Mahotas – Roundness of Image

In this article we will see how we can get the image roundness feature in mahotas. Roundness is dominated by the shape’s gross features rather than the definition of its edges and corners, or the surface roughness of a manufactured object. A smooth ellipse can have low roundness, if its eccentricity is large

For this tutorial we will use ‘lena’ image, below is the command to load the lena image

mahotas.demos.load('lena')

Below is the lena image

In order to do this we will use mahotas.features.roundness method

Syntax : mahotas.features.roundness(img)



Argument : It takes image object as argument

Return : It returns float value

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

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# 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()
  
# computing roundness in image
value = mahotas.features.roundness(img)
   
  
# printing value
print("Roundness : " + str(value))

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Output :

Image

Roundness : 0.0

Another example

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code

# 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()
  
# computing roundness in image
value = mahotas.features.roundness(img)
   
  
# printing value
print("Roundness : " + str(value))

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Output :

Image

Roundness : 0.04297201733896709



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