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Michael Brockly's M.S. thesis presentation for Purdue University, December 2013.
This study created a framework to quantify and mitigate the amount of error that test administrators introduced to a biometric system during data collection. Prior research has focused only on the subject and the errors they make when interacting with biometric systems, while ignoring the test administrator. This study used a longitudinal data collection, focusing on demographics in government identification forms such as driver’s licenses, fingerprint metadata such a moisture and skin temperature, and face image compliance to an ISO best practice standard. Error was quantified from the first visit and baseline test administrator error rates were measured. Additional training, software development, and error mitigation techniques were introduced before a second visit, in which the error rates were measured again. The new system greatly reduced the amount of test administrator error and improved the integrity of the data collected. Findings from this study show how to measure test administrator error and how to reduce it in future data collections.