PCA Face Recognition using MATLAB

Developed a face recognition system in MATLAB using Principal Component Analysis (PCA) and the Eigenfaces algorithm for dimensionality reduction and facial feature extraction. The project processes grayscale facial images, computes the mean face, generates eigenfaces, projects images into eigenspace, and recognizes faces by comparing Euclidean distances in the reduced feature space. Key Features: • Mean face computation • Eigenface generation and visualization • Face reconstruction from principal components • PCA-based face recognition • Euclidean distance matching The implementation achieved a recognition accuracy of 93.75% on the ORL Face Dataset and demonstrates the application of classical machine learning techniques in computer vision.