Mahotas – Majority filter

In this article, we will see how we can apply majority filter to the image in mahotas. In Majority filters for each group of pixels considered in the input map, a majority filter assign the predominant (=mostly frequently occurring) value or class name of these to the center pixel in the output map.

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.majority_filter method
Syntax : mahotas.majority_filter(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()

# applying majority filter
new_img = mahotas.majority_filter(img)


# showing image
print("Majority Filter")
imshow(new_img)
show()

Output :

Image

Majority Filter

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()

# applying majority filter
new_img = mahotas.majority_filter(img)


# showing image
print("Majority Filter")
imshow(new_img)
show()

Output :

Image

Majority Filter