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Mahotas – Element Structure for Dilating Image

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  • Last Updated : 29 Jul, 2021

In this article we will see how we can set the element structure of the dilate of image in mahotas. Dilation adds pixels to the boundaries of objects in an image, while erosion removes pixels on object boundaries. The number of pixels added or removed from the objects in an image depends on the size and shape of the structuring element used to process the image. In order to dilate the image we use mahotas.morph.dilate method.By setting element structure we can increase or decrease the dilating effect on the image.

In this tutorial we will use “luispedro” image, below is the command to load it.

mahotas.demos.load('luispedro')

Below is the luispedro image 

Implementation steps : 
1. Load the image 
2. Filter the image 
3. Use otsu method for threshold of the image 
4. Create a structure of the element with the help of numpy ndarray for binary values 
5. Use the element for dilating the image 
 

Below is the implementation 

Python3




# importing required libraries
import mahotas
import mahotas.demos
from pylab import gray, imshow, show
import numpy as np
  
# loading image
luispedro = mahotas.demos.load('luispedro')
  
# filtering image
luispedro = luispedro.max(2)
  
# otsu method
T_otsu = mahotas.otsu(luispedro)
   
# image values should be greater than otsu value
img = luispedro > T_otsu
  
print("Image threshold using Otsu Method")
  
# showing image
imshow(img)
show()
  
# erode structure
es = np.array([
        [1, 1, 1, 1],
        [1, 1, 1, 1],
        [1, 1, 1, 1],
        [1, 1, 1, 1]], bool)
 
# dilating image
dilate_img = mahotas.morph.dilate(img, es)
  
# showing dilated image
print("Dilated Image")
imshow(dilate_img)
show()

Output : 

Image threshold using Otsu Method

Dilated Image

Another example  

Python3




# importing required libraries
import mahotas
import numpy as np
import matplotlib.pyplot as plt
import os
  
# loading image
img = mahotas.imread('dog_image.png')
       
# setting filter to the image
img = img[:, :, 0]
 
# otsu method
T_otsu = mahotas.otsu(img)
  
 
# image values should be greater than otsu value
img = img > T_otsu
 
print("Image threshold using Otsu Method")
 
# showing image
imshow(img)
show()
 
# erode structure
es = np.array([
        [1, 1, 1, 1],
        [1, 1, 1, 1],
        [1, 1, 1, 1],
        [1, 1, 1, 1]], bool)
 
# dilating image
dilate_img = mahotas.morph.dilate(img, es)
  
# showing dilated image
print("Dilated Image")
imshow(dilate_img)
show()

Output : 

Image threshold using Otsu Method

Dilated Image

 


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