This paper presents four significant advancements in iris recognition technology: 1) improved methods for detecting and modeling the inner and outer boundaries of the iris using active contours, leading to more flexible coordinate systems; 2) Fourier-based methods for handling off-axis gaze by detecting and "rotating" the eye into orthographic perspective; 3) statistical inference methods for detecting and excluding eyelashes; and 4) exploration of score normalizations based on the amount of iris data available and the required scale of database search. The statistical results are based on 200 billion iris cross-comparisons from the United Arab Emirates database, analyzing the normalization issues across different regions of receiver operating characteristic (ROC) curves. These advancements aim to improve both the false match rate (FMR) and false non-match rate (FnMR) under various conditions, making iris recognition more robust and reliable for large-scale applications.This paper presents four significant advancements in iris recognition technology: 1) improved methods for detecting and modeling the inner and outer boundaries of the iris using active contours, leading to more flexible coordinate systems; 2) Fourier-based methods for handling off-axis gaze by detecting and "rotating" the eye into orthographic perspective; 3) statistical inference methods for detecting and excluding eyelashes; and 4) exploration of score normalizations based on the amount of iris data available and the required scale of database search. The statistical results are based on 200 billion iris cross-comparisons from the United Arab Emirates database, analyzing the normalization issues across different regions of receiver operating characteristic (ROC) curves. These advancements aim to improve both the false match rate (FMR) and false non-match rate (FnMR) under various conditions, making iris recognition more robust and reliable for large-scale applications.