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Mahotas – Getting Image Moments
  • Last Updated : 29 May, 2021

In this article we will see how we can the image moments in mahotas. In image processing, computer vision and related fields, an image moment is a certain particular weighted average of the image pixels’ intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. Image moments are useful to describe objects after segmentation.

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.moments method
Syntax : mahotas.moments(img, p0, p1)
Argument : It takes image object and two float values 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
import matplotlib.pyplot as plt
   
# loading image
img = mahotas.demos.load('lena')
   
# filtering image
img = img.max(2)
 
print("Image")
   
# showing image
imshow(img)
show()
 
# Power for first dimension
p0 = 5.5
 
# Power for second dimension
p1 = 5.5
 
 
# getting moments
moment = mahotas.moments(img, p0, p1)
  
 
# printing moments
print("Moment value = " + str(moment))

Output :

Image
 

Moment value = 6.784986531904299e+35

Another example  

Python3




# importing required libraries
import mahotas
import numpy as np
from pylab import gray, imshow, show
import os
import matplotlib.pyplot as plt
  
# loading image
img = mahotas.imread('dog_image.png')
 
 
# filtering image
img = img[:, :, 0]
   
print("Image")
   
# showing image
imshow(img)
show()
 
# Power for first dimension
p0 = 10.5
 
# Power for second dimension
p1 = 2.5
 
 
# getting moments
moment = mahotas.moments(img, p0, p1)
  
 
# printing moments
print("Moment value = " + str(moment))

Output :

Image
 

Moment value = 1.5229432312149368e+42

 

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