Face Recognition Login

Project Overview

A cutting-edge biometric authentication system that enables users to log in using facial recognition. The system leverages Azure Cognitive Services for accurate face detection and verification, providing a seamless and secure alternative to traditional passwords.

Designed for enterprise applications requiring enhanced security, the system includes liveness detection to prevent photo-based spoofing attacks and supports multi-factor authentication integration.

Key Features

• Real-time Face Detection

  Instant face detection with 99.9% accuracy using Azure Face API

• Liveness Detection

  Anti-spoofing measures to detect photos, videos, or masks

• Multi-factor Integration

  Combine facial recognition with PIN or device authentication

• Face Enrollment

  Easy face registration with multiple angle capture for accuracy

• Audit Logging

  Complete authentication logs with timestamps and confidence scores

• Privacy Compliance

  GDPR-compliant data handling with encrypted face encodings

Technical Implementation

The system captures face images through the browser's camera API and sends them to Azure Face API for analysis. Face encodings are stored securely (not actual images) and compared during authentication with configurable confidence thresholds.

Azure AI

.NET Core

Angular

SQL Server

Architecture Highlights

• Azure Face API: Industry-leading facial recognition with 99.9% accuracy
• Secure Encoding: Only encrypted face vectors stored, never raw images
• WebRTC Integration: Browser-based camera capture with real-time preview
• Fallback Authentication: Alternative login methods when face recognition unavailable
• Threshold Configuration: Adjustable confidence levels per security requirements