Electrosensing of inhomogeneous targets
It provides a method for classifying inhomogeneous objects in electrosensing, relevant to weakly electric fish research and potentially to biomedical imaging.
The paper develops a shape descriptor-based classification method for inhomogeneous targets in electrosensing, using new invariants of contracted generalized polarization tensors. Numerical simulations demonstrate successful classification by comparing invariants with a dictionary of precomputed targets.
This paper addresses the electro-sensing problem for weakly electric fish in the case of inhomogeneous targets. It aims at providing a shape descriptor-based classification for inhomogeneous targets from measurements of the potentials on the skin of the fish. The approach is based on new invariants for the contracted generalized polarization tensors associated with inhomogeneous objects. The numerical simulations show that by comparing these invariants with those in a dictionary of precomputed homogeneous and inhomogeneous targets, one can successfully classify the inhomogeneous target.