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Circular interpolation techniques towards accurate segmentation of iris biometric images for infants

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dc.contributor.author Nelufule, Nthatheni
dc.contributor.author Mabuza-Hocquet, Gugulethu P
dc.contributor.author De Kock, Antonie J
dc.date.accessioned 2021-03-07T18:56:25Z
dc.date.available 2021-03-07T18:56:25Z
dc.date.issued 2020-01
dc.identifier.citation Nelufule, N., Mabuza-Hocquet, G.P. & De Kock, A.J. 2020. Circular interpolation techniques towards accurate segmentation of iris biometric images for infants. http://hdl.handle.net/10204/11838 . en_ZA
dc.identifier.isbn 978-1-7281-4162-6
dc.identifier.isbn 978-1-7281-4163-3
dc.identifier.uri http://hdl.handle.net/10204/11838
dc.description.abstract In most biometric modalities, recognition and authentication methods for adults have already been fully designed, developed and commercially available. However, for infants and children who are the most vulnerable population to abduction, swapping at hospitals and illegal adoption, such technologies are still lacking. Another challenge is that the current commercial devices are accompanied by locked-in software, which makes devices procurement in bulks unaffordable, especially for local governments in developing countries. Achieving recognition using existing algorithms for images acquired from young children also poses a challenge, since the algorithms have been developed with adults in mind. This paper presents part of a bigger project aimed at developing a multimodal biometric system for infants and children as they grow. With a dedicated focus towards iris recognition, this paper proposes an iris detection method using circular Hough transforms with circular interpolation to achieve successful iris segmentation from a database with the youngest infant being six weeks old. The proposed method outperforms the state-of-the-art iris detection algorithms with segmentation accuracy of 98% for the images within our database. en_US
dc.format Abstract en_US
dc.language.iso en en_US
dc.relation.uri DOI: 10.1109/SAUPEC/RobMech/PRASA48453.2020.9041135 untranslated en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9041135 untranslated en_US
dc.source 2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa, South Africa, 29-31 January 2020 en_US
dc.subject Children Biometrics en_US
dc.subject Circular interpolation en_US
dc.subject Hough circles en_US
dc.subject Hough transforms en_US
dc.subject Iris detection en_US
dc.subject Pupil detection en_US
dc.subject Pupil glare removal en_US
dc.title Circular interpolation techniques towards accurate segmentation of iris biometric images for infants en_US
dc.type Conference Presentation en_US
dc.description.pages 6pp en_US
dc.description.note Due to copyright restrictions, the attached PDF file contains the abstract of the full-text item. For access to the full-text item, please consult the publisher's website: https://ieeexplore.ieee.org/document/9041135 en_US
dc.description.cluster Defence and Security
dc.description.impactarea Information Security Centre en_US
dc.description.impactarea Optronic Sensor Systems
dc.identifier.apacitation Nelufule, N., Mabuza-Hocquet, G. P., & De Kock, A. J. (2020). Circular interpolation techniques towards accurate segmentation of iris biometric images for infants. http://hdl.handle.net/10204/11838 en_ZA
dc.identifier.chicagocitation Nelufule, Nthatheni, Gugulethu P Mabuza-Hocquet, and Antonie J De Kock. "Circular interpolation techniques towards accurate segmentation of iris biometric images for infants." <i>2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa, South Africa, 29-31 January 2020</i> (2020): http://hdl.handle.net/10204/11838 en_ZA
dc.identifier.vancouvercitation Nelufule N, Mabuza-Hocquet GP, De Kock AJ, Circular interpolation techniques towards accurate segmentation of iris biometric images for infants; 2020. http://hdl.handle.net/10204/11838 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Nelufule, Nthatheni AU - Mabuza-Hocquet, Gugulethu P AU - De Kock, Antonie J AB - In most biometric modalities, recognition and authentication methods for adults have already been fully designed, developed and commercially available. However, for infants and children who are the most vulnerable population to abduction, swapping at hospitals and illegal adoption, such technologies are still lacking. Another challenge is that the current commercial devices are accompanied by locked-in software, which makes devices procurement in bulks unaffordable, especially for local governments in developing countries. Achieving recognition using existing algorithms for images acquired from young children also poses a challenge, since the algorithms have been developed with adults in mind. This paper presents part of a bigger project aimed at developing a multimodal biometric system for infants and children as they grow. With a dedicated focus towards iris recognition, this paper proposes an iris detection method using circular Hough transforms with circular interpolation to achieve successful iris segmentation from a database with the youngest infant being six weeks old. The proposed method outperforms the state-of-the-art iris detection algorithms with segmentation accuracy of 98% for the images within our database. DA - 2020-01 DB - ResearchSpace DP - CSIR J1 - 2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa, South Africa, 29-31 January 2020 KW - Children Biometrics KW - Circular interpolation KW - Hough circles KW - Hough transforms KW - Iris detection KW - Pupil detection KW - Pupil glare removal LK - https://researchspace.csir.co.za PY - 2020 SM - 978-1-7281-4162-6 SM - 978-1-7281-4163-3 T1 - Circular interpolation techniques towards accurate segmentation of iris biometric images for infants TI - Circular interpolation techniques towards accurate segmentation of iris biometric images for infants UR - http://hdl.handle.net/10204/11838 ER - en_ZA
dc.identifier.worklist 23911 en_US


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