Feature Extraction and Recognition in Face Recognition Systems

I previously developed a MATLAB-based face recognition program that implements feature extraction algorithms and performs identity verification by comparing extracted features against pre-stored biometric data. The system employs computer vision techniques including facial landmark detection, dimensionality reduction methods like PCA (Principal Component Analysis) for feature compression, and similarity measurement algorithms for matching. This practical solution can be adapted for various security applications such as surveillance systems, access control mechanisms, and identity verification platforms. The modular code structure allows for customization and optimization of parameters like threshold settings, feature vector dimensions, and classification algorithms to improve recognition accuracy and computational performance. The implementation demonstrates core computer vision concepts while providing a functional foundation for real-world face recognition applications.