Open In App

Mahotas – Eroding Image

Improve
Improve
Like Article
Like
Save
Share
Report

In this article we will see how we can erode the image in mahotas. Erosion (usually represented by ?) is one of two fundamental operations (the other being dilation) in morphological image processing from which all other morphological operations are based. It was originally defined for binary images, later being extended to grayscale images, and subsequently to complete lattices.

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

mahotas.demos.load('luispedro')

Below is the luispedro image  

In order to do this we will use mahotas.morph.erodemethod 

Syntax : mahotas.morph.erode(image)
Argument :It takes image object as argument
Return : It returns image object 
 

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 

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()
 
# eroding image
new_img = mahotas.morph.erode(img)
 
# showing eroded image
print("Eroded Image")
imshow(new_img)
show()


Output : 

Image threshold using Otsu Method 

Eroded 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()
 
# eroding image
new_img = mahotas.morph.erode(img)
 
# showing eroded image
print("Eroded Image")
imshow(new_img)
show()


Output : 

Image threshold using Otsu Method 

Eroded Image

 



Last Updated : 29 Jul, 2021
Like Article
Save Article
Previous
Next
Share your thoughts in the comments
Similar Reads