| 1 | Title of the Article | Feature Extraction Techniques for Iris Recognition System: A Survey |
| 2 | Author's name | Adekunle, Y.A.: Computer Science Department, Babcock University, Ilishan-Remo, Nigeria. |
| 3 | Author's name | Aiyeniko, O.*, Eze, M.O., Alao, O.D. |
| 4 | Subject | Compter Science |
| 5 | Keyword(s) | Biometrics, Computer vision, Feature extraction, Pattern recognition. |
| 6 | Abstract | The extraction of features involves the method of converting the original pixel values of an image to more meaningful, useful and measurable information that can be used in other techniques, such as image processing, pattern recognition and machine learning. The feature extraction plays a predominant role in iris recognition in which also the recognition rate is determined. The effective recognition accuracy, reduction of misclassification of two iris templates mostly depends on feature extraction techniques. An efficient iris recognition system requires that the discriminating information presents in an iris pattern to be accurately obtained. This paper performed a literature review on different techniques of feature extraction of iris recognition. The recommendation was made on how these techniques can be further enhanced to produce an effective iris recognition system. |
| 7 | Publisher | Innovative Research Publication |
| 8 | Journal Name; vol., no. | International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-8 Issue-2 |
| 9 | Publication Date | March 2020 |
| 10 | Type | Peer-reviewed Article |
| 11 | Format | |
| 12 | Uniform Resource Identifier | https://ijircst.org/view_abstract.php?title=Feature-Extraction-Techniques-for-Iris-Recognition-System:-A-Survey&year=2020&vol=8&primary=QVJULTM4MQ== |
| 13 | Digital Object Identifier(DOI) | 10.21276/ijircst.2020.8.2.5 https://doi.org/10.21276/ijircst.2020.8.2.5 |
| 14 | Language | English |
| 15 | Page No | 37-42 |