Abstract
A new iris recognition method based on a robust iris segmentation approach is presented in this paper for improving iris recognition performance. The robust iris segmentation approach applies power-law transformations for more accurate detection of the pupil region, which significantly reduces the candidate limbic boundary search space for increasing detection accuracy and efficiency. The limbic circle having a centre within close range of the pupil centre is selectively detected, and the eyelid detection approach thus leads to improved iris recognition performance. Experiments using the Iris Challenge Evaluation (ICE) database show the effectiveness of the proposed method.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 56-76 |
| Number of pages | 21 |
| Journal | International Journal of Biometrics |
| Volume | 4 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2012 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics
Keywords
- Biometrics
- ICE
- Iris challenge evaluation
- Iris recognition
- Iris segmentation
- Power-law transformations