LBP-Based Face Recognition Implementation

Face recognition system implemented using the open-source Yale face database, employing Local Binary Patterns (LBP) for facial feature extraction and K-Nearest Neighbors algorithm for classifying facial feature vectors, achieving approximately 90% recognition accuracy with excellent performance results.

K-Nearest Neighbor Algorithm MATLAB Implementation with Source Code

MATLAB source code for K-Nearest Neighbor (KNN) algorithm with test data, suitable for both multi-class and binary classification problems. The implementation uses the popular Iris dataset for validation, demonstrating exceptional classification accuracy reaching 98%. The code implements core KNN functionality including distance calculation, neighbor selection, and majority voting classification.