Target Identification Using Dictionary Matching of Generalized   Polarization Tensors
  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. 
Habib Ammari, Thomas Boulier, Josselin Garnier, Wenjia Jing,   Hy{\oe}nb{\ae} Kang, Han Wang
math.OC math-ph math.AP math.MP math.NA