MATLAB Tutorial

Image Processing using MATLAB

Image processing is a crucial application of MATLAB, providing tools for manipulating, analyzing, and visualizing images. MATLAB’s Image Processing Toolbox offers a wide range of functions to work with images effectively. This section introduces key concepts, examples, and problems in image processing.

Reading, Writing and Displaying Images

You can read, display and write images using MATLAB commands like imread, imshow and imwrite.

There are three way you can upload the images in Matlab using “imread” function:

1. img = imread(‘myImage.png’); when image is located in the work directory.
2. img = imread(‘C:/path_to_image/myImage.jpg’); when image is located in different directory.
3. [filename, pathname] = uigetfile({‘*.jpg;*.png;*.bmp’, ‘Image Files’}); select any location

Example 1: Reading and Displaying Images in Matlab


% Read and display images from predefined paths 

img1 = imread('peppers.png'); 

img2 = imread('C:/Users/JohnWick/Pictures/myImage.jpg'); 


subplot(1, 2, 1); % Create a 1x2 grid, select the first section

imshow(img1);

title('Image 1');



subplot(1, 2, 2); % Select the second section

imshow(img2);

title('Image 2');

Output:

Both images will be displayed side by side in the figure window.

Example 2: Reading and Displaying Images in Matlab using uigetfile function


% Read and display images with uigetfile, works similar to Windows UI 

[filename, pathname] = uigetfile({'*.jpg;*.png;*.bmp', 'Image Files'});

if isequal(filename, 0)

    disp('No file selected');

else

    img = imread(fullfile(pathname, filename));

    imshow(img);

end

Example 3: Reading, writing and displaying Images in Matlab using imwrite function


% Read and display images with uigetfile, works similar to Windows UI 

img = imread('C:/Users/JohnWick/Pictures/continental_01.jpg'); % Read an image 

imwrite(img, 'C:/Users/JohnWick/Pictures/continental_01.png'); % Save the image in PNG format 

imshow(img);

Output:

continental_01.jpg will be saved as continental_01.png

Example 4: Converting Image to Grayscale, in Matlab


% Convert an RGB image to grayscale 

img = imread('peppers.png'); 

gray_img = rgb2gray(img); 

subplot(1, 2, 1); % Create a 1x2 grid, select the first section

imshow(img);

title('Color Image');



subplot(1, 2, 2); % Select the second section

imshow(gray_img);

title('Grayscale Image');

Example 5: Resizing Images in Matlab


% Resize an image 

img = imread('car.png'); 

resized_img = imresize(img, 0.5); % Resized to 50% 

imshow(resized_img);

imwrite(img, 'C:/Users/JohnWick/Pictures/car_01.png');

Image Filtering and Enhancement in Matlab

Matlab offers many functions for applying filters, and to enhance image features or suppress noise:

Example 6: Applying a Gaussian Filter on a image in Matlab


% Apply Gaussian filter 

img1 = imread('puppy.png'); 

gray_img = rgb2gray(img1); 

smoothed_img = imgaussfilt(gray_img, 2); % Standard deviation = 2 

imshow(smoothed_img);

Example 7: Edge Detection in Matlab


% Detect edges using Canny method 

edges = edge(gray_img, 'Canny'); 

imshow(edges);

Example 8: Image Geometric Transformations in Matlab

Perform transformations like rotation, translation, and scaling:


% Read the original image 

original_img = imread('C:/Users/JohnDoe/Pictures/sample_image.jpg'); 
 


% Perform transformations 

rotated_img = imrotate(original_img, 45); % Rotate by 45 degrees 

translated_img = imtranslate(original_img, [50, 30]); % Translate by [50 pixels right, 30 pixels down] 

scaled_img = imresize(original_img, 0.5); % Scale down by 50% 
 


% Display images in a 2x2 grid 

figure; 

subplot(2, 2, 1);  

imshow(original_img);  

title('Original Image'); 
 


subplot(2, 2, 2);  

imshow(rotated_img);  

title('Rotated Image'); 
 


subplot(2, 2, 3);  

imshow(translated_img);  

title('Translated Image'); 
 


subplot(2, 2, 4);  

imshow(scaled_img);  

title('Scaled Image');

Example 9: Simple Region of Interest (ROI) Image Processing using Matlab

Focus on specific areas of an image:


my_img = imread('C:/Users/JohnDoe/Pictures/sample_image.jpg'); 


% Extract a region of interest 

roi = my_img(50:200, 50:200, :); % Selects a 150 by 150px square sub-image 

imshow(roi);

Example 10: User Selected Region of Interest (ROI) Image using Matlab

User can use computer mouse to click and select specific areas ROI of an image:


        % Read the original image 

original_img = imread('C:/Users/JohnWick/Pictures/my_car_01.jpg'); 
 


% Display the image 

figure; 

imshow(original_img); 

title('Click to select points for ROI. Press Enter when done.'); 
 


% Initialize variables for storing points 

x = []; 

y = []; 
 


