NIST · ИТ · bf5e2caae7d4b6211248
IREX III Supplement 1: Failure Analysis
Iris recognition has the potential to be extremely accurate, but it is highly dependent on the quality of the input data. Iris occlusion, off-axis gaze, blurred images, and iris rotation are common problems that can make recognizing individuals more
NIST · ИТОфициальный источник · 2012-04-18
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"title_en": "IREX III Supplement 1: Failure Analysis",
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"date": "2012-04-18",
"date_original": "April 18, 2012",
"url": "https://www.nist.gov/publications/irex-iii-supplement-1-failure-analysis",
"source": "NIST Publications",
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"authors_en": "George W. Quinn , Patrick J. Grother",
"abstract_excerpt_en": "Iris recognition has the potential to be extremely accurate, but it is highly dependent on the quality of the input data. Iris occlusion, off-axis gaze, blurred images, and iris rotation are common problems that can make recognizing individuals more",
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"title_en": "IREX III Supplement 1: Failure Analysis",
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