✋ Hand Gesture Recognition using OpenCV

🎯 Overview

This project demonstrates real-time hand gesture recognition using OpenCV. The model detects hand gestures and identifies specific gestures like "ONE", "TWO", "THREE", etc., based on convexity defects in the hand contour.

✨ Use Case: This system can empower specially-abled children to study online without needing to attend special schools, by enabling interaction through hand gestures.

🛠️ Features

• Real-time hand gesture recognition using a webcam.
• Detects and identifies gestures like ONE, TWO, THREE, and more.
• Visualizes contours, convex hulls, and defects for understanding gesture anatomy.
• Accessible and adaptable for educational or interactive applications.

📷 How It Works

1. Hand Detection:

   • A sub-window (ROI) isolates the hand for detection.
   • Converts the image to grayscale and applies Gaussian blur.

2. Thresholding:

   • Thresholding is used to separate the hand region from the background.

3. Contour and Convex Hull:

   • Contours are extracted from the thresholded image.
   • Convex hull and convexity defects are computed to analyze the hand's shape.

4. Gesture Recognition:

   • Defects are analyzed using the cosine rule to determine the angle between fingers.
   • Gestures are recognized based on the number of defects detected.

5. Real-Time Feedback:

   • Displays the detected gesture on the screen in real-time.

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