In this article we will see how we can do conditional dilating of the image in mahotas. Dilation adds pixels to the boundaries of objects in an image, while erosion removes pixels on object boundaries. The number of pixels added or removed from the objects in an image depends on the size and shape of the structuring element used to process the image. We use mahotas.morph.dilate method to do normal dilating.
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.cdilate method
Syntax : mahotas.cdilate(img, c_grey, Bc={3×3 cross}, n=1)
Argument : It takes image object, conditional image as compulsory argument, element structure and iteration number are optional 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# 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 * 100 # 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() # dilating image using conditional grey imagedilate_img = mahotas.cdilate(img, g) # showing dilated imageprint("Dilated Image")imshow(dilate_img)show() |
Output :
Image threshold using Otsu Method
Dilated Image
Another example
Python3
# importing required librariesimport mahotasimport numpy as npfrom pylab import gray, imshow, showimport os # loading imageimg = mahotas.imread('dog_image.png') # grey imageg = img[:, :, 2]# multiplying grey image valuesg = g * 100 # 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() # dilating image using conditional grey imagedilate_img = mahotas.cdilate(img, g) # showing dilated imageprint("Dilated Image")imshow(dilate_img)show() |
Output :
Image threshold using Otsu Method
Dilated Image
