Face Recognition and Crime Detection

Abstract

Face recognition has emerged as a pivotal technology in the fields of security and law enforcement. This project explores the integration of face recognition systems with crime detection databases to identify suspects, repeat offenders, and missing individuals in real-time. By leveraging advanced machine learning and deep learning techniques—particularly Convolutional Neural Networks (CNNs)—the system captures and compares facial features against a known criminal database. The proposed solution aims to enhance surveillance systems, reduce manual investigation efforts, and support authorities in proactive crime prevention. With high accuracy and real-time identification capabilities, face recognition can revolutionize modern policing and contribute significantly to public safety