Mahotas – Getting Image Moments
Last Updated :
19 Feb, 2022
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 the “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
import mahotas
import mahotas.demos
from pylab import gray, imshow, show
import numpy as np
import matplotlib.pyplot as plt
img = mahotas.demos.load( 'lena' )
img = img. max ( 2 )
print ( "Image" )
imshow(img)
show()
p0 = 5.5
p1 = 5.5
moment = mahotas.moments(img, p0, p1)
print ( "Moment value = " + str (moment))
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Output :
Image
Moment value = 6.784986531904299e+35
Another example
Python3
import mahotas
import numpy as np
from pylab import gray, imshow, show
import os
import matplotlib.pyplot as plt
img = mahotas.imread( 'dog_image.png' )
img = img[:, :, 0 ]
print ( "Image" )
imshow(img)
show()
p0 = 10.5
p1 = 2.5
moment = mahotas.moments(img, p0, p1)
print ( "Moment value = " + str (moment))
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Output :
Image
Moment value = 1.5229432312149368e+42
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