FLD-Based Face Recognition System with Fast Wavelet Transform Implementation

This FLD-based face recognition system demonstrates exceptional performance through its implementation of Fast Wavelet Transform, making it particularly suitable for learning and research applications. The system employs the FLD algorithm for effective facial feature extraction and classification, while integrating Fast Wavelet Transform for optimized feature representation and matching operations. Through this combined approach, the system achieves accurate face identification with high processing efficiency. The implementation typically involves key functions such as wavelet decomposition for multi-resolution analysis, FLD projection for dimensionality reduction, and classification modules using distance metrics like Euclidean or Mahalanobis distance. The learning curve remains relatively gentle due to well-structured code organization and clear separation between preprocessing, feature extraction, and classification stages. For learners interested in face recognition technologies, this system serves as an excellent educational tool that demonstrates practical implementation of computer vision algorithms. We encourage users to fully utilize this system to enhance their capabilities in the field of face recognition technology.