Please use this identifier to cite or link to this item: https://doi.org/10.1049/iet-cvi.2010.0133
DC FieldValue
dc.titleIris matching using multi-dimensional artificial neural network
dc.contributor.authorFarouk, R.M.
dc.contributor.authorKumar, R.
dc.contributor.authorRiad, K.A.
dc.date.accessioned2014-06-17T02:54:20Z
dc.date.available2014-06-17T02:54:20Z
dc.date.issued2011-05
dc.identifier.citationFarouk, R.M., Kumar, R., Riad, K.A. (2011-05). Iris matching using multi-dimensional artificial neural network. IET Computer Vision 5 (3) : 178-184. ScholarBank@NUS Repository. https://doi.org/10.1049/iet-cvi.2010.0133
dc.identifier.issn17519632
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/56416
dc.description.abstractIris recognition is one of the most widely used biometric technique for personal identification. This identification is achieved in this work by using the concept that, the iris patterns are statistically unique and suitable for biometric measurements. In this study, a novel method of recognition of these patterns of an iris is considered by using a multi-dimensional artificial neural network. The proposed technique has the distinct advantage of using the entire resized iris as an input at once. It is capable of excellent pattern recognition properties as the iris texture is unique for every person used for recognition. The system is trained and tested using two publicly available databases (CASIA and UBIRIS). The proposed approach shows significant promise and potential for improvements, compared with the other conventional matching techniques with regard to time and efficiency of results. © 2011 The Institution of Engineering and Technology.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1049/iet-cvi.2010.0133
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1049/iet-cvi.2010.0133
dc.description.sourcetitleIET Computer Vision
dc.description.volume5
dc.description.issue3
dc.description.page178-184
dc.identifier.isiut000290852700004
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

20
checked on Jan 20, 2022

WEB OF SCIENCETM
Citations

14
checked on Jan 20, 2022

Page view(s)

145
checked on Jan 20, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.