Mahotas - Appropriate structuring element of image

In this article we will see how we can get the appropriate structuring element of the image in mahotas. A structuring element is a matrix that identifies the pixel in the image being processed and defines the neighborhood used in the processing of each pixel.
In this tutorial we will use “lena” image, below is the command to load it.

mahotas.demos.load('lena')

Below is the lena image

In order to do this we will use mahotas.get_structuring_elem method

Syntax : mahotas.get_structuring_elem(img, n)

Argument : It takes image object and integer as argument

Return : It returns numpy ndarray

Note : Input image should be filtered or should be loaded as grey

In order to filter the image we will take the image object which is numpy.ndarray and filter it with the help of indexing, below is the command to do this

image = image[:, :, 0]

Below is the implementation

# importing required libraries 
import mahotas 
import mahotas.demos 
from pylab import gray, imshow, show 
import numpy as np 
import matplotlib.pyplot as plt 
    
# loading iamge 
img = mahotas.demos.load('lena') 
  
  
    
# filtering image 
img = img.max(2) 
  
print("Image") 
    
# showing image 
imshow(img) 
show() 
  
# getting structring element 
value = mahotas.get_structuring_elem(img, 1) 
   
# showing value 
print(value) 

Output :

Image

[[0 1 0]
 [1 1 1]
 [0 1 0]]

Another example

# importing required libraries 
import mahotas 
import numpy as np 
from pylab import gray, imshow, show 
import os 
import matplotlib.pyplot as plt 
   
# loading iamge 
img = mahotas.imread('dog_image.png') 
  
  
# fltering image 
img = img[:, :, 0] 
    
print("Image") 
    
# showing image 
imshow(img) 
show() 
  
# getting structring element 
value = mahotas.get_structuring_elem(img, 2) 
   
# showing value 
print(value) 

Output :

Image

[[1 1 1]
 [1 1 1]
 [1 1 1]]

My Personal Notes

Aug	SEP	Oct
	22
2019	2020	2021

Mahotas – Appropriate structuring element of image

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