MATLAB: How to read every next img in a file, then invert it, and save it

imageindexinvert

So I need to invert/complement (change all the white to black and black to white) a bunch of images in a file. All of these images are named image10.jpg, image20.jpg, image30.jpg, etc. There could be up to a thousand of these images. I need to invert the colors of all these images and then re-save them. I would prefer to re-save them over their non-inverted image too. I know the command img1=~img1 inverts the image but I am just not quite sure how to do the rest.

Thanks in advance for any help.

Best Answer

Are the images color, grayscale, or binary? Sometimes you'd say theImage = 255 - theImage. I don't know the format of this massive file that contains all your images. Is it a multi-page TIFF image? Or a dicom file? Saving your new image over your original images is a dangerous and risky thing to do unless you have a back up of them somewhere.

Related Solutions

MATLAB: How to get those object and turn background color into white of the binary image

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 = 20;
% Check that user has the Image Processing Toolbox installed.
hasIPT = license('test', 'image_toolbox');
if ~hasIPT
  % User does not have the toolbox installed.
  message = sprintf('Sorry, but you do not seem to have the Image Processing Toolbox.\nDo you want to try to continue anyway?');
  reply = questdlg(message, 'Toolbox missing', 'Yes', 'No', 'Yes');
  if strcmpi(reply, 'No')
    % User said No, so exit.
    return;
  end
end
% Read in a demo image.
folder = pwd % or wherever the image lives
baseFileName = 'batik22.PNG';
%===============================================================================
% Read in a color reference image.
% 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 = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 2, 1);
imshow(rgbImage);
title('Original Color Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0, 1, 1]);
% Take the red channel
grayImage = rgbImage(:,:, 1);
subplot(2, 2, 2);
imshow(grayImage);
axis on;
title('Red Channel Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Threshold the image
binaryImage = grayImage < 127;
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Take the 8 largest blobs, then invert the image
binaryImage = ~bwareafilt(binaryImage, 8);
subplot(2, 2, 4);
imshow(binaryImage, []);
caption = sprintf('Final Binary Image with 8 largest blobs');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');

MATLAB: Plotting RGB Histograms of Colored Images

Guan Zhao, see my demo:

%----------------------------------------------------------


% Program to read in all the RGB color images in a folder and 
% display the histograms of each color channel.
%, Feb. 2011
%----------------------------------------------------------
function RGB_Histogram_Demo()
% Change the current folder to the folder of this m-file.
if(~isdeployed)
  cd(fileparts(which(mfilename)));
end
clc;  % Clear command window.
close all;  % Close all figure windows except those created by imtool.
imtool close all;  % Close all figure windows created by imtool.
workspace;  % Make sure the workspace panel is showing.
fontSize = 16;
try
% Read in standard MATLAB color demo images.
% Construct the folder name where the demo images live.
imagesFolder = fullfile(matlabroot, '\toolbox\images\imdemos');
if ~exist(imagesFolder, 'dir')
  % That folder didn't exist.  Ask user to specify folder.
   message = sprintf('Please browse to your image folder');
  button = questdlg(message, 'Specify Folder', 'OK', 'Cancel', 'OK');
  drawnow;  % Refresh screen to get rid of dialog box remnants.
  if strcmpi(button, 'Cancel')
     return;
  else
    imagesFolder = uigetdir();
    if imagesFolder == 0
      % Exit if uer clicked Cancel.
      return;
    end
  end
end
% Read the directory to get a list of images.
filePattern = [imagesFolder, '\*.jpg'];
jpegFiles = dir(filePattern);
filePattern = [imagesFolder, '\*.tif'];
tifFiles = dir(filePattern);
filePattern = [imagesFolder, '\*.png'];
pngFiles = dir(filePattern);
filePattern = [imagesFolder, '\*.bmp'];
bmpFiles = dir(filePattern);
% Add more extensions if you need to.
imageFiles = [jpegFiles; tifFiles; pngFiles; bmpFiles];
% Bail out if there aren't any images in that folder.
numberOfImagesProcessed = 0;
numberOfImagesToProcess = length(imageFiles);
if numberOfImagesToProcess <= 0
   message = sprintf('I did not find any JPG, TIF, PNG, or BMP images in the folder\n%s\nClick OK to Exit.', imagesFolder);
  uiwait(msgbox(message));
  return;
end
% Create a figure for our images.
figure;
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
set(gcf,'name','Image Analysis Demo','numbertitle','off') 
% Preallocate arrays to hold the mean intensity values of all the images.
redChannel_Mean = zeros(numberOfImagesToProcess, 1);
greenChannel_Mean = zeros(numberOfImagesToProcess, 1);
blueChannel_Mean = zeros(numberOfImagesToProcess, 1);
% We'll be skipping monochrome and indexed images
% and just looking at true color images.
% Keep track of how many we actually look at.
numberOfImagesToProcess2 = numberOfImagesToProcess;
% Loop though all images, calculating and displaying the histograms.
% and then getting the means of the Red, green, and blue channels.
for k = 1 : numberOfImagesToProcess
  % Read in this one file.
  baseFileName = imageFiles(k).name;
  fullFileName = fullfile(imagesFolder, baseFileName);
  rgbImage = imread(fullFileName);
  % Check to see that it is a color image (3 dimensions).
  % Skip it if it is not true RGB color.
  if ndims(rgbImage) < 3
    % Skip monochrome or indexed images.
    fprintf('Skipped %s.  It is a grayscale or indexed image.\n', baseFileName);
    % Decrement the number of images that we'll report that we need to look at.
    numberOfImagesToProcess2 = numberOfImagesToProcess2 - 1;  
    continue;
  end
  
  % If we get to here, it's a true color image.
  subplot(3, 3, 1);
  imshow(rgbImage, []);
  [rows columns numberOfColorBands] = size(rgbImage);
  
  % Create a title for the image.
  caption = sprintf('Original Color Image\n%s\n%d rows by %d columns by %d color channels', ...
    baseFileName, rows, columns, numberOfColorBands);
  % If there are underlines in the name, title() converts the next character to a subscript.
  % To avoid this, replace underlines by spaces.
  caption = strrep(caption, '_', ' ');
  title(caption, 'FontSize', fontSize);
  drawnow;  % Force it to update, otherwise it waits until after the conversion to double.
  
