In this article we will see how we can do conditional eroding of the image in mahotas. Erosion is one of two fundamental operations (the other being dilation) in morphological image processing from which all other morphological operations are based. It was originally defined for binary images, later being extended to grayscale images, and subsequently to complete lattices.
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.cerode method
Syntax : mahotas.cerode(img, c_grey)
Argument : It takes image object, conditional image 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 librariesimport mahotasimport mahotas.demosfrom pylab import gray, imshow, showimport numpy as np # loading imageimg = mahotas.demos.load('lena') # grey imageg = img[:, :, 1] # multiplying grey image valuesg = g * 3# filtering imageimg = img.max(2) # otsu methodT_otsu = mahotas.otsu(img) # image values should be greater than otsu valueimg = img > T_otsu print("Image threshold using Otsu Method") # showing imageimshow(img)show() # eroding image using conditional grey imagenew_img = mahotas.cerode(img, g) # showing eroded imageprint("Eroded Image")imshow(new_img)show() |
Output :
Image threshold using Otsu Method
Eroded Image
Another example
Python3
# importing required librariesimport mahotasimport numpy as npfrom pylab import gray, imshow, showimport os # loading imageimg = mahotas.imread('dog_image.png')# getting grey imageg = img[:, :, 0] # multiplying grey image valuesg = g * 2# filtering imageimg = img[:, :, 0] # otsu methodT_otsu = mahotas.otsu(img) # image values should be greater than otsu valueimg = img > T_otsu print("Image threshold using Otsu Method") # showing imageimshow(img)show() # eroding image using conditional grey imagenew_img = mahotas.cerode(img, g) # showing eroded imageprint("Eroded Image")imshow(new_img)show() |
Output :
Image threshold using Otsu Method
Eroded Image
