Circular Interpolation Techniques towards Accurate Segmentation of Iris Biometric Images for Infants

Nelufule, Norman; Mabuza-Hocquet, Gugulethu; Kock, Anton De

doi:10.1109/saupec/robmech/prasa48453.2020.9041135

Cited by 3 publications

(1 citation statement)

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“…The analysis was based on three age groups. This is the same approach described in [11]- [13]. In 2021, Das et al [14] also conducted a longitudinal collection of iris data from children aged four (4) to 11 (11) years over three years.…”

Section: Related Workmentioning

confidence: 99%

Infant Biometric Data Acquisitions: The Lessons Learnt

Nelufule¹,

Moolla²,

Ntshangase³

et al. 2023

Preprint

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Collecting relevant data is an important aspect in allowing evaluation of the performance of systems, methods, algorithms, and techniques developed in the research process. Researchers at the South African Scientific and Industrial Research Council perfoemd a study to identify biometric(s) that can be used to identify and verify young children from birth to 16 years old. Three types of biometrics were considered in this study as a resukt of a comprehensive preliminary research, namely, fingerprins, iris and ear shap. This paper presents challenges identified and lessons learned during the in trying to collect data for scientific research that require interaction with children of different ages and their parents in different environments. . The study is primarily based on researcher’s experiences. Some of the discussion points discussed are of global relevance to children and general human beings, while others relate to South Africa in particular. The discussion aims to share knowledge and experience, hoping that this will help researchers prepare for a trouble-free child data collection process in the future. Keywords: Baby biometrics; long-term data collection, baby fingerprints, baby iris, baby ears

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Section: Related Workmentioning

confidence: 99%