Matlab | Erosion of an Image
Last Updated :
30 Nov, 2021
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:
In this article, we will be discussing Erosion.
Erosion:
- Erosion shrink-ens the image pixels i.e. it is used for shrinking of element A by using element B.
- Erosion removes pixels on object boundaries.:
- The value of the output pixel is the minimum value of all the pixels in the neighborhood. A pixel is set to 0 if any of the neighboring pixels have the value 0.
Approach:
- 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 0, then change the value of that pixel to 0.
Example:
MATLAB
I=imread( 'lenna.png' );
I=im2bw(I);
se=ones(5, 5);
[P, Q]=size(se);
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)
on=I(i-floor(P/2):i+floor(P/2), j-floor(Q/2):j+floor(Q/2));
nh=on(logical(se));
In(i, j)=min(nh(:));
end
end
imshow(In);
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Output:
figure: Input image
figure: Output Image
Let’s take another image to perform Erosion and here we use different MATLAB functions.
Syntax:
- imread() function is used to read the image.
- strel() function is used to define the structuring element. We have chosen disk-shaped SE, of radius 5.
- imerode() function is used to perform the erosion operation.
- imtool() function is used to display the image.
Example:
Matlab
k=imread( "erosion.png" );
SE=strel( 'disk' ,5);
e=imerode(k,SE);
imtool(k,[]);
imtool(e,[]);
imtool(k-e,[]);
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Output:
Figure: Left: Original image, Right: Eroded image
Figure: Output image
Code explanation:
- k=imread(“erosion_exmp.png”); this line reads the image.
- SE=strel(‘disk’,5); this line defines the structuring element.
- e=imerode(k,SE); this line applies the erosion operation.
- imtool(k,[]); this line displays the original image.
- imtool(e,[]); this line displays the eroded image.
- imtool(k-e,[]); this line shows the effective reduction in original image.
The last image shows the extent to which the original image got eroded. 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.
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