728 research outputs found
Shape recognition and classification in electro-sensing
This paper aims at advancing the field of electro-sensing. It exhibits the
physical mechanism underlying shape perception for weakly electric fish. These
fish orient themselves at night in complete darkness by employing their active
electrolocation system. They generate a stable, high-frequency, weak electric
field and perceive the transdermal potential modulations caused by a nearby
target with different admittivity than the surrounding water. In this paper, we
explain how weakly electric fish might identify and classify a target, knowing
by advance that the latter belongs to a certain collection of shapes. Our model
of the weakly electric fish relies on differential imaging, i.e., by forming an
image from the perturbations of the field due to targets, and physics-based
classification. The electric fish would first locate the target using a
specific location search algorithm. Then it could extract, from the
perturbations of the electric field, generalized (or high-order) polarization
tensors of the target. Computing, from the extracted features, invariants under
rigid motions and scaling yields shape descriptors. The weakly electric fish
might classify a target by comparing its invariants with those of a set of
learned shapes. On the other hand, when measurements are taken at multiple
frequencies, the fish might exploit the shifts and use the spectral content of
the generalized polarization tensors to dramatically improve the stability with
respect to measurement noise of the classification procedure in
electro-sensing. Surprisingly, it turns out that the first-order polarization
tensor at multiple frequencies could be enough for the purpose of
classification. A procedure to eliminate the background field in the case where
the permittivity of the surrounding medium can be neglected, and hence improve
further the stability of the classification process, is also discussed.Comment: 10 pages, 15 figure
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