Face Recognition System

This project implements a Face Recognition System using Principal Component Analysis (PCA) for feature extraction and an Artificial Neural Network (ANN) for classification. The system can detect and recognize faces from images, distinguishing between authorized users and imposters.

Features

• Detects and identifies faces in images
• Recognizes known individuals using trained ANN
• Can flag unknown or imposter faces
• Built using Python with libraries like OpenCV, NumPy, and scikit-learn

How it Works

1. Face Detection: Detects faces in input images using OpenCV.
2. Feature Extraction: Reduces dimensionality of face images using PCA.
3. Classification: Classifies faces using a trained ANN model.
4. Imposter Detection: Identifies unknown faces by comparing with known centroids.