Lattice networks with nearest and next nearest interconnections, are characterized by Gabor-like impulse responses, with a near-optimal filtering behaviour in space and spatial frequency domains, and can support a variety of embedded analog filtering operators in smart vision sensors. These networks can be mapped, very efficiently, on VLSI structures operating as an array of analog perceptual engines. The adaptability required to tackle the hardware implementation of early vision tasks can be obtained by combining these perceptual engines through suitable weighted sums. Applications in the field of dynamic stereo vision are presented.

How to organize analog VLSI operators to perform perceptual tasks in machine vision

BISIO, GIACOMO;SABATINI, SILVIO PAOLO;SOLARI, FABIO
2004-01-01

Abstract

Lattice networks with nearest and next nearest interconnections, are characterized by Gabor-like impulse responses, with a near-optimal filtering behaviour in space and spatial frequency domains, and can support a variety of embedded analog filtering operators in smart vision sensors. These networks can be mapped, very efficiently, on VLSI structures operating as an array of analog perceptual engines. The adaptability required to tackle the hardware implementation of early vision tasks can be obtained by combining these perceptual engines through suitable weighted sums. Applications in the field of dynamic stereo vision are presented.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/227342
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