Mahotas – Regional Minima of Image

In this article, we will see how we can get regional minima of images 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 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.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