A Novel Methodology for the Interoperability Evaluation of An Iris Segmentation Algorithm

The performance of an iris recognition system depends
greatly on how well the iris segmentation part of the system
performs its task. The performance of an iris segmenta-
tion algorithm can be evaluated using different criteria and
methods. Some of the methods evaluate the performance of
the segmentation algorithm based on the performance of the
whole iris recognition system. Other methods evaluate the
performance of an iris segmentation subsystem independent
of the performance of the system’s other subsystems. To our
knowledge there do not exist a generally accepted method
or criteria for the evaluation of the standalone iris segmen-
tation subsystem. This paper proposes a novel methodology
to compare the performance of different iris segmentation
algorithms, applied to different image datasets in a consis-
tent way. The methodology employs the F1 score and an empirical cumulative distribution function. The implementation of the F
1 score estimation, adapted to the iris segmentation task is described. Finally the application of the proposed methodology is demonstrated and discussed.