MATLAB Code Implementation for Face Recognition Using PCA Algorithm

In this document, we will discuss the face recognition algorithm and demonstrate its implementation using MATLAB source code. Specifically, we will explore the application of Principal Component Analysis (PCA) in face recognition systems, including how this algorithm trains models using eigenface decomposition to achieve accurate facial identification. The implementation typically involves key MATLAB functions such as pca() for dimensionality reduction and fitcecoc() for multiclass classification. We will also examine common face recognition application scenarios like security systems and facial unlock mechanisms, demonstrating how MATLAB's image processing toolbox (e.g., detectFaceParts() and vision.CascadeObjectDetector) can enhance efficiency and security in these applications. Finally, we will provide resources and references to help readers deepen their understanding of face recognition technology and its practical implementations, including code samples for preprocessing techniques like histogram equalization and facial landmark detection.