 Corresponding author: Gift Adene. Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0. Digital Criminal Biometric Archives (DICA) and Public Facial Recognition System (FRS) for Nigerian criminal investigation using HAAR cascades classifier technique Onyemachi Joshua Ndubuisi 1 , Gift Adene 2, * , Belonwu Tochukwu Sunday 3 , Chinedu Emmanuel Mbonu 3 and Adannaya Uneke Gift-Adene 2 1 Teesside University Middlessbrough, United Kingdom. 2 Akanu Ibiam Federal Polytechnic, Unwana, Nigeria. 3 Nnamdi Azikiwe University, Awka, Nigeria. World Journal of Advanced Engineering Technology and Sciences, 2024, 11(02), 029–043 Publication history: Received on 22 January 2024; revised on 04 February 2024; accepted on 06 February 2024 Article DOI: https://doi.org/10.30574/wjaets.2024.11.2.0077 Abstract In Nigeria, there are many different security concerns and thus crimes have increased despite the fact that there are stringent laws and punishments in place to deter them, making it appear as though the authorities are unable to stop it. In order to identify criminals and conduct investigations, it is imperative that a facial recognition system be connected to a constantly updated digital library. The focus of this paper is to develop an automatic criminal investigation system that can identify criminals based on their faces and produce real-time digital archives about them. However, as an object detection method and facial recognition model, the new system is built on the Haar Cascades Classifier technique in the OpenCV package. Additionally, appropriate programming languages that may provide the needed results were investigated. Python 3.6 was used with the Django 4.2 framework, OpenCV-Python, and Dlib for language execution. Due to Django's ORM, support for numerous databases, and usage of the SQLite3 database, a straightforward database was employed for lightweight applications. The 12 factor app idea was used to construct the DICA-FR system's essential skills. Face detection was applied to the image using the Haar method during processing, and during post-processing, the discovered face was compared with well-known criminal face encodings for matching purposes. Results demonstrated that DICA-FRS could effectively replace human systems since it can recover faces from the furthest distances, display the name of the offender, and sound an alert on the DICA web app's output screen. The DICA system is a working prototype of a system that might be used in the criminal investigative process in Nigeria. Keywords: Crime; Facial Detection System; Criminal Biometrics; Criminal Investigation; Haar Cascades Classifier Technique 1. Introduction Crime is a social canker-worm that has eaten deeply into the Nigerian society's social fabric, having a wide-ranging impact [1]. The functionality of crime in a society like ours must be taken seriously due to the social and psychological issues it has caused many victims to experience, even though [2] believes that crime is an inevitable and normal aspect of social life. Despite the fact that crime serves a purpose in society, committing a crime is nonetheless wrong and undesirable in a society that is functioning well [3]. Armed robbery, theft, assault, burglary, rape, and other popular crimes that were common in Nigeria in the 1970s have now given way to terrorism, bomb blasts, kidnapping, drug trafficking, money laundering, child trafficking, assassinations, and other criminal activities [4]. According to [5], Nigeria has a wide range of security issues, including abduction, terrorism, civil unrest, political violence, fraud, assassination, and armed robbery. Even though there are