Estimating and Fusing Quality Factors for Iris Biometric Images

Iris recognition, the ability to recognize and distinguish individuals by their iris pattern, is one of the most reliable biometrics in terms of recognition and identification performance. However, the performance of these systems is affected by poor-quality imaging. In this paper, we extend iris qu...

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Veröffentlicht in:	IEEE transactions on systems, man and cybernetics. Part A, Systems and humans man and cybernetics. Part A, Systems and humans, 2010-05, Vol.40 (3), p.509-524
Hauptverfasser:	Kalka, Nathan D, Jinyu Zuo, Schmid, Natalia A, Cukic, Bojan
Format:	Artikel
Sprache:	eng
Schlagworte:	Automation Belief function Biometrics Dempster-Shafer (DS) theory Illumination Image quality iris image quality Iris recognition Lighting Motion estimation Occlusion Operations research Optical reflection Pattern recognition Performance analysis Pixel Q factor Quality assessment Quality factor quality metrics Recognition Studies
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