PCA-Based Face Recognition MATLAB System

The Principal Component Analysis (PCA) based face recognition system provides an efficient and user-friendly solution that can be deployed immediately without complex debugging processes. The system demonstrates proven effectiveness through its implementation of the eigenface algorithm, which reduces facial dimensions while preserving critical features. Beyond reliable face identification capabilities, the system offers several key advantages: it can process large-scale facial datasets while maintaining low computational overhead through optimized matrix operations. The implementation includes robustness enhancements that enable recognition under varying conditions - different angles, diverse lighting scenarios, and multiple facial expressions. The core MATLAB implementation utilizes built-in functions like pca() for covariance matrix decomposition and k-nearest neighbor classification for matching. Additional features include automated data preprocessing and batch processing capabilities for handling multiple images simultaneously.