It is clear from prior research that quality metrics can predict and improve recognition performance. As we add new quality metrics, however,
determining a weighting scheme using simple rules for their combination becomes infeasible. This argues for a machine learning approach that… More
In Phase I we developed a machine learning method for predicting match score errors in iris imagery to determine the quality of the image. We now
propose to develop a flexible and configurable tool for creating, refining, and applying such a match score predictor to any image quality… More