MATLAB: How to classified according to height

Image Processing Toolboximage segmentationlabeled image

I have an image like shown, I want to differentiate all the markers according to their height from upper limit an want a program that clearly show me that which one is smaller in height an so on… I want a asending or desending order and then numbering it for further use .

Best Answer

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.jpg';
% 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.
subplot(2, 2, 1);
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;
%--------------------------------------------------------------------------------------------------------
% Binarize the image.
binaryImage = imbinarize(grayImage);
% Remove huge white frame surrounding the image.
binaryImage = imclearborder(binaryImage);
subplot(2, 2, 2);
imshow(binaryImage, []);
axis('on', 'image');
title('Mask Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
drawnow;
% Find blobs
[labeledImage, numRegions] = bwlabel(binaryImage);
props = regionprops(binaryImage, 'Centroid');
xy = vertcat(props.Centroid)
y = xy(:, 2)
[sortedy, sortOrder] = sort(y, 'ascend')
xy = xy(sortOrder, :)
xy =
867.917808219178 67.1095890410959
791.06862745098 243.107843137255
818.159482758621 438.556034482759
797.25652173913 453.526086956522
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