A Systematic Literature Review on Neonatal Fingerprint Recognition
Luiz Fernando Puttow Southier, Gustavo Alexandre Tuchlinowicz Nunes, João Henrique Pereira Machado, Matheus Buratti, PEDRO HENRIQUE DE VIVEIROS TRENTIN, Wesley Augusto Catuzzo de Bona, Barbara de Oliveira Koop, Elioenai M. F. Diniz, João Victor Costa Mazzochin, João Leonardo Harres Dall Agnol, Lucas Caldeira de Oliveira, Marcelo Filipak, Luiz Antonio Zanlorensi Junior, Marcos Paulo Belançon, Jefferson Tales Oliva, Marcelo Teixeira, Dalcimar Casanova · ACM Computing Surveys · 2025
Neonatal biometrics, especially those based on fingerprint traits, can potentially improve early childhood identification with decisive applications in healthcare, identity management, and other critical social domains. Although many biometric approaches to human recognition exist, most of them cannot be directly applied to neonates. The main barrier is the reduced size of children’s biometric traits, which affects image quality as these traits are still developing. Another issue is the lack of child biometric databases, as a periodic recollection of images is a fundamental part of neonatal identification regarding the feasibility evaluation of temporal recognition. Several works can be found in the literature addressing some of these issues. However, there is still no systematic review allowing a general understanding of these solutions, discussing their links, gaps, comparisons, and open challenges. In this sense, this article presents a systematic literature review on neonatal biometrics. In total, 1,878 papers were screened and classified, resulting in 45 being selected to be analyzed in this study. We detail and compare the results of datasets, scanners, methods, and techniques to achieve and improve neonatal recognition. Finally, research trends are identified and discussed based on the main gaps in the literature.