Leveraging Facial Recognition Technology in Criminal Identification

Abstract

Detecting and identifying a criminal is a time-consuming and complex task. Criminals have become more astute in recent years, leaving no genetic evidence or fingerprint traces at the crime site. Using state-of-the-art facial identification technology is a quick and simple option. Surveillance cameras are being deployed at most buildings and traffic signals for monitoring reasons, thanks to advancements in security technology. Perpetrators, offenders, runaways, and lost individuals can all be identified using the camera's video recordings. This article aims to provide a brief survey of current improvements in face recognition, as well as a complete overview of several approaches to incorporating face detection in criminal identification based on various application scenarios. We also look at the evolution of facial recognition and where it is now in this study. It gives an overview of the internal architecture of a typical face detection system. It also highlights the obstacles that will be faced in instilling facial recognition as well as approaches to improve it while taking various trade-offs into account. It also identifies areas for future research in the incorporation of facial identification in a variety of sectors.

Keywords: machine learning, face recognition, neural networks, criminal identification, CCTV