The Evolution of Forensic Facial Recognition: From Anthropometry to Multimodal Biometric Systems

Abstract

Forensic facial recognition is a crucial tool in contemporary investigations, benefiting from technological advancements that standardize and improve forensic processes for law enforcement agencies. Unlike other biometric applications, errors in facial recognition can have serious consequences, necessitating robust solutions tailored to the unique challenges of forensic contexts. This review provides a thorough examination of the evolution, challenges, and ethical considerations surrounding forensic facial recognition technology. It traces the development of technology from early anthropometric methods to modern deep learning approaches, and discusses the technical aspects and limitations of automated facial recognition systems. Furthermore, it discusses the legal landscape in India regarding automated facial recognition, highlighting important legislative provisions and their implications. The review also covers traditional and modern forensic methods, showcasing the shift from physical traits-based identification to multimodal biometric systems. Various applications of automated facial recognition, such as digital documentation, airport operations, and law enforcement initiatives, are explored to demonstrate the wide-ranging utility of this technology. In summary, this review offers a comprehensive analysis of forensic facial recognition, providing insights into its current status, challenges, and future directions.