Open In App
Related Articles

Matlab | Dilation of an Image

Improve Article
Save Article
Like Article

Morphology is known as the broad set of image processing operations that process images based on shapes. It is also known as a tool used for extracting image components that are useful in the representation and description of region shape. 

The basic morphological operations are: 

  • Erosion 
  • Dilation


  • Dilation expands the image pixels i.e. it is used for expanding an element A by using structuring element B.
  • Dilation adds pixels to object boundaries.
  • The value of the output pixel is the maximum value of all the pixels in the neighborhood. A pixel is set to 1 if any of the neighboring pixels have the value 1.


  • Read the RGB image.
  • Using function im2bw(), convert the RGB image to a binary image.
  • Create a structuring element or you can use any predefined mask eg. special(‘sobel’).
  • Store the number of rows and columns in an array and loop through it.
  • Create a zero matrix of the size same as the size of our image.
  • Leaving the boundary pixels start moving the structuring element on the image and start comparing the pixel with the pixels present in the neighborhood.
  • If the value of the neighborhood pixel is 1, then change the value of that pixel to 1.



% MATLAB code for Dilation
% read image
% convert to binary
% create structuring element            
se=ones(5, 5);
% store number of rows in P and
% number of columns in Q.          
[P, Q]=size(se);
% create a zero matrix of size I.       
In=zeros(size(I, 1), size(I, 2));
for i=ceil(P/2):size(I, 1)-floor(P/2)
    for j=ceil(Q/2):size(I, 2)-floor(Q/2)
        % take all the neighbourhoods.
        on=I(i-floor(P/2):i+floor(P/2), j-floor(Q/2):j+floor(Q/2)); 
        % take logical se
        % compare and take minimum value of the neighbor
        % and set the pixel value to that minimum value.   
        In(i, j)=max(nh(:));     


Figure: Input image

Figure: Output image

Let’s take another example for dilation.


  • imread() function is used to read the image.
  • strel() function is used to define the structuring element. We have chosen a disk-shaped SE, of radius 5.
  • imdialate() function is used to perform the dilation operation.
  • imtool() function is used to display the image.



%  MATLAB code for Dilation
% read the image.
% define the structuring element.
% apply the dilation operation.
%display all the images.
%see the effective expansion
% in original image


Figure: Left: Original image, Right: Dilated image

Figure: Expansion in the original image

Code Explanation: 

  • k=imread(“dilation_exmp.png”); this line reads the image.
  • SE=strel(‘disk’,5); this line defines the structuring element.
  • d=imdilate(k,SE); this line applies the dilation operation.
  • imtool(k,[]); this line displays the original image.
  • imtool(e,[]); this line displays the  dilated image.
  • imtool(d-k,[]); this line shows the effective expansion in original image.

The last image shows the extent to which the original image got dilated. We have used the Structuring element of disk-shaped and the image we used is also circular in shape. This gives us the very desired output to understand erosion.

Whether you're preparing for your first job interview or aiming to upskill in this ever-evolving tech landscape, GeeksforGeeks Courses are your key to success. We provide top-quality content at affordable prices, all geared towards accelerating your growth in a time-bound manner. Join the millions we've already empowered, and we're here to do the same for you. Don't miss out - check it out now!

Last Updated : 23 Mar, 2022
Like Article
Save Article
Similar Reads