Law Enforcement Facial Recognition System for Crime

Facial recognition technology is used by police enforcement to identify offenders and find missing people. This paper describes a law enforcement facial recognition system that detects and recognizes faces using the Local Binary Pattern Histogram (LBPH) and the Haar Cascade Classifier. The system's simple Tkinter-based graphical user interface (GUI) enables authorized workers to register photographs of offenders and missing people, analyse images, and process films for facial recognition. To offer best data handling and storage, the system is built with Python (Tkinter), PHP, MySQL (phpMyAdmin), and OpenCV. The results aid in correct identification by projecting the confidence level for facial matches. Future developments will incorporate real-time video processing and deep learning approaches to improve accuracy. Keywords: Facial Recognition, Law Enforcement, Criminal Identification, Missing Person Detection, Local Binary Pattern Histogram (LBPH), Haar Cascade Classifier, Image Processing, Video Analysis, Tkinter GUI, OpenCV, Machine Learning, Face Detection, Database Management, Security and Surveillance, Pattern Recognition.