Skip to content
Related Articles

Related Articles

Improve Article

Mahotas – Closing Process on Image

  • Last Updated : 30 Jul, 2021
Geek Week

In this article we will see how we can perform closing on the image in mahotas. Closing is a process in which first dilation operation is performed and then erosion operation is performed. It eliminates the small holes from the obtained image, it is used for smoothening of contour and fusing of narrow breaks.

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.closemethod  



Syntax : mahotas.morph.close(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()
 
# closing image
new_img = mahotas.morph.close(img)
  
# showing new image
print("Closed Image")
imshow(new_img)
show()

Output : 

Image threshold using Otsu Method 

Closed 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()
 
# closing image
new_img = mahotas.morph.close(img)
  
# showing new image
print("Closed Image")
imshow(new_img)
show()

Output : 

Image threshold using Otsu Method 

Closed Image

 

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course




My Personal Notes arrow_drop_up
Recommended Articles
Page :