A Complete Face Recognition System Using LBP (Local Binary Pattern)

This article presents a complete face recognition system utilizing Local Binary Pattern (LBP) methodology. The system incorporates key subroutines such as local binarization processing (where each pixel is compared with its neighbors to generate binary patterns) and histogram feature vector calculation (which aggregates LBP codes into statistical distributions representing facial textures). These components work together to extract discriminative facial features and compare them against enrolled face databases. The system architecture allows for testing recognition accuracy by integrating custom face databases, with empirical results confirming exceptionally high recognition rates. Implementation typically involves OpenCV functions like cv2.LBPHFaceRecognizer_create() for classifier training and prediction, with preprocessing steps including face detection and region normalization. With practical applications spanning access control systems, secure payment authentication, and biometric security solutions, this LBP-based framework offers significant potential for enhancing convenience and safety in daily life through reliable face recognition technology.