Practical: Erosion and Dilation in Python

We saw how to perform dilation on thesholded images in the previous videos. This practical gives you a chance to try this for yourself, as well as adapting the code so it performs the erosion algorithm instead.

All the instructions you need are in the attached pdf Erosion practical.

The image data used in the practical is displayed below (right-click, save image as to use).

The code for dilation is below (copy / paste to use):

from ij.gui import NewImage
from ij import IJ

# get the current image selected in Fiji
imp = IJ.getImage()
processor = imp.getProcessor()

# get width and height of image
w = processor.getWidth()
h = processor.getHeight()

# make new image (initially filled with black pixels)
output = NewImage.createImage("Dilated",w, h, 1, 8, NewImage.FILL_BLACK)
output_processor = output.getProcessor()

# search all neighbouring pixels of each pixel in turn
for x in range(1, w-1):
	for y in range(1, h-1):
 foundWhite = False
 for a in range(x-1, x+2):
 for b in range(y-1, y+2):
 if(processor.getPixel(a,b)==255):
 foundWhite = True

 if foundWhite:
 output_processor.setColor(255)
 output_processor.drawPixel(x,y)

# show the result
output.show()

Alternatively the code can also be found at our Github repository https://github.com/nlmellor/PhenoDataCampp/tree/main/ImageAnalysis/code.

Please let us know how you get on in the comments below.