Name
Abstract | ||
|---|---|---|
Iris segmentation is one of the complex research areas, as human eyes contain intricate details and are difficult to process. Due to the advancement of technology, security based application employ biometrics to ensure the identity of an individual. Though fingerprint is the commonly utilized biometric, iris is the most promising biometric. However, extracting the iris is not a simple task and the iris recognition accuracy depends on the effectiveness of the iris segmentation. Taking this statement into account, this work proposes a reliable iris segmentation algorithm which is based on SuperPixel Segmentation (SPS). Initially, the eyelids and pupil of the eye image are detected. This is followed by the segmentation of iris. The proposed approach is applied over four benchmark datasets such as CASIA iris V1, V2, V3 and Ubiris V2 databases. The performance of the proposed iris segmentation algorithm is compared with the existing techniques. The proposed segmentation algorithm proves its stability in all the datasets with respect to segmentation accuracy, sensitivity and specificity. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.cogsys.2018.09.029 | Cognitive Systems Research |
Keywords | Field | DocType |
Iris segmentation,Pupil detection,Iris detection | Iris recognition,Segmentation,Pupil,Algorithm,Psychology,Fingerprint,Biometrics,Superpixel segmentation | Journal |
Volume | ISSN | Citations |
57 | 1389-0417 | 1 |
PageRank | References | Authors |
0.35 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| N. Susitha | 1 | 1 | 0.35 |
| Ravi Subban | 2 | 7 | 1.59 |