Reliability of Automatic Biometric Iris Recognition after Phacoemulsification or Drug-Induced Pupil Dilation

Iris recognition under the influence of diabetes

In this study, iris recognition under the influence of diabetes was investigated. A new database containing 1318 pictures from 343 irides – 546 images from 162 healthy irides (62% female users, 38% male users, 21% <20 years old, 61% (20) < 40 years old, 12% (40) <60 years old and 6% more than 60 years old) and 772 iris images from 181 diabetic eyes but with a clearly visible iris pattern (80% female users, 20% male users, 1% <20 years old, 17.5% (20) <40 years old, 46.5% (40) <60 years old and 35% more than 60 years old) – were collected. All of the diabetes-affected eyes had clearly visible iris patterns without any visible impairments and only type II diabetic patients with at least 2 years of being diabetic were considered for the investigation. Three different open source iris recognition codes and one commercial software development kit were used for achieving the iris recognition system’s performance evaluation results under the influence of diabetes. For statistical analysis, the t-test and the Kolmogorov-Simonov test were used.

Phacoemulsification Cataract Surgery Affects the Discriminative Capacity of Iris Pattern Recognition

Cataract is a common ophthalmic disorder and the leading cause of blindness worldwide. While cataract is cured via surgical procedures, its impact on iris based biometric recognition has not been effectively studied. The key objective of this research is to assess the effect of cataract surgery on the iris texture pattern as a means of personal authentication. We prepare and release the IIITD Cataract Surgery Database (CaSD) captured from 132 cataract patients using three commercial iris sensors. A non-comparative non-randomized cohort study is performed on the iris texture patterns in CaSD and authentication performance is studied using three biometric recognition systems. Performance is lower when matching pre-operative images to post-operative images (74.69 ± 9.77%) as compared to matching pre-operative images to pre-operative images (93.42 ± 1.76%). 100% recognition performance is observed on a control-group of healthy irises from 68 subjects. Authentication performance improves if cataract affected subjects are re-enrolled in the system, though re-enrollment does not ensure performance at par with pre-operative scenarios (86.67 ± 5.64%). The results indicate that cataract surgery affects the discriminative nature of the iris texture pattern. This finding raises concerns about the reliability of iris-based biometric recognition systems in the context of subjects undergoing cataract surgery.