
Precise pupil features detection is an important factor for screening diabetic retinopathy. Some interferences caused by reflections, eyelashes and eyelids in pupil extraction need to be solved. This paper presents an algorithm to precisely estimate pupil features: pupil center and pupil radius. The system's hardware component allows for high frame rate image acquisition under infrared lighting conditions. We use several real time image processing techniques to estimate the pupil size under the influence of corneal reflection and eyelid occlusion conditions. The experimental results show a good robustness and accuracy.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 10 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
