Here is what I have so far:
% Demo by Image Analyst
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
imtool close all; % Close all imtool figures if you have the Image Processing Toolbox.
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 16;
%===============================================================================
% Read in gray scale image.
folder = pwd;
baseFileName = '4.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
% Didn't find it there. Check the search path for it.
fullFileName = baseFileName; % No path this time.
if ~exist(fullFileName, 'file')
% Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist.', fullFileName);
uiwait(warndlg(errorMessage));
return;
end
end
[rgbImage, map] = imread(fullFileName);
% Get the dimensions of the image. numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(rgbImage);
% If it's RGB instead of grayscale, convert it to gray scale.
if numberOfColorBands > 1
grayImage = rgbImage(:, :, 1); % Take red channel.
else
grayImage = rgbImage;
end
% Display the original image.
subplot(2, 3, 1);
imshow(grayImage, []);
axis on;
impixelinfo; % Let user mouse around and see gray level.
caption = sprintf('Original Gray Scale Image : %s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'none');
impixelinfo;
% Enlarge figure to full screen.
g = gcf;
g.WindowState = 'maximized';
g.NumberTitle = 'off';
g.Name = 'Histogram Analysis';
drawnow;
mkdir('results');
startingImage = grayImage;
kx = 4;
ky = 24;
% for kx = 2 : 2 : 24
% for ky = 2 : 2 : 24
grayImage = adapthisteq(startingImage, 'numTiles', [kx, ky]);
% Display the image.
subplot(2, 3, 2);
imshow(grayImage, []);
axis on;
impixelinfo; % Let user mouse around and see gray level.
caption = sprintf('/results/%d %d.png', kx, ky);
fn = fullfile(pwd, caption);
title(caption, 'FontSize', fontSize, 'Interpreter', 'none');
impixelinfo;
drawnow;
% imwrite(grayImage, fn);
% end
% end
%===============================================================================
% Display the histogram
subplot(2, 3, 3);
[pixelCounts, grayLevels] = imhist(grayImage);
bar(grayLevels, pixelCounts);
grid on;
title('Image Histogram', 'FontSize', fontSize);
xlabel('Gray Level', 'FontSize', fontSize);
ylabel('Pixel Count', 'FontSize', fontSize);
% verticalSDProfile = std(double(grayImage), [], 2);
% verticalSDProfile = sgolayfilt(verticalSDProfile, 2, 31);
verticalProfile = mean(double(grayImage), 2);
verticalProfile = sgolayfilt(verticalProfile, 3, 29);
% Display the vertical profile.
subplot(2, 3, 4);
plot(verticalProfile, '-', 'Linewidth', 2);
grid on;
impixelinfo; % Let user mouse around and see gray level.
title('Mean Profile', 'FontSize', fontSize, 'Interpreter', 'none');
impixelinfo;
% Display the vertical profile.
% subplot(2, 3, 6);
% plot(verticalSDProfile, '-', 'Linewidth', 2);
% grid on;
% impixelinfo; % Let user mouse around and see gray level.
% title('SD Profile', 'FontSize', fontSize, 'Interpreter', 'none');
% impixelinfo;
As you can see the bands are quite well found from the vertical profile. So what you need to do is to take my attached radon transform demo and rotate your images so that the bands are perfectly horizontal. Then use the code above to find the starting and stopping lines for each band.
