ahmedhosny2024 / image-processing-labs

✨ Solution of image processing course labs. They handle many related topics to image processing like smoothing , classification ...etc

Image Processing Labs

”The World Behind Your Eyes 🪐“

Table of Contents

• 📙 Overview
• ✨ Contributors
• 🔒 License

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Overview

• Solution of image processing course labs
• Content

• 🚀 Lab 1 (Link)

  • Basics of Python, Jupyter and Skimage
  • Read & print image
  • Show half of image
  • Convert RGB to HSV
  • Convert RGB to gray scale
  • Apply salt & pepper noise
  • Apply histogram with different pins
  • Draw a grey-scale image that has uniform histogram

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• ⚡ Lab 2 (Link)

  • Learn the concept of Convolution in the space domain.
  • Learn the concept of Inverse Fourier Transform
  • Learn the concept of Multiplication in frequency domain

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• 🚄 Lab 3 (Link)

  • Smoothing
  • Median filter algorithm and compare it with skimage median filter
  • Apply Gaussion Filters with different Sigma

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• 🛤 Lab 4 (Link)

  • Know the effect of Negative transformation.
  • Know the effect of contrast enhancement.
  • Know the effect of gamma correction.
  • Understand and implement Histogram Equalization.

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• 🚧 Lab 5 (Link)

  • Apply and notice the differences between edge detection techniques.
  • Understand the effect of different parameters used in edge detection techniques.
  • Learn and implement “Sobel operator “and “LOG” edge detection techniques.

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• ⛰ Lab 6 (Link)

  • Erosion / Dilation
  • Credit Card Number Extraction
  • Skeletonization with Skimage's "skeletonize(image)" and Skimage's "thin(image, max_iter)"

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• ❄ Lab 7 (Link)

  • Learn how to deal with pixel level values with minimum usage of already-implemented functions.
  • Learn simple threshold technique(s).

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• ⛱ Lab 8 (Link)

  • Learn adaptive thresholding technique(s).

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• 🚨 Lab 9 (Link)

  • A segment for clothes with a jeans texture
  • A segment for clothes with a cotton texture
  • A segment for the background
  • Implement your own function that computes the LBP histogram of a grayscale image

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Contributors

Ahmed Hosny

Nour Ziad Almulhem

Eslam Ashraf

🔒 License

Note: This software is licensed under MIT License, See License for more information ©AhmedHosny2024.