Morphological operations (erosion, dilation) in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to perform erosion on the binary image using scipy.

SciPy

from scipy import ndimage

binary_image = [[0, 1, 1, 0], [1, 1, 1, 0], [0, 1, 0, 0]]
eroded_image = ndimage.binary_[1](binary_image)
print(eroded_image)

Drag options to blanks, or click blank then click option'

Aerosion

Bdilation

Copening

Dclosing

Attempts:

3 left

💡 Hint

Common Mistakes

Using dilation instead of erosion

Misspelling the function name

Confusing opening and erosion

The binary_erosion function performs erosion on a binary image, shrinking the white regions.

2fill in blank

medium

Complete the code to perform dilation on the binary image using scipy.

SciPy

from scipy import ndimage

binary_image = [[0, 1, 0], [1, 0, 1], [0, 1, 0]]
dilated_image = ndimage.binary_[1](binary_image)
print(dilated_image)

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Aerosion

Bdilation

Cgradient

Dhit_or_miss

Attempts:

3 left

💡 Hint

Common Mistakes

Using erosion instead of dilation

Using unrelated morphological functions

Forgetting to import ndimage

The binary_dilation function expands the white regions in a binary image.

3fill in blank

hard

Fix the error in the code to correctly perform erosion with a 3x3 structuring element.

SciPy

from scipy import ndimage
import numpy as np

binary_image = np.array([[1, 1, 0], [1, 0, 1], [0, 1, 1]])
structure = np.ones((3, 3))
eroded = ndimage.binary_[1](binary_image, structure=structure)
print(eroded)

Drag options to blanks, or click blank then click option'

Aopening

Bclosing

Cerosion

Ddilation

Attempts:

3 left

💡 Hint

Common Mistakes

Using dilation instead of erosion

Passing structuring element to wrong argument

Misspelling function name

Using binary_erosion with a 3x3 structuring element correctly erodes the image.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each pixel to its dilation and erosion results.

SciPy

from scipy import ndimage
import numpy as np

image = np.array([[0, 1], [1, 0]])
results = {pixel: (ndimage.binary_[1](image == pixel), ndimage.binary_[2](image == pixel)) for pixel in [0, 1]}
print(results)

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Adilation

Berosion

Copening

Dclosing

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping dilation and erosion

Using opening or closing instead

Not using binary_ functions

The dictionary maps each pixel value to its dilation and erosion results using binary_dilation and binary_erosion.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each pixel to its closing, erosion, and opening results.

SciPy

from scipy import ndimage
import numpy as np

image = np.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]])
results = {pixel: (ndimage.binary_[1](image == pixel), ndimage.binary_[2](image == pixel), ndimage.binary_[3](image == pixel)) for pixel in [0, 1]}
print(results)

Drag options to blanks, or click blank then click option'

Adilation

Berosion

Copening

Dclosing

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up opening and closing

Using dilation instead of closing

Not using binary_ functions

The dictionary comprehension maps each pixel to its closing (binary_closing), erosion (binary_erosion), and opening (binary_opening) results.