AI-Enhanced CCTV Surveillance System

Facial Recognition using Python and OpenCV

This repository contains an AI-powered facial recognition surveillance system developed using Python and OpenCV.

The system detects human faces in real time, captures facial datasets, trains a recognition model, and identifies individuals using computer vision techniques.

This project demonstrates how AI-enhanced CCTV systems can be used for identity recognition and monitoring.

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Project Overview

Traditional CCTV systems only record footage without understanding what is happening in the scene.

This project enhances surveillance systems by introducing facial recognition capabilities, allowing the system to identify individuals from a trained dataset.

The system performs the following tasks:

• Detects faces using Haar Cascade classifiers
• Captures facial images to build a dataset
• Trains a recognition model
• Recognizes faces from a live camera feed

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Key Features

• Real-time face detection
• Facial dataset generation
• Face recognition using trained models
• Identity verification
• Graphical user interface for system interaction

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Project Structure

Baze-University-Final-Year-Project
│
├── dataset_creator.py              # Captures facial datasets
├── detector.py                     # Face detection logic
├── trainer.py                      # Model training script
├── gui.py                          # Graphical user interface
├── main.py                         # Main application entry point
│
├── Face Detection.bat              # Script to launch the system
│
├── haarcascade_eye.xml             # Eye detection model
├── haarcascade_frontalface_default.xml   # Face detection model
├── haarcascade_profileface.xml     # Profile face detection model
│
├── data/                           # Captured training image dataset
├── recognizer/                     # Trained recognition model
├── unknown/                        # Images not recognized by the system
│
├── requirement.txt                 # Project dependencies
├── face_recognition.db             # Local recognition database
└── README.md                       # Project documentation

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Technologies Used

• Python
• OpenCV
• Computer Vision
• Machine Learning
• Haar Cascade Classifiers

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Installation

Clone the repository

git clone https://github.com/bxthxl/Baze-University-Final-Year-Project.git

Navigate to the project directory

cd Baze-University-Final-Year-Project

Install required dependencies

pip install -r requirement.txt

Run the system

python main.py

Or launch using the batch file

Face Detection.bat

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Future Improvements

Possible improvements for this project include:

• Deep learning–based facial recognition models
• Integration with real CCTV camera systems
• Web dashboard for monitoring
• Cloud-based identity database
• Multi-camera surveillance support

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Author

Bethel Eberechukwu George-Nwaeke

Computer Scientist
Software Developer | AI Systems Enthusiast

GitHub: https://github.com/bxthxl