dc.contributor.author |
Mabuza-Hocquet, Gugulethu P
|
|
dc.contributor.author |
Nelwamondo, Fulufhelo V
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|
dc.contributor.author |
Marwala, T
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|
dc.date.accessioned |
2017-08-22T13:09:09Z |
|
dc.date.available |
2017-08-22T13:09:09Z |
|
dc.date.issued |
2017-03 |
|
dc.identifier.citation |
Mabuza-Hocquet, G., Nelwamondo, F. and Marwala, T. 2017. Ethnicity prediction and classification from iris texture patterns: A survey on recent advances. 2016 International Conference on Computational Science and Computational Intelligence, Las Vegas, NV, USA, 15-17 Dec 2016, p. 818-823. DOI: 10.1109/CSCI.2016.0159 |
en_US |
dc.identifier.isbn |
978-1-5090-5510-4 |
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dc.identifier.uri |
DOI: 10.1109/CSCI.2016.0159
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|
dc.identifier.uri |
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7881452
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|
dc.identifier.uri |
http://hdl.handle.net/10204/9460
|
|
dc.description |
Copyright: 2016 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, kindly consult the publisher's website. |
en_US |
dc.description.abstract |
The prediction and classification of ethnicity based on iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a recent topic in iris biometrics. While the large body of knowledge and research in iris biometrics has been focused on using iris features for individual recognition and verification, very little work has been focused on using iris texture patterns to determine other demographic attributes of individuals such as ethnicity and gender. The aim of this paper is to consolidate most of the work done by researchers, through delving and comparing the different techniques, algorithms and results achieved over the last decade. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE |
en_US |
dc.relation.ispartofseries |
Worklist;19272 |
|
dc.subject |
Iris texture patterns |
en_US |
dc.subject |
Iris ethnic classification |
en_US |
dc.subject |
Iris feature extraction |
en_US |
dc.subject |
Iris textons |
en_US |
dc.title |
Ethnicity prediction and classification from iris texture patterns: A survey on recent advances |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Mabuza-Hocquet, G., Nelwamondo, F. V., & Marwala, T. (2017). Ethnicity prediction and classification from iris texture patterns: A survey on recent advances. IEEE. http://hdl.handle.net/10204/9460 |
en_ZA |
dc.identifier.chicagocitation |
Mabuza-Hocquet, Gugulethu, Fulufhelo V Nelwamondo, and T Marwala. "Ethnicity prediction and classification from iris texture patterns: A survey on recent advances." (2017): http://hdl.handle.net/10204/9460 |
en_ZA |
dc.identifier.vancouvercitation |
Mabuza-Hocquet G, Nelwamondo FV, Marwala T, Ethnicity prediction and classification from iris texture patterns: A survey on recent advances; IEEE; 2017. http://hdl.handle.net/10204/9460 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Mabuza-Hocquet, Gugulethu
AU - Nelwamondo, Fulufhelo V
AU - Marwala, T
AB - The prediction and classification of ethnicity based on iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a recent topic in iris biometrics. While the large body of knowledge and research in iris biometrics has been focused on using iris features for individual recognition and verification, very little work has been focused on using iris texture patterns to determine other demographic attributes of individuals such as ethnicity and gender. The aim of this paper is to consolidate most of the work done by researchers, through delving and comparing the different techniques, algorithms and results achieved over the last decade.
DA - 2017-03
DB - ResearchSpace
DP - CSIR
KW - Iris texture patterns
KW - Iris ethnic classification
KW - Iris feature extraction
KW - Iris textons
LK - https://researchspace.csir.co.za
PY - 2017
SM - 978-1-5090-5510-4
T1 - Ethnicity prediction and classification from iris texture patterns: A survey on recent advances
TI - Ethnicity prediction and classification from iris texture patterns: A survey on recent advances
UR - http://hdl.handle.net/10204/9460
ER - |
en_ZA |