| Paper: | SPTM-P2.5 | ||
| Session: | Detection | ||
| Time: | Tuesday, May 16, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Detection, Estimation, Classification Theory and Applications | ||
| Title: | Epsilon-Optimal Anomaly Detection in Parametric Tomography | ||
| Authors: | Lionel Fillatre, ENST Bretagne, France; Igor Nikiforov, Florent Retraint, Université de technologie de Troyes, France | ||
| Abstract: | The paper concerns the radiographic non-destructive testing of well-manufactured objects. The detection of anomalies is addressed from the statistical point of view as a binary hypothesis testing problem with nonlinear nuisance parameters. A new detection scheme is proposed as an alternative to the classical GLR test. It is shown that this original decision rule detects anomalies with a loss of a negligible (epsilon) part of optimality with respect to an optimal invariant test designed for the ``closest'' hypothesis testing problem with linear nuisance parameters. | ||
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