Your question is very unclear and ambiguous. Like, exactly what does "want to find distance of one thin line to thick line (top to bottom)" mean??? Where are thin lines and where are the thick lines in your image?
Here is another guess at what you might mean. I just find the topmost and bottommost white pixel in the image for each column, and compute the distance (height) between them:
% 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;
%--------------------------------------------------------------------------------------------------------
% READ IN IMAGE
folder = pwd;
baseFileName = 'image.jpeg';
% 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
subplot(2, 2, 1);
imshow(grayImage, []);
impixelinfo;
title('Original Gray Scale Image', 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
%--------------------------------------------------------------------------------------------------------
% SEGMENTATION OF IMAGE
% Get a binary image
binaryImage = imbinarize(grayImage);
% Get rid of big white frame around the border of the image.
binaryImage = imclearborder(binaryImage);
subplot(2, 2, 2);
imshow(binaryImage, []);
impixelinfo;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
hFig = gcf;
hFig.WindowState = 'maximized'; % May not work in earlier versions of MATLAB.
drawnow;
% Scan image finding the distance from topmost white pixel to bottommost.
topRows = nan(1, columns);
bottomRows = nan(1, columns);
for col = 1 : columns
thisColumn = binaryImage(:, col);
t = find(thisColumn, 1, 'first');
if ~isempty(t)
topRows(col) = t;
bottomRows(col) = find(thisColumn, 1, 'last');
end
end
% Plot top rows and bottom rows.
subplot(2, 2, 3);
x = 1 : columns;
plot(x, topRows, 'b-', 'LineWidth', 2);
grid on;
hold on;
plot(x, bottomRows, 'r-', 'LineWidth', 2);
title('Top and Bottom Rows', 'FontSize', fontSize);
xlabel('Column', 'FontSize', fontSize);
ylabel('Row', 'FontSize', fontSize);
legend('Top Rows', 'Bottom Rows');
% Plot heights.
heights = bottomRows - topRows;
subplot(2, 2, 4);
x = 1 : columns;
plot(x, heights, 'b-', 'LineWidth', 2);
grid on;
title('Heights', 'FontSize', fontSize);
xlabel('Column', 'FontSize', fontSize);
ylabel('Height in Rows', 'FontSize', fontSize);
