In this article we will see how we can get the eccentricity of the image in mahotas. Eccentricity measures the shortest length of the paths from a given vertex v to reach any other vertex w of a connected graph. Computed for every vertex v it transforms the connectivity structure of the graph into a set of values. For a connected region of a digital image it is defined through its neighbourhood graph and the given metric.
mahotas.demos.load('lena')
Below is the lena image
In order to do this we will use mahotas.features.eccentricity( method
Syntax : mahotas.features.eccentricity(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
Python3
# importing required librariesimport mahotasimport mahotas.demosfrom pylab import gray, imshow, showimport numpy as npimport matplotlib.pyplot as plt # loading imageimg = mahotas.demos.load('lena') # filtering imageimg = img.max(2)print("Image") # showing imageimshow(img)show()# computing eccentricity valuevalue = mahotas.features.eccentricity(img) # showing valueprint("Eccentricity value = " + str(value)) |
Output :
Image
Eccentricity value = 0.0
Another example
Python3
# importing required librariesimport mahotasimport numpy as npfrom pylab import gray, imshow, showimport osimport matplotlib.pyplot as plt # loading imageimg = mahotas.imread('dog_image.png')# filtering imageimg = img[:, :, 0] print("Image") # showing imageimshow(img)show()# computing eccentricity valuevalue = mahotas.features.eccentricity(img) # showing valueprint("Eccentricity value = " + str(value)) |
Output :
Image
Eccentricity value = 0.7950893156644899