  % Extract the individual red, green, and blue color channels.
  redChannel = rgbImage(:, :, 1);
  greenChannel = rgbImage(:, :, 2);
  blueChannel = rgbImage(:, :, 3);
  
  % Red image:
  subplot(3, 3, 4);
  imshow(redChannel, []); % Display the image.


  % Compute mean


  redChannel_Mean(k) = mean(redChannel(:));
  caption = sprintf('Red Image.  Mean = %6.2f', redChannel_Mean(k));
  title(caption, 'FontSize', fontSize);
  % Compute and display the histogram for the Red image.
  pixelCountRed = PlotHistogramOfOneColorChannel(redChannel, 7, 'Histogram of Red Image', 'r');
  % Green image:
  subplot(3, 3, 5);
  imshow(greenChannel, []); % Display the image.
  % Compute mean
  greenChannel_Mean(k) = mean(greenChannel(:));
  caption = sprintf('Green Image.  Mean = %6.2f', greenChannel_Mean(k));
  title(caption, 'FontSize', fontSize);
  % Compute and display the histogram for the Green image.
  pixelCountGreen = PlotHistogramOfOneColorChannel(greenChannel, 8, 'Histogram of Green Image', 'g');
  % Blue image:
  subplot(3, 3, 6);
  imshow(blueChannel, []); % Display the image.
  numberOfImagesProcessed = numberOfImagesProcessed + 1;
  % Compute mean
  blueChannel_Mean(k) = mean(blueChannel(:));
  caption = sprintf('Blue Image.  Mean = %6.2f', blueChannel_Mean(k));
  title(caption, 'FontSize', fontSize);
  % Compute and display the histogram for the Blue image.
  pixelCountBlue = PlotHistogramOfOneColorChannel(blueChannel, 9, 'Histogram of Blue Image', 'b');
  
  % Plot all three histograms on the same plot.
  subplot(3, 3, 2:3);
  lineWidth = 2;
  hold off;
  plot(pixelCountRed, 'r', 'LineWidth', lineWidth);
  hold on;
  grid on;
  plot(pixelCountGreen, 'g', 'LineWidth', lineWidth);
  plot(pixelCountBlue, 'b', 'LineWidth', lineWidth);
  title('All the Color Histograms (Superimposed)', 'FontSize', fontSize);
  % Set the x axis range manually to be 0-255.

  xlim([0 255]); 
  
  % Prompt user to continue, unless they're at the last image.
  if k < numberOfImagesToProcess
    promptMessage = sprintf('Currently displaying image #%d of a possible %d:\n%s\n\nDo you want to\nContinue processing, or\nCancel processing?',...
      numberOfImagesProcessed, numberOfImagesToProcess2, baseFileName);
    button = questdlg(promptMessage, 'Continue?', 'Continue', 'Cancel', 'Continue');
    if strcmp(button, 'Cancel')
      break;
    end
  end
end
% Crop off any unassigned values:
redChannel_Mean = redChannel_Mean(1:numberOfImagesProcessed);
greenChannel_Mean = greenChannel_Mean(1:numberOfImagesProcessed);
blueChannel_Mean = blueChannel_Mean(1:numberOfImagesProcessed);
% Print to command window
fprintf(1, '                Filename,   Red Mean, Green Mean, Blue Mean\n');
for k = 1 : length(redChannel_Mean)
  baseFileName = imageFiles(k).name;
  fprintf(1, '%24s    %6.2f,   %6.2f,     %6.2f\n', ...
    baseFileName, redChannel_Mean(k), greenChannel_Mean(k), blueChannel_Mean(k));
end
if numberOfImagesProcessed == 1
  caption = sprintf('Done with demo!\n\nProcessed 1 image.\nCheck out the command window for the results');
else
  caption = sprintf('Done with demo!\n\nProcessed %d images.\nCheck out the command window for the results', numberOfImagesProcessed);
end
msgbox(caption);
catch ME
  errorMessage = sprintf('Error in function RGB_Hist_Demo.\n.\n\nError Message:\n%s', ME.message);
  uiwait(warndlg(errorMessage));
end
%----------------------------------------------------------
% Plots a bar chart of the histogram of the color channel.
function pixelCount = PlotHistogramOfOneColorChannel(oneColorChannel, subplotNumber, caption, color)
  try
    % Let's get its histogram into 256 bins.
    [pixelCount grayLevels] = imhist(oneColorChannel, 256);
    subplot(3, 3, subplotNumber);
    bar(grayLevels, pixelCount, 'FaceColor', color); 
    title(caption, 'FontSize', 16);
    grid on;
    % Set the x axis range manually to be 0-255.
    xlim([0 255]); 
  catch ME
    errorMessage = sprintf('Error in function PlotHistogramOfOneColorChannel.\n.\n\nError Message:\n%s', ME.message);
    uiwait(warndlg(errorMessage));
  end
  return;

Best Answer

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MATLAB: How to get those object and turn background color into white of the binary image

MATLAB: Plotting RGB Histograms of Colored Images

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