A variety of computational tasks in early vision can be formulated through lattice networks. The cooperative action of these networks depends upon 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 analysed in detail, pointing out how a near-optimal filtering behaviour 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 analogue 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); and (iii) the implementation technology (2mhu and 0.8mhu gate lengths). Applications of the perceptual engine to machine vision algorithms are discussed.
Analog VLSI primitives for perceptual tasks in machine vision / BISIO G.M; RAFFO L; S.P. SABATINI. - In: NEURAL COMPUTING & APPLICATIONS. - ISSN 0941-0643. - STAMPA. - 7(1998), pp. 216-228.
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Titolo: | Analog VLSI primitives for perceptual tasks in machine vision |
Autori: | |
Data di pubblicazione: | 1998 |
Rivista: | |
Citazione: | Analog VLSI primitives for perceptual tasks in machine vision / BISIO G.M; RAFFO L; S.P. SABATINI. - In: NEURAL COMPUTING & APPLICATIONS. - ISSN 0941-0643. - STAMPA. - 7(1998), pp. 216-228. |
Abstract: | A variety of computational tasks in early vision can be formulated through lattice networks. The cooperative action of these networks depends upon 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 analysed in detail, pointing out how a near-optimal filtering behaviour 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 analogue 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); and (iii) the implementation technology (2mhu and 0.8mhu gate lengths). Applications of the perceptual engine to machine vision algorithms are discussed. |
Handle: | http://hdl.handle.net/11567/255978 |
Appare nelle tipologie: | 01.01 - Articolo su rivista |