👁️ Eye Blinking Detection System 📌 Overview The Eye Blinking Detection System is a computer vision–based project that detects eye blinks in real time using a webcam. It leverages facial landmark detection to monitor eye movement and identify blinking patterns. This project can be used in applications such as driver drowsiness detection, attention monitoring, and human–computer interaction.

🚀 Features Real-time eye blink detection

Uses webcam for live video feed

Facial landmark–based eye tracking

Accurate blink counting

Lightweight and fast execution

🛠️ Technologies Used Python

OpenCV

Dlib

NumPy

Imutils

🧠 Working Principle The system detects facial landmarks and extracts eye regions. Using the Eye Aspect Ratio (EAR) technique:

Eyes open → EAR remains above a threshold

Eyes closed → EAR drops below the threshold

A blink is counted when EAR falls and rises again

📂 Project Structure Copy code Eye-Blinking-Detection/ │ ├── eye_blink_detection.py ├── shape_predictor_68_face_landmarks.dat ├── requirements.txt └── README.md ⚙️ Installation & Setup Clone the repository

bash Copy code pip install -r requirements.txt Download shape_predictor_68_face_landmarks.dat (Place it in the project directory)

Run the project

bash Copy code python eye_blink_detection.py 📊 Output Displays live video feed

Shows blink count on the screen

Marks eye landmarks for visualization

🎯 Use Cases Driver drowsiness detection

Online exam monitoring

Accessibility systems

Human-computer interaction

🔮 Future Enhancements Drowsiness alert system

Mobile application integration

Improved accuracy using deep learning

Multi-face blink detection

👨‍💻 Author Vansh Saxena B.Tech CSE | Python & Computer Vision Enthusiast