🔐 SecureFace AI

A real-time Face Authentication System built using Flask, MediaPipe, InsightFace (ArcFace), and MongoDB. SecureFace AI authenticates users using both traditional credentials and biometric facial recognition for enhanced security.

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📌 Features

• 👤 User Registration
• 🔑 Secure Login using Face + Password
• 📷 Real-Time Webcam Face Capture
• 😊 Face Detection using MediaPipe
• 🧠 Face Recognition using InsightFace (ArcFace)
• 📐 512-D Face Embeddings
• 📊 Cosine Similarity & Euclidean Distance Matching
• 🔒 Password Hashing (Werkzeug - Scrypt)
• 💾 MongoDB Database Integration
• 🆔 Automatic User ID Generation
• ⏳ Session-based Authentication (2 Days)
• 📱 Responsive User Interface
• 🧪 Face Similarity Testing Module

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🚀 Demo

Landing Page

• Project Introduction
• Features Overview
• Login/Register Navigation

Registration

• User Details
• Live Face Capture
• Face Embedding Generation
• Secure Password Storage

Login

• User ID Verification
• Email Verification
• Password Verification
• Live Face Verification
• Dashboard Access

Dashboard

• User Profile
• Project Information
• Authentication Status
• Technology Stack

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🏗 Project Architecture

SecureFace AI
│
├── app
│   │
│   ├── api
│   │   ├── detect.py
│   │   ├── register.py
│   │   ├── login.py
│   │   └── dashboard.py
│   │
│   ├── core
│   │   ├── face_detector.py
│   │   ├── get_embedings.py
│   │   ├── check_similarity.py
│   │   └── anti_spoof.py (Future)
│   │
│   ├── db
│   │   ├── mongodb.py
│   │   └── user_repo.py
│   │
│   └── __init__.py
│
├── image
├── static
├── templates
├── test
│
├── .env
├── requirements.txt
├── run.py
└── README.md

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⚙️ Technology Stack

Backend

• Python
• Flask
• REST API

Frontend

• HTML5
• CSS3
• JavaScript
• Fetch API

Computer Vision

• OpenCV
• MediaPipe

Face Recognition

• InsightFace
• ArcFace (buffalo_sc)

Machine Learning

• NumPy

Database

• MongoDB Atlas

Security

• Werkzeug Security (Scrypt)
• Flask Sessions
• Environment Variables

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🧠 AI Pipeline

Registration Flow

User
      │
      ▼
Capture Face
      │
      ▼
MediaPipe Face Detection
      │
      ▼
Face Crop
      │
      ▼
InsightFace Embedding
      │
      ▼
Generate User ID
      │
      ▼
Hash Password
      │
      ▼
Store User Data
      │
      ▼
MongoDB

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Login Flow

User
      │
      ▼
Capture Live Face
      │
      ▼
MediaPipe Detection
      │
      ▼
Generate Face Embedding
      │
      ▼
Verify Email
      │
      ▼
Verify User ID
      │
      ▼
Verify Password
      │
      ▼
Compare Face Embeddings
      │
      ▼
Authentication Success
      │
      ▼
Dashboard

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🔍 Face Recognition Pipeline

Input Image
      │
      ▼
MediaPipe Face Detection
      │
      ▼
Face Crop
      │
      ▼
InsightFace ArcFace
      │
      ▼
512-D Face Embedding
      │
      ▼
Cosine Similarity
      │
      ▼
Euclidean Distance
      │
      ▼
Authentication Result

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📊 Face Matching

The system compares two facial embeddings using:

• Cosine Similarity
• Euclidean Distance

Authentication is successful only if both similarity metrics satisfy predefined thresholds.

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🔒 Security Features

• Password Hashing using Scrypt
• Session Authentication
• Environment Variables
• Face Authentication
• User ID Validation
• Email Validation

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📂 Database Schema

Each registered user contains:

Field	Description
User ID	Unique Generated ID
Name	User Name
Email	User Email
Password	Hashed Password
Face Embedding	512-D Vector
Created At	Registration Date

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🧪 Testing

The project includes testing modules for:

Face Detection

• Detect face successfully
• Face crop validation

Face Embedding

• Generate 512-dimensional embeddings

Similarity Testing

Tests include:

• Same Person Matching
• Different Person Matching

Outputs:

• Cosine Similarity
• Euclidean Distance
• Match Decision

Results are stored in:

similarity_results.csv

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📦 Installation

Clone Repository

git clone https://github.com/yourusername/SecureFace-AI.git

cd SecureFace-AI

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Create Virtual Environment

python -m venv faceenv

Activate

Windows

faceenv\Scripts\activate

Linux/Mac

source faceenv/bin/activate

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Install Dependencies

pip install -r requirements.txt

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Configure Environment Variables

Create a .env file

MONGO_URI=your_mongodb_connection_string

SECRET_KEY=your_secret_key

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Run Project

python run.py

Application will run at

http://127.0.0.1:10000

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📈 Future Improvements

• Anti-Spoof Detection (MiniFASNet)
• JWT Authentication
• PostgreSQL Support
• Qdrant Vector Database
• Docker Deployment
• Redis Session Storage
• Admin Dashboard
• Authentication Logs
• Email Verification
• Password Reset
• Face Registration History
• Multi-Factor Authentication

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🎯 Project Highlights

• Real-Time Face Authentication
• Secure User Registration
• Face + Password Login
• InsightFace ArcFace Recognition
• MediaPipe Face Detection
• MongoDB Integration
• Flask Modular Architecture
• Session-Based Authentication
• Face Similarity Evaluation
• Production-Oriented Design

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👨‍💻 Author

Kumar Shanu

B.Tech Computer Science Engineering (AI & ML)

Machine Learning & Full Stack Developer

GitHub: https://github.com/kumar-shanu-1881/

LinkedIn: https://www.linkedin.com/in/kumar-shanu-9219a5293/

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⭐ If you found this project useful, consider giving it a star on GitHub!