  This chapter provides insight on how iris recognition, one of the leading
biometric identification technologies in the world, can be impacted by
pathologies and illnesses present in the eye, what are the possible
repercussions of this influence, and what are the possible means for taking
such effects into account when matching iris samples.
  To make this study possible, a special database of iris images has been used,
representing more than 20 different medical conditions of the ocular region
(including cataract, glaucoma, rubeosis iridis, synechiae, iris defects,
corneal pathologies and other) and containing almost 3000 samples collected
from 230 distinct irises. Then, with the use of four different iris recognition
methods, a series of experiments has been conducted, concluding in several
important observations.
  One of the most popular ocular disorders worldwide - the cataract - is shown
to worsen genuine comparison scores when results obtained from
cataract-affected eyes are compared to those coming from healthy irises. An
analysis devoted to different types of impact on eye structures caused by
diseases is also carried out with significant results. The enrollment process
is highly sensitive to those eye conditions that make the iris obstructed or
introduce geometrical distortions. Disorders affecting iris geometry, or
producing obstructions are exceptionally capable of degrading the genuine
comparison scores, so that the performance of the entire biometric system can
be influenced. Experiments also reveal that imperfect execution of the image
segmentation stage is the most prominent contributor to recognition errors.
