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Mahotas – Otsu’s method

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In this article we will see how we can implement otsu’s method in mahotas. In computer vision and image processing, Otsu’s method, named after Nobuyuki Otsu, is used to perform automatic image thresholding. In the simplest form, the algorithm returns a single intensity threshold that separates pixels into two classes, foreground and background. 

In this tutorial we will use “luispedro” image, below is the command to load it. 

mahotas.demos.load('luispedro')

Below is the luispedro image  

In order to do this we will use mahotas.otsu method  

Syntax : mahotas.otsu(image)
Argument : It takes image object as argument
Return : It returns integer 
 

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]

Example 1: 

Python3




# importing required libraries
import mahotas
import mahotas.demos
import numpy as np
from pylab import imshow, gray, show
from os import path
 
# loading the image
photo = mahotas.demos.load('luispedro')
 
# showing original image
print("Original Image")
imshow(photo)
show()
 
# loading image as grey
photo = mahotas.demos.load('luispedro', as_grey = True)
 
# converting image type to unit8
# because as_grey returns floating values
photo = photo.astype(np.uint8)
 
# otsu method
T_otsu = mahotas.otsu(photo)
 
# printing otsu value
print("Otsu Method value : " + str(T_otsu))
 
print("Image threshold using Otsu Method")
# showing image
# image values should be greater than otsu value
imshow(photo > T_otsu)
show()


Output : 

Example 2: 

Python3




# importing required libraries
import mahotas
import numpy as np
from pylab import imshow, show
import os
 
 
# loading image
img = mahotas.imread('dog_image.png')
     
 
# setting filter to the image
img = img[:, :, 0]
 
imshow(img)
show()
 
 
# otsu method
T_otsu = mahotas.otsu(img)
 
# printing otsu value
print("Otsu Method value : " + str(T_otsu))
 
print("Image threshold using Otsu Method")
# showing image
# image values should be greater than otsu value
imshow(img > T_otsu)
show()


Output : 

 



Last Updated : 29 Jul, 2021
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