dc.contributor.author |
Mabuza-Hocquet, Gugulethu P
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|
dc.contributor.author |
Nelwamondo, Fulufhelo V
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|
dc.date.accessioned |
2016-01-26T07:03:23Z |
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dc.date.available |
2016-01-26T07:03:23Z |
|
dc.date.issued |
2015-12 |
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dc.identifier.citation |
Mabuza-Hocquet, G and Nelwamondo, F. 2015. Fusion of phase congruency and harris algorithm for extraction of iris corner points. In: Third International Conference on Artificial Intelligence, Modelling and Simulation, Malaysia, Sabah, Kota Kinabalu, Le Meridien Hotel, December 2015 |
en_US |
dc.identifier.isbn |
978-1-4673-8675-3 |
|
dc.identifier.uri |
http://uksim.info/aims2015/CD/data/8675a315.pdf
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|
dc.identifier.uri |
http://hdl.handle.net/10204/8373
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|
dc.description |
Third International Conference on Artificial Intelligence, Modelling and Simulation, Malaysia, Sabah, Kota Kinabalu, Le Meridien Hotel, December 2015. 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 |
Iris recognition uses automated techniques to extract iris features which are stored in a database as a feature template to be later used for individual identification and authentication. Strict image quality control is a basic requirement for most iris identification systems. Low cost devices used under uncontrolled environments acquire poor iris images with inconsistent illumination and specular reflections. These factors inflict challenges towards the accurate identification and extraction of reliable iris features. This work proposes a fusion of Phase congruency and Harris algorithm to detect corner features found within the arrangement of iris patterns. This fusion produces a feature vector with the exact location of corner features that are not only congruent in phase but are also invariant to illumination and rotation. Results of the proposed approach are tested on two non-ideal databases and obtain an accurate match rate of 99.9% while producing a feature template of 512 bits that requires low storage space. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE Xplore |
en_US |
dc.relation.ispartofseries |
Workflow;16047 |
|
dc.subject |
Phase congruency |
en_US |
dc.subject |
Harris corner detector |
en_US |
dc.subject |
Iris segmentation |
en_US |
dc.subject |
Chan-Vese algorithm |
en_US |
dc.subject |
Feature extraction |
en_US |
dc.title |
Fusion of phase congruency and harris algorithm for extraction of iris corner points |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Mabuza-Hocquet, G. P., & Nelwamondo, F. V. (2015). Fusion of phase congruency and harris algorithm for extraction of iris corner points. IEEE Xplore. http://hdl.handle.net/10204/8373 |
en_ZA |
dc.identifier.chicagocitation |
Mabuza-Hocquet, Gugulethu P, and Fulufhelo V Nelwamondo. "Fusion of phase congruency and harris algorithm for extraction of iris corner points." (2015): http://hdl.handle.net/10204/8373 |
en_ZA |
dc.identifier.vancouvercitation |
Mabuza-Hocquet GP, Nelwamondo FV, Fusion of phase congruency and harris algorithm for extraction of iris corner points; IEEE Xplore; 2015. http://hdl.handle.net/10204/8373 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Mabuza-Hocquet, Gugulethu P
AU - Nelwamondo, Fulufhelo V
AB - Iris recognition uses automated techniques to extract iris features which are stored in a database as a feature template to be later used for individual identification and authentication. Strict image quality control is a basic requirement for most iris identification systems. Low cost devices used under uncontrolled environments acquire poor iris images with inconsistent illumination and specular reflections. These factors inflict challenges towards the accurate identification and extraction of reliable iris features. This work proposes a fusion of Phase congruency and Harris algorithm to detect corner features found within the arrangement of iris patterns. This fusion produces a feature vector with the exact location of corner features that are not only congruent in phase but are also invariant to illumination and rotation. Results of the proposed approach are tested on two non-ideal databases and obtain an accurate match rate of 99.9% while producing a feature template of 512 bits that requires low storage space.
DA - 2015-12
DB - ResearchSpace
DP - CSIR
KW - Phase congruency
KW - Harris corner detector
KW - Iris segmentation
KW - Chan-Vese algorithm
KW - Feature extraction
LK - https://researchspace.csir.co.za
PY - 2015
SM - 978-1-4673-8675-3
T1 - Fusion of phase congruency and harris algorithm for extraction of iris corner points
TI - Fusion of phase congruency and harris algorithm for extraction of iris corner points
UR - http://hdl.handle.net/10204/8373
ER -
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en_ZA |