% Loop to capture clicks and display '+' after each click 

hold on; 

while true 

    % Get a point from the user 

    [xi, yi, button] = ginput(1); 
 

    
    % Break if the user presses Enter (button = empty) 

    if isempty(button) 

        break; 

    end 
 

    
    % Store the point 

    x = [x; xi]; 

    y = [y; yi]; 
 

    
    % Plot the '+' sign at the selected point 

    plot(xi, yi, 'r+', 'MarkerSize', 10, 'LineWidth', 2); 

end 

hold off; 
 


% Create a binary mask for the selected ROI 

roi_mask = poly2mask(x, y, size(original_img, 1), size(original_img, 2)); 
 


% Extract the ROI 

roi = bsxfun(@times, original_img, cast(roi_mask, 'like', original_img)); 
 


% Create an all-white image of the same size as the original image 

white_image = 255 * ones(size(original_img), 'like', original_img); 
 


% Overlay the ROI onto the white image 

output_image = bsxfun(@times, white_image, ~cast(roi_mask, 'like', original_img)) + roi; 
 


% Save the result 

imwrite(output_image, 'C:/Users/JohnDoe/Pictures/roi_output.jpg'); 
 


% Display the final ROI 

figure; 

imshow(output_image); 

title('Extracted Region of Interest on White Background');

Example 11: Image Histogram Equalization in Matlab

Enhance contrast in images using histogram equalization:


% Equalize the histogram of a grayscale image 
 

% Read the original image 

original_img = imread('C:/Users/JohnWick/Pictures/Helen_Wick_01.jpg'); 


eq_img = histeq(original_img); 

imshow(eq_img);

Example 12: Making Videos from Images in Matlab

Use selects multiple images, and then creates videos out of the selected images:


% Prompt the user to select multiple image files  

[fileNames, pathName] = uigetfile({'*.jpg;*.png;*.bmp', 'Image Files (*.jpg, *.png, *.bmp)'}, ...  

                                  'Select Images', 'MultiSelect', 'on');  
  


% Check if the user selected files  

if isequal(fileNames, 0)  

    disp('No files selected.');  

    return;  

end  
  


% If only one file is selected, make it a cell array for consistency  

if ischar(fileNames)  

    fileNames = {fileNames};  

end  
  


% Create a VideoWriter object for the output video  

outputVideo = VideoWriter('output_video.avi'); % Output video file  

outputVideo.FrameRate = 2; % Set frame rate (e.g., 2 frames per second)  

open(outputVideo);  
  


% Read each image and add it as a frame to the video  

for i = 1:length(fileNames)  

    % Read the image  

    img = imread(fullfile(pathName, fileNames{i}));  
  

    
    % Convert the image to match video format if necessary  

    if size(img, 3) ~= 3  

        img = repmat(img, [1, 1, 3]); % Convert grayscale to RGB  

    end  
  

    
    % Write the image to the video  

    writeVideo(outputVideo, img);  

end  
  


% Close the VideoWriter object  

close(outputVideo);  
  


disp('Video created successfully as output_video.avi');

Example 13: Extracting Image frames from Videos in Matlab

Use can extract image frames from the selected video using the following Matlab codes:


% Specify the video file 

videoFile = 'C:/Users/JohnWick/Videos/John_Helen.mp4'; 
 


% Create a VideoReader object 

videoObj = VideoReader(videoFile); 
 


% Create a folder to save the extracted frames 

outputFolder = 'C:/Users/JohnDoe/Videos/ExtractedFrames'; 

if ~exist(outputFolder, 'dir') 

    mkdir(outputFolder); 

end 
 


% Initialize frame counter 

frameCount = 0; 
 


% Loop through each frame in the video 

while hasFrame(videoObj) 

    % Read the next frame 

    frame = readFrame(videoObj); 
 

    
    % Increment frame counter 

    frameCount = frameCount + 1; 
 

    
    % Create a filename for the frame 

    frameFileName = fullfile(outputFolder, sprintf('frame_%04d.jpg', frameCount)); 
 

    
    % Save the frame as an image 

    imwrite(frame, frameFileName); 

end 
 


disp(['Frames extracted and saved to: ', outputFolder]);

Useful MATLAB Functions for Image Processing

Function

Explanation

imread

Reads an image from a file.

imshow

Displays an image in a figure window.

imwrite

Writes an image to a file.

rgb2gray

Converts an RGB image to grayscale.

imresize

Resizes an image to a specified size or scale.

imgaussfilt

Applies a Gaussian filter to an image.

edge

Detects edges in an image using specified methods like ‘Canny’ or ‘Sobel’.

imrotate

Rotates an image by a specified angle.

histeq

Enhances the contrast of a grayscale image.

Practice Questions

Test Yourself

1. Load an image, convert it to grayscale, and perform edge detection.

2. Rotate an image by 30 degrees and crop the rotated image.

3. Resize an image to half its original size and enhance its contrast.

4. Apply a Gaussian filter to an image and compare it with the original.