This work presents a generalizable test environment platform which can load multiple algorithms and au-tomatically run them with an image database to determine their performance based on various metrics of interest. This is useful because it enables algorithm developers to develop and test algorithms for various systems without physical access to those systems. The output will be text and graphical data communicating performance such as hit rates, ROC curves, proportion correct, and other methods of estimating detection, as well as the algorithm run time. The platform provides great ﬂexibility by easily integrating algorithms written in various programming languages, allowing for uniform measurement of similar algorithms deployed in diﬀerent software environments, and working on both Windows and Linux. This platform has many appli-cations within the non-destructive evaluation community, including anomaly detection, feature extraction, and quality assurance. As an example, this work will analyze the performance of algorithms running on a database of duel energy X-rays stored as DICOS ﬁles.
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