17 May 2006 Performance measures for ATR systems with multiple classifiers and multiple labels
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Abstract
Significant advances in the performance of ATR systems can be made when fusing individual classification systems into a single combined classification system. Often, these individual systems are dependent, or correlated, with one another. Additionally, these systems typically assume that two outcome labels, (for instance "target" and "non-target") exist. Little is known about the performance of fused classification systems when multiple outcome labels are used. In this paper, we propose a methodology for quantifying the performance of the fused classifier system using multiple labels. Specifically, a performance measure for a fused classification system using two classifiers and multiple labels will be developed. The performance measure developed is based on the Receiver Operating Characteristic (ROC) curve. The ROC curve in a two-label system has been well defined and used extensively, in not only ATR applications, but also other engineering and biomedical applications. A ROC manifold is defined and use in order to incorporate the multiple labels. An example of this performance measure for a given fusion rule and multiple labels is given.
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Christine M. Schubert, Steven Thorsen, Mark E. Oxley, Kenneth W. Bauer, "Performance measures for ATR systems with multiple classifiers and multiple labels", Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 62350V (17 May 2006); doi: 10.1117/12.668464; https://doi.org/10.1117/12.668464
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