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Mahotas – Bernsen local thresholding

  • Last Updated : 20 Jul, 2021

In this article, we will see how we can implement bernsen local thresholding in mahotas. Bernsen’s method is one of locally adaptive binarization methods developed for image segmentation. In this study, Bernsen’s locally adaptive binarization method is implemented and then tested for different grayscale images.

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.thresholding.bernsen method  



Syntax : mahotas.thresholding.bernsen(image, contrast_threshold, global_threshold)
Argument : It takes image object and two integer 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]

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')
 
 
# loading image as grey
photo = mahotas.demos.load('luispedro', as_grey = True)
 
# converting image type to unit8
# beacuse as_grey returns floating values
photo = photo.astype(np.uint8)
 
# showing original image
print("Image")
imshow(photo)
show()
 
# bernsen threshold
photo = mahotas.thresholding.bernsen(photo, 7, 200)
 
 
print("Image with bernsen threshold")
 
# showing image
imshow(photo)
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]
 
print("Image")
 
# showing the image
imshow(img)
show()
 
 
# bernsen threshold
img = mahotas.thresholding.bernsen(img, 5, 100)
 
 
print("Image with bernsen threshold")
 
# showing image
imshow(img)
show()

Output : 

 

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