  In this paper we introduce an efficient algorithm for identifying conductive
objects using induction data derived from eddy currents. Our method consists of
first extracting geometric features from the induction data and then matching
them to precomputed data for known objects from a given dictionary. The
matching step relies on fundamental properties of conductive polarization
tensors and new invariants introduced in this paper. A new shape identification
scheme is introduced and studied. We test it numerically in the presence of
measurement noise. Stability and resolution capabilities of the proposed
identification algorithm are quantified in numerical simulations.
