Analog VLSI primitives for perceptual tasks in
machine vision.

Giacomo M. Bisio and Silvio P. Sabatini
DIBE - University of Genoa, Via Opera Pia 11a, 16145 Genova, ITALY
Luigi Raffo
DIEE - University of Cagliari, Piazza d'Armi, 09123 Cagliari, ITALY

A variety of computational tasks in early vision can be formulated through
lattice networks. The cooperative action of these networks depends on the
topology of interconnections, both feedforward and recurrent ones.
The Gabor-like impulse response of a 2nd-order lattice network, i.e.,  with
nearest and next-to-nearest interconnections, is analyzed in detail,
pointing out how a near-optimal filtering behavior in space and frequency domains
can be achieved through excitatory/inhibitory interactions without impairing
the stability of the system. These architectures can be mapped, very efficiently
at transistor level, on VLSI structures operating as analog perceptual engines.
The hardware implementation of early vision tasks can, indeed, be tackled by
combining these perceptual agents through suitable weighted sums.
Various implementation strategies have been pursued with reference to:
(i) the algorithm-circuit mapping (current-mode and transconductor approaches);
(ii) the degree of programmability (fixed, selectable, and tunable);
(iii) the implementation technology ( and  gate lengths).
Applications of the perceptual engine to machine vision algorithms are
discussed.