Identity verification using iris images: Performance of human examiners
Kevin McGinn, Samuel Tarin, Kevin W. Bowyer · 2013
We are not aware of any previous systematic investigation of how well human examiners perform at identity verification using the same type of images as acquired for automated iris recognition. This paper presents results of an experiment in which examiners consider a pair of iris images to decide if they are either (a) two images of the same eye of the same person, or (b) images of two different eyes, with the two different individuals having the same gender, ethnicity and approximate age. Results suggest that novice examiners can readily achieve accuracy exceeding 90% and can exceed 96% when they judge their decision as “certain”. Results also suggest that examiners may be able to improve their accuracy with experience.