Criminal Detection System

Author: Yeshwanth Goud Guddibagu
Regd. No: HU21CSCI0200001
Institution: GITAM (Deemed to be University), School of Science, Department of Computer Science
Project Guide: Dr. Raghavendra Kulkarni, Ph. D.

Project Overview

The Criminal Detection System is a portable, real-time surveillance solution designed to enhance law enforcement efforts using advanced facial recognition technology. This project leverages computer vision techniques and cloud-based database management to provide comprehensive criminal registration, dynamic suspect scanning, and seamless integration with CCTV infrastructure using standard webcams.

Features

• Real-Time Surveillance: Monitor and track individuals of interest using webcams.
• Criminal Registration: Capture and store detailed information and photos of suspects in a cloud-based database.
• Dynamic Scanning: Compare live video feeds with a database of known offenders to identify and flag suspects.
• Facial Recognition: Use pre-trained Haar Cascade classifiers for accurate face detection and recognition.
• CCTV Integration: Connect with existing CCTV infrastructure to extend surveillance capabilities.
• Cloud-Based Scalability: Utilize AWS for secure and scalable data storage and management.
• Portability and Accessibility: Access the system from anywhere using standard computing devices.

System Architecture

• Webcam: Captures real-time video footage for analysis.
• Facial Recognition Module: Detects and recognizes faces using OpenCV and custom algorithms.
• Database (AWS MySQL): Stores criminal data securely in the cloud.
• GUI: User interface for criminal registration, face scanning, and database access.

Technologies Used

• Programming Language: Python
• Libraries: OpenCV, Tkinter, pymysql
• Database: MySQL hosted on AWS
• Algorithms: Viola-Jones for face detection, Eigenfaces for face recognition
• Cloud Services: Amazon Web Services (AWS)

Installation and Setup

1. Clone the Repository:

   git clone https://github.com/yourusername/criminal-detection-system.git
   cd criminal-detection-system
   

Set Up Virtual Environment:

python -m venv env
source env/bin/activate   # On Windows, use `env\Scripts\activate`

Install Dependencies:

pip install -r requirements.txt

Configure Database:

• Set up an AWS MySQL database. Update database connection details in the configuration file.

Run the Application:

python main.py

Usage

• Register a Criminal: Use the GUI to enter details and capture photos of a suspect.

• Scan for Criminals: Activate real-time surveillance to detect and identify suspects in live video feeds.

• Access Database: Retrieve and manage criminal records from the cloud-based database.

Project Structure

• main.py - Main application script.

• config.py - Configuration file for database settings.

• requirements.txt - List of dependencies.

• modules/ - Directory containing core modules for face detection, recognition, and database operations.

• gui/ - Directory containing GUI implementation.

Future Work

• Integration with additional biometric identification methods.

• Enhancement of facial recognition accuracy under varying conditions.

• Expansion of the system to support multi-camera setups.

• Addressing ethical and privacy concerns in facial recognition technology.

Acknowledgements

I would like to thank my project guide, Prof. Dr. Raghavendra Kulkarni, for his constant support and guidance. I also extend my gratitude to the faculty members of the Department of Computer Science, my friends, and family for their encouragement and assistance throughout the project.

##DEMO

demo.mp4