Computer Vision Assignment 01

Overview

This project is a Computer Vision Assignment that demonstrates the creation of a hybrid image by combining low-frequency and high-frequency components of two input images. It leverages foundational image processing techniques such as Gaussian blurring and image arithmetic.

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Objectives

• To understand and apply image filtering techniques, including low-pass and high-pass filters.
• To create a hybrid image that visually integrates features of two images.
• To use Python libraries like OpenCV and Matplotlib for image processing and visualization.

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Features

1. Image Input:
   • Allows users to upload two images (e.g., of group members).
   • Images are processed in grayscale for simplicity.

2. Image Preprocessing:

   • Resizes the uploaded images to a standard dimension of 500x500 pixels.

3. Filtering Operations:

   • Low-Pass Filter: A Gaussian Blur is applied to extract smooth, low-frequency components from the first image.
   • High-Pass Filter: High-frequency details are extracted from the second image by subtracting a blurred version of the image from the original.

4. Hybrid Image Creation:

   • Combines the low-pass filtered image and the high-pass filtered image to generate a hybrid image.

5. Visualization:

   • Displays the original, filtered, and hybrid images for comparison using Matplotlib.

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Dependencies

The following Python libraries are required:

• OpenCV: For image processing.
• NumPy: For numerical operations.
• Matplotlib: For image visualization.

To install the dependencies, run:

pip install opencv-python-headless numpy matplotlib

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How to Run

1. Upload Images:

   • Run the code and upload the required images when prompted. The first image is for the low-pass filter, and the second is for the high-pass filter.

2. View Results:

   • The script will process the images and display:
     • Original images
     • Low-pass and high-pass filtered images
     • Final hybrid image

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Code Structure

Main Steps:

1. Import Required Libraries
2. Image Upload and Preprocessing
   • Resize images to 500x500 pixels.
3. Apply Filters
   • Gaussian blur for low-pass filtering.
   • Image subtraction for high-pass filtering.
4. Combine Filters
   • Weighted addition of filtered images.
5. Display Results

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Results

The hybrid image combines the dominant features of one image (low-frequency) with the fine details of another (high-frequency), creating a unique visual effect.

Author

• Group Members: Muhammad Mubashir, Javid Mir.
• Assignment Title: Assignment 01 – Computer Vision

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Acknowledgments

• Instructor: Engr Ahmed Khawaja
• Course: Computer Vision – Software Engineering Program