How can I calculated centroid contour distance in image at every 10 degree?

I I have done many experiments, but I have not been able to determine the angle in the image, I want to get the vertices only at every 10 degrees, but in my experiments, I get the vertices on each pixel contained in the image? please help me solve this problem :). Here is my code

clc;
close all;
clear all;
fontSize = 10;

image_folder = 'D:\Mangrove Classification\Data Training';
filenames = dir(fullfile(image_folder, '*.png'));
total_images = numel(filenames);
for n = 1:total_images
    full_name= fullfile(image_folder, filenames(n).name);
    I = imread(full_name);
    I = imresize(I,0.2);
    M = I(:,:,1) < 168;
    % Fill holes
    M = imfill(M, 'holes');
    % Take largest blob only.
    M = bwareafilt(M, 1);
    subplot (1,2,1);
    imshow(M);
    
    [labeledImage numberOfBlobs] = bwlabel(M, 8);
    blobMeasurements = regionprops(labeledImage, 'Centroid', 'Orientation');
    xCenter = blobMeasurements(1).Centroid(1);
    yCenter = blobMeasurements(1).Centroid(2);
    subplot(1,2,2);
    imshow(I);
    axis on;
    hold on;
    % Plot the centroid.
    plot(xCenter, yCenter, 'b+', 'MarkerSize', 10, 'LineWidth', 3);
    boundaries = bwboundaries(M);
    set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
    for k = 1 : length(boundaries)
      thisBoundary = boundaries{k};
      plot(thisBoundary(:,2), thisBoundary(:,1), 'b', 'LineWidth', 2);
      numberOfBoundaryPoints = length(thisBoundary);
      angle = 0: 10 : 360;
      for a = 1 : length(angle)
       xb = thisBoundary(a,2);
       yb = thisBoundary(a,1);
       angles(a) = atand((yb-yCenter) / (xb-xCenter));
       distances(a) = sqrt((xb-xCenter).^2+(yb-yCenter).^2);
      end
    end
    save('Latih.mat','angles','distances');
end

[darova]

The code doesn't work

[Muhammad Andi Yusran]

hello darova, yeah u right, the code get all of the boundary points in every pixels as i know (CMIIW), but in my case, i just want to declare the image as 360 degree and get the boundary point every 10 degree, please help me :(

[darova]

I mean we don't have your data to try your code. CAn your attach?

[Muhammad Andi Yusran]

oh sorry, i forget sir..

this is the image

tes.png

Answer 1

[Image Analyst]

No, that won't work (as you know). Try it this way, in my well-commented/explained example below:

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 = 20;

image_folder = pwd; %'D:\Mangrove Classification\Data Training';
filenames = dir(fullfile(image_folder, '*.jpg'));
totalNumberOfImages = numel(filenames);
% Define the angles where we want to get distances for.
desiredAngles = 0: 20 : 360;
% Define the output distance matrix.
allDistances = zeros(totalNumberOfImages, length(desiredAngles));
for k = 1:totalNumberOfImages
	fullImageFileName= fullfile(image_folder, filenames(k).name);
	grayImage = imread(fullImageFileName);
	subplot (2,2,1);
	imshow(grayImage);
	axis('on', 'image');
	caption = sprintf('Original image : "%s"', filenames(k).name);
	title(caption, 'FontSize', fontSize);
	if ndims(grayImage) == 3
		% It's not gray scale.  convert to gray scale.
		grayImage = rgb2gray(grayImage);
	end
	% Resize to one fifth the original size.
	grayImage = imresize(grayImage,0.2);
	
	% Get a binary image.
	% Threshold to get things darker than 168 gray levels.
	binaryImage = grayImage(:,:,1) < 168;
	% Fill holes
	binaryImage = imfill(binaryImage, 'holes');
	% Take largest blob only.
	binaryImage = bwareafilt(binaryImage, 1);
	subplot (2,2,2);
	imshow(binaryImage);
	axis('on', 'image');
	title('Binary Image', 'FontSize', fontSize);
	
	% Find the centroid.
	[labeledImage, numberOfBlobs] = bwlabel(binaryImage, 8);
	blobMeasurements = regionprops(labeledImage, 'Centroid');
	xCenter = blobMeasurements(1).Centroid(1);
	yCenter = blobMeasurements(1).Centroid(2);
	% Plot the centroid over the image
	subplot(2,2,3);
	cla reset;
	imshow(grayImage);
	title('Resized Gray Image with Boundaries Overlaid on It', 'FontSize', fontSize);
	axis('on', 'image');
	hold on;
	% Plot the centroid.
	plot(xCenter, yCenter, 'b+', 'MarkerSize', 10, 'LineWidth', 3);
	hold off;
	
	% Compute the boundary for this one binary blob.
	boundaries = bwboundaries(binaryImage);
	% Plot it over the resized gray scale image.
	set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
	% For this one largest blob in the image, get the distances at certain angles.
	thisBoundary = boundaries{1}; % Extract double matrix from cell.
	xb = thisBoundary(:,2);
	yb = thisBoundary(:,1);
	hold on;
	plot(xb, yb, '-', 'LineWidth', 2);
	grid on;
	
	% Get the distances from every boundary point to the blob centroid.
	distances = sqrt((xb-xCenter).^2+(yb-yCenter).^2);
	% Get the angles from every boundary point to the blob centroid.
	angles = atan2d((yb-yCenter), (xb-xCenter)) + 180;
	% depending on the shape, like if the curve bends around,
	% there may be more than 1 index with the same angle.
	% In that case, just take one of them
	% (not sure if it will be the closest or farthest distance though!)
	[uniqueAngles, ia, ic] = unique(angles);
	% Now get the distances for only the unique angles.
	uniqueDistances = distances(ia);
	% Now if the angles don't go the whole distance, (like in my image they go from 13.1 to 358.3)
	% then we don't know what it will be at 0 or 360 so we need to add on extra points on the ends
	uniqueAngles = [uniqueAngles(end)-360; uniqueAngles; uniqueAngles(1) + 360];
	uniqueDistances = [uniqueDistances(end); uniqueDistances; uniqueDistances(1)];
	% Plot the unique distances vs. angle.
	subplot(2, 2, 4);
	plot(uniqueAngles, uniqueDistances, 'b.-', 'MarkerSize', 20, 'LineWidth', 2);
	grid on;
	
	% Now use interp1() to interpolate the distances at the desired angles
	desiredDistances = interp1(uniqueAngles, uniqueDistances, desiredAngles);
	% Plot them with red circles.
	hold on
	plot(desiredAngles, desiredDistances, 'ro', 'LineWidth', 2);
	title('Centroid-to-Boundary Distance vs. Angle', 'FontSize', fontSize);
	xlabel('Angle [degrees]', 'FontSize', fontSize);
	ylabel('Distance [pixels]', 'FontSize', fontSize);
	hold off;
	drawnow;
	
	% Save these distances in our main output matrix
	allDistances(k, :) = desiredDistances;
	
	% See if user wants to quit.
	promptMessage = sprintf('Do you want to Continue processing,\nor Quit processing?');
	titleBarCaption = 'Continue?';
	buttonText = questdlg(promptMessage, titleBarCaption, 'Continue', 'Quit', 'Continue');
	if contains(buttonText, 'Quit')
		% Crop out only what we've computed so far, discarding the rest of the array which will be all zeros.
		allDistances = allDistances(1:k, :);
		break; % out of loop.
	end
end
save('Latih.mat', 'desiredAngles', 'allDistances');
% delete('Latih.mat');

[Muhammad Andi Yusran]

Ohh yess. Thats work! Thank you so much Mr. Image Analyst. I will try it in my case.