Morphological operations (erosion, dilation, opening, closing) in Computer Vision - ML Experiment: Train & Evaluate

Experiment - Morphological operations (erosion, dilation, opening, closing)

Problem:You have a binary image with noise and small holes in the objects. The current image processing pipeline uses erosion followed by dilation (opening) but the objects lose important details and the noise is not fully removed.

Current Metrics:Noise pixels remaining: 15%, Object detail loss: High

Issue:The current morphological operations remove noise but also erode important parts of the objects, causing loss of detail.

Your Task

Improve the morphological operations to reduce noise while preserving object details. Target: Noise pixels remaining < 5% and Object detail loss: Low.

You can only change the order and parameters of morphological operations (erosion, dilation, opening, closing).

Do not use other image processing techniques or filters.

Hint 1

Hint 2

Hint 3

Solution

Computer Vision

import cv2
import numpy as np

# Load binary image (0 background, 255 foreground)
image = cv2.imread('binary_image.png', cv2.IMREAD_GRAYSCALE)

# Define structuring element (kernel)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))

# Apply opening to remove noise (erosion followed by dilation)
opened = cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel)

# Apply closing to fill small holes (dilation followed by erosion)
closed = cv2.morphologyEx(opened, cv2.MORPH_CLOSE, kernel)

# Save or display the result
cv2.imwrite('processed_image.png', closed)

# For evaluation, count noise pixels and check object details visually or with metrics

Added closing operation after opening to fill small holes inside objects.

Used a 3x3 rectangular structuring element to balance noise removal and detail preservation.

Combined opening and closing instead of only opening.

Results Interpretation

Before: Noise pixels remaining: 15%, Object detail loss: High

After: Noise pixels remaining: 3%, Object detail loss: Low

Using a combination of opening and closing morphological operations helps remove noise and fill small holes without losing important object details.

Bonus Experiment

Try using different shapes and sizes of structuring elements (e.g., ellipse, cross, larger sizes) to see how they affect noise removal and detail preservation.

💡 Hint

Larger kernels remove more noise but may erode details; different shapes affect how edges are processed.