How to calculate the distance between two black point?

I have two black points. I need to measure maximum distance between these two points in every pics. I think the edge of upper and lower of black points would help us.But I can not find out how to explain these method in Matlab.I should have to find these distance for 1200 pics.Please help me.

[Cedric]

How do you define this "maximum distance"?

Answer 1

[Akira Agata]

How about the following script??

% Read the image and binarize
I = imread('DCB57 0346.jpg');
BW = imbinarize(rgb2gray(I));

% Remove noise
se = strel('disk',3);
BW = imclose(BW, se);

% Detect edge pixels for each area
BW2 = bwperim(~BW);
stats = regionprops(BW2,'PixelList');

% Measure distance and extract maximum
d = pdist2(stats(1).PixelList, stats(2).PixelList);
[maxDist,idx] = max(d(:));
[r,c] = ind2sub(size(d), idx);

% Show result
imshow(I)
hold on
plot(stats(1).PixelList(r,1), stats(1).PixelList(r,2), 'ro')
plot(stats(2).PixelList(c,1), stats(2).PixelList(c,2), 'ro')

The result is as follows.

>> maxDist
maxDist =
203.3839

Answer 2

[Image Analyst]

What I would do is

1. Binarize and extract the two largest blobs
2. Scan across columns getting the top edge of the top blob and bottom edge of the bottom blob
3. Scan across columns getting the min distance from the top edge pixel to the bottom edge pixel
4. Average those minimum distances

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 short g;
format compact;
fontSize = 25;

%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'DCB57 0346.jpg';
% Get the full filename, with path prepended.
folder = pwd
fullFileName = fullfile(folder, baseFileName);

if ~exist(fullFileName, 'file')
  errorMessage = sprintf('This image does not exist:\n%s', fullFileName);
  errordlg(errorMessage);
  return;
end

%===============================================================================
% Read in a first image.
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;
axis image;
caption = sprintf('Original Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();

% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, .96]);
% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')
drawnow;

% Binarize the image.
threshold = 128;
binaryImage = grayImage < threshold;  % Determine number from histogram.
% binaryImage = imbinarize(grayImage);
% Take only the largest 2 blobs
binaryImage = bwareafilt(binaryImage, 2);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
caption = sprintf('Binary Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();

% Scan the top and bottom edge
topEdge = zeros(1, columns); % Initialize
bottomEdge = rows * ones(1, columns); % Initialize
for col = 1 : columns
  thisColumn = binaryImage(:, col);
  % Find top edge
  edgeLocation = find(thisColumn, 1, 'first');
  if isempty(edgeLocation)
    % No edge found.
    continue; % Skip to next columns
  end
  if edgeLocation < rows/2
    % It's in the top half, so log it.
    topEdge(col) = edgeLocation;
  end
  
  % Find bottom edge
  edgeLocation = find(thisColumn, 1, 'last');
  if edgeLocation > rows/2
    % It's in the top half, so log it.
    bottomEdge(col) = edgeLocation;
  end
end
% Show the edges in red
% Display the image.
subplot(2, 2, 3);
imshow(binaryImage, []);
axis on;
axis image;
caption = sprintf('Binary Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hold on;
plot(topEdge, 'r.-', 'MarkerSize', 20);
plot(bottomEdge, 'r.-', 'MarkerSize', 20);

% Find the distance from each top pixel to the closest bottom pixel
x2 = 1:columns;
minDistances = zeros(1, columns);
for col = 1 : columns
  x1 = col;
  y1 = topEdge(col);
  if y1 == 0
    % Skip those columns not touching a blob.
    continue;
  end
  distances = sqrt((x1 - x2) .^ 2 + (y1 - bottomEdge) .^ 2);
  minDistances(col) = min(distances);
end
subplot(2, 2, 4);
area(minDistances);
grid on;
% Find the average min distance.
averageMinDistance = mean(minDistances(minDistances> 0))
xlabel('Column', 'FontSize', fontSize);
ylabel('Distance', 'FontSize', fontSize);
message = sprintf('Average Min Distance from top of top blob\nto bottom of bottom blob = %.2f', averageMinDistance);
title(message, 'FontSize', fontSize);