Complete Face Detection and Recognition System Source Code in MATLAB

This article presents a comprehensive MATLAB-based source code implementation for a complete face detection and recognition system. The system provides users with practical tools for performing both face detection and identification tasks. The source code demonstrates how to implement core computer vision functionalities within the MATLAB environment, utilizing key image processing techniques and pattern recognition algorithms. The implementation includes essential functions and algorithms such as Haar cascade classifiers for face detection, PCA (Principal Component Analysis) for feature extraction, and machine learning approaches for recognition. Users can study the code structure to understand how to preprocess facial images, extract distinguishing features, and implement classification mechanisms. The modular design allows easy comprehension and execution, with each component clearly documented for educational purposes. Researchers and developers can leverage this codebase to explore advanced topics in facial recognition technology, with flexibility to modify parameters, integrate additional algorithms, or extend functionality for specific applications. This serves as a valuable resource for students, researchers, and practitioners interested in computer vision and biometric identification systems. The codebase emphasizes practical implementation aspects including image preprocessing techniques, feature vector computation, and classification accuracy optimization. Users can experiment with different dataset configurations and algorithm parameters to enhance system performance or adapt the solution to specific recognition scenarios.