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Image quality assessment for iris biometrics for minors

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dc.contributor.author Nelufule, Nthatheni
dc.date.accessioned 2020-03-19T10:52:37Z
dc.date.available 2020-03-19T10:52:37Z
dc.date.issued 2019-03
dc.identifier.citation Nelufule, N. et al. 2019. Image quality assessment for iris biometrics for minors. In: Information Communication Technology and Society Conference (ICTAS), Blue waters Hotel Durban, 6-8 March 2019 en_US
dc.identifier.isbn 978-1-5386-7365-2
dc.identifier.isbn 978-1-5386-7366-9
dc.identifier.uri https://ieeexplore.ieee.org/document/8703520
dc.identifier.uri 10.1109/ICTAS.2019.8703520
dc.identifier.uri http://www.ictas2019.com/ictas2019_program.pdf
dc.identifier.uri http://hdl.handle.net/10204/11357
dc.description Copyright: 2019 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. en_US
dc.description.abstract Image quality assessment plays an important role in enhancing the performance of pattern recognition systems, including biometric systems. Although, quality assessment methods have been utilized for iris recognition on adults they have not been investigated on iris recognition for children. Iris recognition on children is difficult because of their uncooperative nature and may result in lower quality iris samples. In this study, we applied four existing quality assessment methods, light variation, pupil dilation, off-angle, and pixel count to data we collected from children and the CASIA database with iris images from adults. The results indicate that once the image without any visible iris area are removed, using an automated process, then the remaining images for children produces similar quality assessment distributions as those of iris images from adults. This study is the first step in creating an iris recognition system for children. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Workflow;22086
dc.subject Children biometric en_US
dc.subject Image quality en_US
dc.subject Iris features en_US
dc.subject Iris recognition en_US
dc.subject Occlusion en_US
dc.subject Quality assessment en_US
dc.title Image quality assessment for iris biometrics for minors en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Nelufule, N. (2019). Image quality assessment for iris biometrics for minors. IEEE. http://hdl.handle.net/10204/11357 en_ZA
dc.identifier.chicagocitation Nelufule, Nthatheni. "Image quality assessment for iris biometrics for minors." (2019): http://hdl.handle.net/10204/11357 en_ZA
dc.identifier.vancouvercitation Nelufule N, Image quality assessment for iris biometrics for minors; IEEE; 2019. http://hdl.handle.net/10204/11357 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Nelufule, Nthatheni AB - Image quality assessment plays an important role in enhancing the performance of pattern recognition systems, including biometric systems. Although, quality assessment methods have been utilized for iris recognition on adults they have not been investigated on iris recognition for children. Iris recognition on children is difficult because of their uncooperative nature and may result in lower quality iris samples. In this study, we applied four existing quality assessment methods, light variation, pupil dilation, off-angle, and pixel count to data we collected from children and the CASIA database with iris images from adults. The results indicate that once the image without any visible iris area are removed, using an automated process, then the remaining images for children produces similar quality assessment distributions as those of iris images from adults. This study is the first step in creating an iris recognition system for children. DA - 2019-03 DB - ResearchSpace DP - CSIR KW - Children biometric KW - Image quality KW - Iris features KW - Iris recognition KW - Occlusion KW - Quality assessment LK - https://researchspace.csir.co.za PY - 2019 SM - 978-1-5386-7365-2 SM - 978-1-5386-7366-9 T1 - Image quality assessment for iris biometrics for minors TI - Image quality assessment for iris biometrics for minors UR - http://hdl.handle.net/10204/11357 ER - en_ZA


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