Eigenface-Based Face Recognition MATLAB Program

This MATLAB program implements eigenface-based face recognition with detailed Chinese annotations. The core algorithm utilizes Principal Component Analysis (PCA) for dimensionality reduction and feature extraction from facial images. Key components include eigenface generation through covariance matrix calculation, feature vector projection for pattern matching, and adaptive thresholding for classification decisions. The program processes input images through preprocessing stages (normalization and alignment) before performing recognition, with visualization functions to annotate detection results directly on images. Additional features include batch processing capabilities and performance metrics calculation. This implementation serves as an educational tool for understanding computer vision fundamentals and pattern recognition techniques, providing modular code structure for easy experimentation with different parameters and datasets.