Detection system performance metrics with scene content dependencies

Timothy D. Ross; William E. Pierson; Edmund G. Zelnio; Kevin L. Priddy

doi:10.1117/12.609758

19 May 2005 Detection system performance metrics with scene content dependencies

Timothy D. Ross, William E. Pierson, Edmund G. Zelnio, Kevin L. Priddy

Proceedings Volume 5808, Algorithms for Synthetic Aperture Radar Imagery XII; (2005) https://doi.org/10.1117/12.609758
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

Traditional detection system performance metrics, such a probability of detection and probability of false alarm, depend only on how the system responds to individual target-sized regions-of-interest (ROIs). The composition of the larger scene does not affect those metrics. There are circumstances however, where a user of a detection system wants to know, "For a given cue, what is the probability that the cue is correct?" or perhaps the detector is being used to determine a property of the overall scene. As an example of the latter case, suppose the detection system is looking for diseased cells in a tissue sample. Even if only one diseased cell exists, the whole "scene" represents a diseased individual. In both cases, the user-perspective or the scene-based perspective, the natural performance metrics depend on the scene content, especially the numbers of target and confuser ROIs. This paper defines scene-content dependent (SCD) performance metrics for detection systems, develops a theory for computing them, and illustrates properties of the metrics with examples. The SCD performance theory enabled determination of the example metrics in about two hours of computation; whereas Monte Carlo methods would have taken almost a year and direct testing would have been almost impossible.

Citation Download Citation

Timothy D. Ross, William E. Pierson, Edmund G. Zelnio, and Kevin L. Priddy "Detection system performance metrics with scene content dependencies", Proc. SPIE 5808, Algorithms for Synthetic Aperture Radar Imagery XII, (19 May 2005); https://doi.org/10.1117/12.609758

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