Real-Time Face Detection and LBPH-Based Face Recognition on Raspberry Pi with OpenCV

Abstract

This paper presents a practical end-to-end project demonstrating real-time face recognition using a Raspberry Pi and OpenCV. consisting of three main stages: training the recognizer, real-time recognition, and face detection and data gathering. —the project offers a comprehensive guide for enthusiasts venturing into computer vision and facial recognition. Employing the Haar Cascade classifier for accurate face detection and the LBPH (Local Binary Patterns Histograms) Face Recognizer for robust training and recognition, the project ensures a thorough understanding of key concepts. The step-by-step process covers software installation, camera testing, face detection, data collection, training, and real-time recognition. With a focus on the Raspberry Pi platform, this project serves as an accessible entry point for exploring facial recognition technology. Readers will gain insights into practical implementation, making it an ideal resource for learners and hobbyists interested in delving into the exciting realm of computer vision.