Ntshangase, Cynthia SBaruni, Kedimotse PHolder, Ross PDe Kock, Antonie JKhumalo, Lethukuthula PChossa, Bheki2025-07-072025-07-072025http://hdl.handle.net/10204/14274The world is getting transformed by digital technologies to ensure balanced development. Likewise, the challenges introduced by the presence of these technologies are increasing. This includes the problem of the unavailability of digital biometric systems that can be used to verify the identity of children from birth to adulthood. This problem is caused by factors such as children’s biometric traits not being fully developed as those of adults and difficulty capturing high-quality biometrics from children using traditional systems. To solve this problem, this study proposes an age-weighted feature matching algorithm that fuses multiple biometric modalities. The system aims to improve the accuracy of identity verification for children. Experimental results show that the proposed multi-modal system, with the age-weighted algorithm, maintains higher recognition rates compared to individual biometrics. The Equal Error Rate (EER) for the multi-modal system without age-weighting is 14.07%, compared to 12.65% with age-weighting applied, indicating a higher successful recognition rate with fewer wrong matches or failures to match. In comparison, the EER for ear recognition is 57.56%, for fingerprint recognition is 32.17%, and for iris recognition is 37.76%, all of which are significantly higher than the combined multi-modal system, indicating lower recognition rates when singular biometric modalities are used. These findings emphasize the system’s potential to contribute meaningfully to applications such as birth registration, healthcare, and child protection—domains where robust and inclusive identity systems are urgently needed for children.FulltextenMulti-Modal BiometricsDigital technologiesChildren's biometric traitsDigital biometric systemsIris recognitionFingerprint recognitionConference PresentationN/A