Exploratory Analysis of an Operational Iris Recognition Dataset from a CBSA Border-Crossing Application

This paper presents an exploratory analysis of an iris recognition dataset from the NEXUS border-crossing program run by the Canadian Border Services Agency. The distribution of the normalized Hamming distance for successful border-crossing transactions is examined in the context of various properties of the operational scenario. The effects of properties such as match score censoring and truncation, same-sensor and cross-sensor matching, sequence-dependent matching, and multiple-kiosk matching are illustrated. Implications of these properties of the operational dataset for the study of iris template aging are discussed.