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Fusion of phase congruency and harris algorithm for extraction of iris corner points

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dc.contributor.author Mabuza-Hocquet, Gugulethu P
dc.contributor.author Nelwamondo, Fulufhelo V
dc.date.accessioned 2016-01-26T07:03:23Z
dc.date.available 2016-01-26T07:03:23Z
dc.date.issued 2015-12
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
dc.identifier.uri http://hdl.handle.net/10204/8373
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 - en_ZA


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