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A new tomography model for almost optimal detection of anomalies

Abstract : In this paper a new methodology for detecting anomaly from few tomography projections is presented. This methodology exploits a statistical model adapted to the content of radiographs together with hypothesis testing theory. The main contributions are the following. First, using a generic model of the tomography acquisition pipeline, the whole non-destructive testing process is entirely automated. Second, by using testing theory the statistical properties of the proposed test are analytically established. This particularly permits the guaranteeing of a prescribed false-alarm probability and allows us to show that the proposed test is almost optimal. Experimental results show the sharpness of the established results and the relevance of the methodology.
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Contributor : Jean-Baptiste VU VAN Connect in order to contact the contributor
Submitted on : Tuesday, September 17, 2019 - 3:32:23 PM
Last modification on : Wednesday, August 31, 2022 - 6:55:20 PM


  • HAL Id : hal-02290322, version 1



Rémi Cogranne, Florent Retraint. A new tomography model for almost optimal detection of anomalies. 2013 20th IEEE International Conference on Image Processing (ICIP), Sep 2013, Melbourne, Australia. pp.1461-1465. ⟨hal-02290322⟩



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