Toward Digitalization: A Secure Approach to Find a Missing Person Using Facial Recognition Technology
Abid Faisal Ayon, S M Maksudul Alam
TL;DR
The paper addresses the challenge of securely locating missing persons using facial recognition on a centralized digital platform. It proposes a dual-database, cross-directory architecture with police-verified administrative processing and a stepwise algorithm for input verification, encoding, cross-matching, and notifications. Key contributions include robust security against intruders, flexible stakeholder support, and real-time notifications, along with a cross-directory matching mechanism that scales to large datasets. The work demonstrates high-accuracy facial-recognition matching (99.38%) and discusses future plans for distributed deployment, immutable identities, and aging-aware recognition, highlighting practical impact for case handling and public safety.
Abstract
Facial Recognition is a technique, based on machine learning technology that can recognize a human being analyzing his facial profile, and is applied in solving various types of realworld problems nowadays. In this paper, a common real-world problem, finding a missing person has been solved in a secure and effective way with the help of facial recognition technology. Although there exist a few works on solving the problem, the proposed work is unique with respect to its security, design, and feasibility. Impeding intruders in participating in the processes and giving importance to both finders and family members of a missing person are two of the major features of this work. The proofs of the works of our system in finding a missing person have been described in the result section of the paper. The advantages that our system provides over the other existing systems can be realized from the comparisons, described in the result summary section of the paper. The work is capable of providing a worthy solution to find a missing person on the digital platform.