Probing the uniqueness and randomness of IrisCodes: Results from 200 billion iris pair comparisons

Recent large-scale deployments of iris recognition for border-crossing controls enable critical assessment of the robustness of this technology against making false matches, since vast numbers of cross comparisons become possible within large databases. This paper presents results from the 200 billion iris cross comparisons that could be performed within a database of 632 500 different iris images, spanning 152 nationalities. Each iris pattern was encoded into a phase sequence of 2048 bits using the Daugman algorithms. Empirically analyzing the tail of the resulting distribution of similarity scores enables specification of decision thresholds, and prediction of performance, of the iris recognition algorithms if deployed in identification mode on national scales.