb(:, 4) ./ bb(:, 3)]
lineIndex = find(aspectRatios > 20)
labeledImage = bwlabel(mask);
labeledImage(labeledImage == lineIndex) = 0;
mask = logical(labeledImage);
% Display the final mask.
subplot(2, 2, 3);
imshow(mask, []);
impixelinfo;
axis('on', 'image');
title('Mask', 'FontSize', fontSize, 'Interpreter', 'None');
% Determine Centroids
props = regionprops(mask, 'Centroid');
xyCentroids = vertcat(props.Centroid)
xCentroids = xyCentroids(:, 1);
yCentroids = xyCentroids(:, 2);
% Sort centroids from top to bottom (increasing y).
[yCentroids, sortOrder] = sort(yCentroids, 'ascend')
xCentroids = xCentroids(sortOrder)
hold on
plot(xCentroids, yCentroids, 'r+', 'MarkerSize', 25, 'Linewidth', 2)
% Fit the x,y to a line to get the centerline.
coefficients = polyfit(yCentroids, xCentroids, 1);
xFit = 1:rows;
centerLineColumns = polyval(coefficients, xFit);
plot(centerLineColumns, xFit, 'r-', 'Linewidth', 2);
centerlineX = polyval(coefficients, yCentroids)
deltax = centerlineX - xCentroids
% Get the delta x from the centroid to the centerline column.
for k = 1 : length(xCentroids)
    thisX = xCentroids(k)
    centerlineX(k)
    % Draw a green line from centroid to centerline
    line([thisX, centerlineX(k)], [yCentroids(k), yCentroids(k)], 'LineWidth', 3, 'Color', 'g')
end
% Plot the deltas
subplot(2, 2, 4);
bar(deltax);
grid on;
xlabel('Step Number', 'FontSize', fontSize)
ylabel('Delta X from Centerline', 'FontSize', fontSize)
title('Delta X from Centerline', 'FontSize', fontSize)