| dc.contributor.author | Ayu Fitrie Haziqah, Sallehuddin | |
| dc.contributor.author | Muhammad Imran, Ahmad | |
| dc.contributor.author | Ruzelita, Ngadiran | |
| dc.contributor.author | Mohd Nazrin, Md Isa | |
| dc.date.accessioned | 2019-12-03T04:23:24Z | |
| dc.date.available | 2019-12-03T04:23:24Z | |
| dc.date.issued | 2016 | |
| dc.identifier.citation | Journal of Telecommunication, Electronic and Computer Engineering, vol.8(4), 2016, 133-138 | en_US |
| dc.identifier.issn | 2180–1843 | |
| dc.identifier.issn | 2289-8131 (online) | |
| dc.identifier.uri | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/63563 | |
| dc.description | Link to publisher's homepage at http://journal.utem.edu.my | en_US |
| dc.description.abstract | The uniqueness of iris texture makes it one of the reliable physiological biometric traits compare to the other biometric traits. In this paper, we investigate a different level of fusion approach in iris image. Although, a number of iris recognition methods has been proposed in recent years, however most of them focus on the feature extraction and classification method. Less number of method focuses on the information fusion of iris images. Fusion is believed to produce a better discrimination power in the feature space, thus we conduct an analysis to investigate which fusion level is able to produce the best result for iris recognition system. Experimental analysis using CASIA dataset shows feature level fusion produce 99% recognition accuracy. The verification analysis shows the best result is GAR = 95% at the FRR = 0.1%. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Universiti Teknikal Malaysia Melaka | en_US |
| dc.subject | Biometric system | en_US |
| dc.subject | Iris recognition | en_US |
| dc.subject | Information fusion | en_US |
| dc.title | A survey of iris recognition system | en_US |
| dc.type | Article | en_US |
| dc.identifier.url | journal.utem.edu.my/index.php/jtec/article/view/1188 | |
| dc.contributor.url | m.imran@unimap.edu.my | |
