Name
Abstract | ||
|---|---|---|
Image degradations can affect the different processing steps of iris recognition systems. With several quality factors proposed for iris images, its specific effect in the segmentation accuracy is often obviated, with most of the efforts focused on its impact in the recognition accuracy. Accordingly, we evaluate the impact of 8 quality measures in the performance of iris segmentation. We use a database acquired with a close-up iris sensor and built-in quality checking process. Despite the latter, we report differences in behavior, with some measures clearly predicting the segmentation performance, while others giving inconclusive results. Recognition experiments with two matchers also show that segmentation and matching performance are not necessarily affected by the same factors. The resilience of one matcher to segmentation inaccuracies also suggest that segmentation errors due to low image quality are not necessarily revealed by the matcher, pointing out the importance of separate evaluation of the segmentation accuracy. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICB.2013.6613016 | Biometrics |
Keywords | Field | DocType |
Q-factor,image matching,image segmentation,iris recognition,built-in quality checking process,close-up iris sensor,image degradations,iris image matching,iris image segmentation,iris recognition systems,quality factors,segmentation errors | Signal processing,Computer vision,Iris recognition,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Image texture,Image quality,Segmentation-based object categorization,Image segmentation,Artificial intelligence | Conference |
ISSN | Citations | PageRank |
2376-4201 | 4 | 0.41 |
References | Authors | |
13 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fernando Alonso-Fernandez | 1 | 531 | 37.65 |
| Josef Bigün | 2 | 876 | 194.07 |
| Alonso-Fernandez, F. | 3 | 4 | 0.41 |