CRIMINAL FACE IDENTIFICATION USING MACHINE LEARNING

This paper presents a Face Recognition System for Criminal Detection aimed at enhancing law enforcement capabilities through automated face recognition technology. The system utilizes Haar Cascade for robust face detection and Local Binary Patterns Histogram (LBPH) for accurate and efficient recognition, enabling real-time identification of individuals. Developed using Python and OpenCV, the project offers features such as criminal registration, profile management, and image-based surveillance, ensuring a comprehensive solution. The system demonstrates significant potential for deployment in real-world scenarios, addressing challenges in criminal identification while paving the way for future enhancements like video surveillance and integration with advanced machine learning techniques. Keywords— Face Recognition, Haar Cascade Classifier, Local Binary Patterns Histogram, OpenCV, Image Surveillance, Criminal Identification.