In this article we will see how we can get the image ellipse axes in mahotas. Ellipse exes are parameters of the image ellipse, parameters of the constant intensity ellipse with the same mass and second-order moments as the original image.
For this tutorial we will use 'lena' image, below is the command to load the lena imageÂ
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mahotas.demos.load('lena')
Below is the lena imageÂ
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In order to do this we will use mahotas.features.ellipse_axes method
Syntax : mahotas.features.ellipse_axes(img)
Argument : It takes image object as argument
Return : It returns two float valuesÂ
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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
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image = image[:, :, 0]
Below is the implementationÂ
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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 image
img = mahotas.demos.load('lena')
# filtering image
img = img.max(2)
print("Image")
# showing image
imshow(img)
show()
# computing Parameters of the âimage ellipseâ
semimajor, semiminor = mahotas.features.ellipse_axes(img)
# showing value
print("Semi Major Exes : " + str(semimajor))
print("Semi Minor Exes : " + str(semiminor))
Output :
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Image
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Semi Major Exes : 295.60277400592844 Semi Minor Exes : 295.60277400592844
Another exampleÂ
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# 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()
# computing Parameters of the âimage ellipseâ
semimajor, semiminor = mahotas.features.ellipse_axes(img)
# showing value
print("Semi Major Exes : " + str(semimajor))
print("Semi Minor Exes : " + str(semiminor))
Output :
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Image
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Semi Major Exes : 508.79612573247636 Semi Minor Exes : 308.5809619544451
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