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Mahotas – Regional Minima of Image

  • Last Updated : 18 May, 2021

In this article we will see how we can get regional minima of image in mahotas. Regional minima is a stricter criterion than the local minima as it takes the whole object into account and not just the neighborhood. Minima are connected components of pixels with a constant intensity value, surrounded by pixels with a higher value. 
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.regmin method
Syntax : mahotas.regmin(img)
Argument : It takes image object 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()
 
# finding regional minima
new_img = mahotas.regmin(img)
  
 
# showing image
print("Regional Minima")
imshow(new_img)
show()

Output :
 

Image

 

 

Regional Minima

 



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()
 
# finding regional minima
new_img = mahotas.regmin(img)
  
 
# showing image
print("Regional Minima")
imshow(new_img)
show()

Output :
 

Image

 

 

Regional Minima

 

 

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