Target Identification Using Dictionary Matching of Generalized Polarization Tensors

Abstract : The aim of this paper is to provide a fast and efficient procedure for (real-time) target identification in imaging based on matching on a dictionary of precomputed generalized polarization tensors (GPTs). The approach is based on some important properties of the GPTs and new invariants. A new shape representation is given and numerically tested in the presence of measurement noise. The stability and resolution of the proposed identification algorithm is numerically quantified.
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https://hal.archives-ouvertes.fr/hal-00688241
Contributeur : Thomas Boulier <>
Soumis le : mardi 17 avril 2012 - 10:38:30
Dernière modification le : jeudi 27 avril 2017 - 09:45:50

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  • HAL Id : hal-00688241, version 1
  • ARXIV : 1204.3035

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Habib Ammari, Thomas Boulier, Josselin Garnier, Wenjia Jing, Hyœnbæ Kang, et al.. Target Identification Using Dictionary Matching of Generalized Polarization Tensors. Submitted to Foundations of Computational Mathematics. 2012. 〈hal-00688241〉

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