Securing Identity from Birth: Biometric Fingerprint Algorithms For Robust Childbirth Registration in Ghana

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dc.contributor.authorBonney, Joseph
dc.contributor.authorPatel, Warish
dc.contributor.authorPatel, Monal
dc.contributor.authorKoyuncu, Hakan
dc.date.accessioned2025-09-22T12:02:59Z
dc.date.available2025-09-22T12:02:59Z
dc.date.issued2025
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractGhana faces persistent challenges in achieving universal birth registration, especially in rural and underserved communities. Traditional paper-based systems remain prone to loss, fraud, and inefficiencies, leaving many children without legal identity and limiting access to critical services such as healthcare and education. This study presents a biometric fingerprint-based childbirth registration system tailored for infants and mothers, designed to integrate with Ghana's national identity framework (Ghana Card). Using a convolutional neural network (CNN)-based fingerprint matching algorithm, our system achieved an identification accuracy of 86.7% for maternal-infant linking during controlled field testing in a selected Chps zone in Aburi, Akwapim South Municipality in the Eastern region in Ghana. The findings demonstrate that early-stage biometric data collection is feasible and reliable within low-resource settings. Ethical consent, data protection, and system misuse were addressed through community engagement protocols and adherence to Ghana's Data Protection Act. The results indicate that implementing a secure biometric registration system can significantly strengthen identity management in Ghana. The study’s primary contribution lies in the development and testing of a context-sensitive biometric algorithm that addresses both technological and infrastructural limitations, offering a scalable and secure model to help Ghana meet Sustainable Development Goal 16.9: ensuring legal identity for all, including birth registration.
dc.identifier.citationBonney, J., Patel, W., Patel, M., & Koyuncu, H. (2025). Securing Identity from Birth: Biometric Fingerprint Algorithms For Robust Childbirth Registration in Ghana. International Journal of Environmental Sciences, 11(6), 1777-1788. 10.64252/vf8aqv05
dc.identifier.doi10.64252/vf8aqv05
dc.identifier.endpage1788
dc.identifier.issn2229-7359
dc.identifier.issue6
dc.identifier.scopus2-s2.0-105014275620
dc.identifier.scopusqualityQ3
dc.identifier.startpage1777
dc.identifier.urihttps://hdl.handle.net/20.500.12939/5944
dc.identifier.volume11
dc.indekslendigikaynakScopus
dc.institutionauthorKoyuncu, Hakan
dc.language.isoen
dc.publisherAcademic Science Publications and Distributions
dc.relation.ispartofInternational Journal of Environmental Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBiometric fingerprint recognition
dc.subjectBirth registration
dc.subjectChild identity management
dc.subjectConvolutional Neural Network (CNN)
dc.subjectData protection
dc.subjectGhana Card integration
dc.subjectInfant biometric authentication
dc.subjectLow-resource settings
dc.subjectMaternal-infant linking
dc.subjectSustainable Development Goal 16.9
dc.titleSecuring Identity from Birth: Biometric Fingerprint Algorithms For Robust Childbirth Registration in Ghana
dc.typeArticle

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