MATLAB: Finding the distance between points of boundaries

Question

Hi all,

I need help to find the distance between boundaries . I have attached my original microscopy image and the code I wrote to get the more clear boudaries of desired regions of that image . After that my problem is to find the distance between right most points of innner(green) and outer(Red) boundaries . Actually, I have to find the the distance between A and B points indicated in the resulting png.

It would be great if you share some ideas about writing codes for this measurement.

Thank you

Answer 1

Babu, to process many images, see the code samples in the FAQ:

https://matlab.fandom.com/wiki/FAQ#How_can_I_process_a_sequence_of_files.3F

To find the distance on the right between the two circles, 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 = 'originalimage.png';
% 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, []);
title('Original Grayscale Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
% Display histogram
subplot(2, 2, 2);
imhist(grayImage);
grid on;
title('Histogram of gray image', 'FontSize', fontSize);
%--------------------------------------------------------------------------------------------------------
%    SEGMENTATION OF IMAGE
% Get a binary image
brightMask = imbinarize(grayImage);
% Take the 2 biggest blobs
brightMask = bwareafilt(brightMask, 1, 4);
% Get rid of the small dots in the star by doing a hole fill.
% binaryImage = imfill(binaryImage, 'holes');
subplot(2, 2, 3);
imshow(brightMask, []);
impixelinfo;
title('Initial Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Need to get rid of little black specks in blob.
props = regionprops(brightMask, 'Area');
brightArea = props.Area
minAllowableArea = brightArea * 0.9
brightMask = ~bwareafilt(~brightMask, 2);
% Blur it a bit to smooth it out.
windowSize = 17;
kernel = ones(windowSize, windowSize) / windowSize ^ 2;
brightMask = imfilter(brightMask, kernel) > 0.5;
subplot(2, 2, 4);
imshow(brightMask, []);
impixelinfo;
title('Final Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
impixelinfo;
% Get boundaries and plot them, just for fun.
boundaries = bwboundaries(brightMask);
subplot(2, 2, 1);
hold on;
for k = 1 : length(boundaries)
	thisBoundary = boundaries{k};
	x = thisBoundary(:, 2);
	y = thisBoundary(:, 1);
	plot(x, y, 'r-', 'LineWidth', 2);
end
%--------------------------------------------------------------------------------------------------------
%    FIND DISTANCE BETWEEN CIRCLES ON THE RIGHT HAND SIDE.
% Find the right-most point.
[r, c] = find(brightMask);
[lastColumn, outerIndex] = max(c)
xRight = c(outerIndex)
yRight = r(outerIndex)
innerBoundary = boundaries{2};
x = innerBoundary(:, 2);
y = innerBoundary(:, 1);
% Find the closest point on the inner boundary to that point.
distances = sqrt((x - xRight).^2 + (y - yRight).^2);
[minDistance, innerIndex] = min(distances)
xInner = innerBoundary(innerIndex, 2);
yInner = innerBoundary(innerIndex, 1);
% Draw a line between them
line([xInner, xRight], [yInner, yRight], 'Color', 'r', 'LineWidth', 2);
subplot(2, 2, 4);
line([xInner, xRight], [yInner, yRight], 'Color', 'r', 'LineWidth', 2);
caption = sprintf('Final Mask.  Distance = %.1f', minDistance);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');