Hamming Distance and Metadata for Pairings (Genuine and Imposter) of Irises with Varying Pupil Dilation and Eyelid Manipulation
收藏IEEE2026-04-17 收录
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https://ieee-dataport.org/documents/hamming-distance-and-metadata-pairings-genuine-and-imposter-irises-varying-pupil-dilation
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资源简介：
This dataset contains six curated subset CSV files, developed to study how pupil dilation and eyelid state influence iris recognition performance. Each CSV represents a specific experimental pairing condition, spanning neutral, squint, dilated, and undilated states, and includes quantitative metrics for both ocular geometry and biometric similarity.
提供机构：
Joel Palko; John Nguyen; Eric Moran; Jack Pessaud
