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Mahotas – Removing Bordered Labelled
  • Last Updated : 21 Apr, 2021

In this article we will see how we can remove the bordered label from the labelled image in mahotas. Border labels are those labels which are touching the border, we can create labelled image from normal image with the help of mahotas.label method.
For this we are going to use the fluorescent microscopy image from a nuclear segmentation benchmark. We can get the image with the help of command given below 
 

mhotas.demos.nuclear_image()

Below is the nuclear_image 
 

Labelled images are integer images where the values correspond to different regions. I.e., region 1 is all of the pixels which have value 1, region two is the pixels with value 2, and so on
In order to do this we will use mahotas.remove_bordering method 
 

Syntax : mahotas.remove_bordering(labelled)
Argument : It takes labelled image object as argument
Return : It returns the labelled image without label at the borders 
 



Example 1: 
 

Python3




# importing required libraries
import mahotas
import numpy as np
from pylab import imshow, show
import os
 
# loading nuclear image
f = mahotas.demos.load('nuclear')
 
# setting filter to the image
f = f[:, :, 0]
 
# setting gaussian filter
f = mahotas.gaussian_filter(f, 4)
 
# setting threshold value
f = (f> f.mean())
 
# creating a labelled image
labelled, n_nucleus = mahotas.label(f)
 
# showing the labelled image
print("Labelled Image")
imshow(labelled)
show()
 
# removing border labels
labelled = mahotas.labelled.remove_bordering(labelled)
 
# showing the image
print("No border Label")
imshow(labelled)
show()

Output : 
 

Example 2: 
 

Python3




# importing required libraries
import numpy as np
import mahotas
from pylab import imshow, show
 
# loading iamge
img = mahotas.imread('dog_image.png')
   
# filtering the imagwe
img = img[:, :, 0]
    
# setting gaussian filter
gaussian = mahotas.gaussian_filter(img, 15)
 
# setting threshold value
gaussian = (gaussian > gaussian.mean())
 
# creating a labelled image
labelled, n_nucleus = mahotas.label(gaussian)
  
print("Labelled Image")
# showing the gaussian filter
imshow(labelled)
show()
 
# removing border labels
labelled = mahotas.labelled.remove_bordering(labelled)
 
# showing the image
print("No border Label")
imshow(labelled)
show()

Output : 
 

 

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