Large Scale Iris Image Quality Evaluation
نویسنده
چکیده
Several recent studies have shown that while iris images captured at near infrared are viable biometrics for verification and identification, similar to other biometrics, its performance drops when comparing images from imperfect sources (e.g. subject blinking), under imperfect conditions (e.g. out of focus) or non-ideal capture device. The immediate question to ask is what factors and to what degree are most influential on iris recognition performance. Motivated by this need, National Institute of Standards and Technology (NIST) initiated Iris Quality Evaluation and Calibration (IQCE). IQCE aims to define and quantify iris image properties that are influential on performance of iris recognition. This paper gives an overview of the IQCE.
منابع مشابه
Optimizations in Iris Recognition A Dissertation Submitted to the Graduate School of the University of Notre Dame in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Computer
by Xiaomei Liu Biometric verification systems employing images of the iris are claimed to be extremely accurate, yielding no false accepts at any reasonable false reject rate. However, there are few if any large scale experimental evaluations on public iris datasets reported in the literature. We have collected an iris image dataset of over 25,000 iris images from over 300 persons (over 600 iri...
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