Removing "straight" lines from image

Hi all! I'm a material scientist by trade and I would appreciate some help with some image processing. The images are like the one below and contain (a) some fairly "straight" lines, which correspond to the rectangular-shaped microstructure and (b) some more "twisted"/"random" lines, which correspond to defects in this material. I would like to process the images to remove all (or most) of the fairly straight lines, but still keep the others. I searched for previous similar questions but most dealt with perfectly straight lines, whereas here this is not exactly the case. I would be very grateful for some suggestions. Many thanks in advance!

Answer 1

[Image Analyst]

Well I worked on it for about 20 minutes and this is what I got. Not bad but you could probably improve it with some tweaking of parameters.

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;

%===============================================================================
% Read in gray scale demo image.
folder = pwd; % Determine where demo folder is (works with all versions).
baseFileName = 'test.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
rgbImage = 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(rgbImage)
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(rgbImage);
  % 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 = rgbImage(:, :, 1); % Take red channel.
else
  grayImage = rgbImage; % It's already gray scale.
end
% Now it's gray scale with range of 0 to 255.

% Display the image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();

%------------------------------------------------------------------------------
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);
% 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
binaryImage = grayImage < 128;

% Display the binary image.
subplot(2, 2, 2);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
drawnow;

% Find branchpoints
bpImage = bwmorph(binaryImage, 'branchpoints');
% Enlarge the branchpoints to really separate the lines.
bpImage2 = imdilate(bpImage, ones(3));

% Erase the branchpoints from the original binary image to leave 
% just the single, unbranched stick-like lines.
linesImage = binaryImage & ~bpImage2;
% Now throw out blobs less than 15 pixels.
linesImage = bwareaopen(linesImage, 15);
% Colorize them.
% Label each blob with 8-connectivity, so we can make measurements of it
[labeledImage, numberOfBlobs] = bwlabel(linesImage, 8);
% Apply a variety of pseudo-colors to the regions.
coloredLabelsImage = label2rgb (labeledImage, 'hsv', 'k', 'shuffle');

% Display the pseudo-colored image.
subplot(2, 2, 3);
imshow(coloredLabelsImage);
title('Lines Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
drawnow;

% Now we need to find the pixels in each line and fit it to a line
% and determine if the line is straight or not.
% If the line is not straight, we keep it.  
% If it's straight, it's boundary "grid" line and we'll want to fill those in.
props = regionprops(linesImage, 'PixelList', 'Solidity');
allSolidities = [props.Solidity]
subplot(2, 2, 4);
histogram(allSolidities);
grid on;

figure;
linesImage = bwpropfilt(linesImage, 'Solidity', [0.35, inf]);
% Put the branchpoints back in.
linesImage = linesImage | bpImage;
% If the branchpoints touched a line that is no longer there, remove them.
linesImage = bwareaopen(linesImage, 15);
% Display the image.
imshow(linesImage);
title('Lines Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
drawnow;

% Use this image to fill in the original binary image
binaryImage2 =~ binaryImage; % Initialize.
binaryImage2(linesImage) = true;
% Display the image.
figure;
imshow(binaryImage2);
title('Final Image', 'FontSize', fontSize, 'Interpreter', 'None');
axis('on', 'image');
hp = impixelinfo();
drawnow;

[Sabin]

Wow, this is great! I will have a go and try changing some parameters to see what happens.

Answer 2

[Sabin]

I have one more quick question about this. The original images are in .tif format rather than .png, I just changed it so I could upload it here. I noticed that the proposed code doesn't work with .tif Would you recommend changing all images to .png or making some changes to the code and running it on the .tif images?