dc.contributor.author |
Mabuza-Hocquet, Gugulethu P
|
|
dc.contributor.author |
Nelwamondo, Fulufhelo V
|
|
dc.date.accessioned |
2012-10-26T09:58:46Z |
|
dc.date.available |
2012-10-26T09:58:46Z |
|
dc.date.issued |
2012-10 |
|
dc.identifier.citation |
Mabuza, GP and Nelwamondo, FV. Iris image enhancement for feature recognition and extraction. 4th CSIR Biennial Conference: Real problems relevant solutions, CSIR, Pretoria, 9-10 October 2012 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/10204/6230
|
|
dc.description |
4th CSIR Biennial Conference: Real problems relevant solutions, CSIR, Pretoria, 9-10 October 2012 |
en_US |
dc.description.abstract |
Poor digital iris images prove to be a challenge when iris features have to be recognised and extracted for use in iris classification. To ensure the accuracy of a typical iris recognition system, acquired
iris images have to undergo a process called pre-processing by employing enhancement algorithms. The purpose of this work is:
(a) to be able to extricate the best suited enhancement technique that will display the articulated iris features and patterns for efficient extraction; and (b) to use the best enhanced images as a directive towards the development of an algorithm that will simulate the change of the different patterns and features by measuring the boundaries between them. This work explores image enhancement in the spatial domain by using three enhancement techniques namely: (i) local histogram equalisation, (ii) global histogram equalisation and (iii) partial contrast, to improve the quality of iris images from three different iris databases. |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
Iris |
en_US |
dc.subject |
Iris classification |
en_US |
dc.subject |
Iris recognition |
en_US |
dc.subject |
User authentication |
en_US |
dc.subject |
Image enhancement |
en_US |
dc.subject |
Feature recognition |
en_US |
dc.title |
Iris image enhancement for feature recognition and extraction |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Mabuza, G., & Nelwamondo, F. V. (2012). Iris image enhancement for feature recognition and extraction. http://hdl.handle.net/10204/6230 |
en_ZA |
dc.identifier.chicagocitation |
Mabuza, GP, and Fulufhelo V Nelwamondo. "Iris image enhancement for feature recognition and extraction." (2012): http://hdl.handle.net/10204/6230 |
en_ZA |
dc.identifier.vancouvercitation |
Mabuza G, Nelwamondo FV, Iris image enhancement for feature recognition and extraction; 2012. http://hdl.handle.net/10204/6230 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Mabuza, GP
AU - Nelwamondo, Fulufhelo V
AB - Poor digital iris images prove to be a challenge when iris features have to be recognised and extracted for use in iris classification. To ensure the accuracy of a typical iris recognition system, acquired
iris images have to undergo a process called pre-processing by employing enhancement algorithms. The purpose of this work is:
(a) to be able to extricate the best suited enhancement technique that will display the articulated iris features and patterns for efficient extraction; and (b) to use the best enhanced images as a directive towards the development of an algorithm that will simulate the change of the different patterns and features by measuring the boundaries between them. This work explores image enhancement in the spatial domain by using three enhancement techniques namely: (i) local histogram equalisation, (ii) global histogram equalisation and (iii) partial contrast, to improve the quality of iris images from three different iris databases.
DA - 2012-10
DB - ResearchSpace
DP - CSIR
KW - Iris
KW - Iris classification
KW - Iris recognition
KW - User authentication
KW - Image enhancement
KW - Feature recognition
LK - https://researchspace.csir.co.za
PY - 2012
T1 - Iris image enhancement for feature recognition and extraction
TI - Iris image enhancement for feature recognition and extraction
UR - http://hdl.handle.net/10204/6230
ER - |
en_ZA |