We describe and analyze the performance of a non-ideal
iris recognition system. The system is designed to
process non-ideal iris images in two steps: (i) estimation
of the gaze direction and (ii) processing and encoding of
the rotated iris image. We use two objective functions to
estimate the gaze direction: Hamming distance and
Daugman’s integro-differential operator and determine
an estimated angle by picking the value that optimizes
the selected objective function. After the angle is
estimated, the off-angle iris image undergoes geometric
transformations involving the estimated angle and is
further processed as if it were a frontal view image. The
encoding technique developed in this work is based on
application of the global Independent Component
Analysis (ICA) to masked iris images. We use two
datasets: CASIA dataset and a special dataset of offangle
iris images collected at WVU to verify the
performance of the encoding technique and angle
estimator, respectively. A series of Receiver Operating
Characteristics (ROCs) demonstrates various effects on
the performance of the non-ideal iris based recognition
system implementing the global ICA encoding.