Face Recognition Program with PCA-SVM Algorithm Implementation

This text discusses a face recognition program with visible source code, highlighting its high-precision recognition capabilities achieved through the PCA-SVM algorithm. The implementation typically involves Principal Component Analysis (PCA) for feature dimensionality reduction and Support Vector Machine (SVM) for classification, which significantly enhances recognition accuracy. Notably, face recognition technology holds broad application prospects in today's information era. For instance, in security applications, this technology can assist law enforcement in identifying suspects through facial feature extraction and matching algorithms. In the financial sector, face recognition serves as an authentication mechanism, implementing biometric verification to enhance user account security through real-time facial detection and verification functions. Therefore, continuously improving the accuracy and stability of face recognition technology remains a critical focus for future development, requiring ongoing optimization of classification algorithms and feature extraction methods.