Cortical Maps of Resistive Anisotropic Networks (CORMORANT)

Funding Agency: CEC

Funding period: 1994-1997

URL:

Contact Person

Giacomo.M. BISIO
Department of Biophysical and Electronic Engineering
University of Genoa
Via Opera Pia, 11a
I-16145 Genova, ITALY
tel:  (+39) 10 353 2756
fax:  (+39) 10 353 2777
e-mail: bisio@dibe.unige.it

Participants

Coordinator:
	     DIBE-University of Genoa			I
Partners:   
             IRST (Trento)				I
	     Ruhr Universitat Bochum			D
	     University of Bonn				D

Abstract

The project will investigate how the information processing capabilities of neural networks can be exploited in the direct (VLSI) implementation of complex algorithmic tasks such as those occurring in natural and artificial visual systems. Research will address: (i) the computational modeling of natural systems as formal neural networks; (ii) the formalization of neural computation through an abstract hierarchy of operators both for low- and high-level capabilities; (iii) the architectural specification of networks of these operators, specified as multilayer meshes of simple processing elements (lattice networks); (iv) the methodological issues related to the programmability/design of these meshes specified at the circuit level.

Results

Analog approaches to the hardware implementation of machine vision systems can be very effective as far as real-time performance, size, and power consumption are concerned, but machine functionality, with regard both to the variety of tasks to be performed, and to the conditions of application, can be hindered by the limited flexibility and lack of programmability of analog circuits. A solution to this problem can be searched through a systematic approach to the sensorial/perceptual computations, that goes from proper model/algorithmic formulations, through adequate architectures based on flexible primitives, to efficient VLSI circuital solutions.

The target machine vision problem considered for proving these statements is the estimation of depth maps on the basis of phase-based disparity measurements. The proposed solutions are validated focussing on chip functionality, tested at layout level and through fabrication, and on the basis of specific computer simulations in artificial and real environments.

Architectural and circuital solutions for microsystems to be used in the emulation of early vision tasks

The single-chip microsystem is characterised by three levels of adaptability:

a variety of algorithms (e.g., stereo depth estimation, texture and motion analysis) can be specified in terms of convolutions with spatial Gabor-like filters; Gabor-like kernels can be related to the impulse response of recurrent filters, specified as cooperative computational structures (i.e., lattice networks);
the phase of these kernels can be varied through linear combinations of the recurrent filter responses at nearby nodes;
the frequency and the spatial extension of the Gabor-like kernel can be controlled by analog tunable circuits.

Analog VLSI Gabor convolution kenels have been prototyped (see www.prosoma.lu).

Validation of the lattice approach under VLSI constraints

From the perspective of analog computation, an algorithm is implementable if it can be reduced to local operations. The phase-based approach to disparity estimation is local except for the convolution operation. However, if the Gaussian envelope is replaced by other kernels, convolution can be transformed into the solution of a set of differential equations whose degree is related to the number of connections per node necessary to implement the filter in a discrete model.
The first and simplest choice, i.e. the Cusp kernel that presents a discontinuity in the first derivative, leads to a fourth degree differential equation. A successive approximation of the Gaussian kernel leads to the Quartic filter that improves the smoothness of the disparity-field estimates but requires higher degree differential equations. The modifications of the system's performance due to the envelope's change are investigated in detail. The results of the simulation experiments indicate that filters' performances are comparable if they are modified in order to eliminate sensitivity to the zero-frequency content of input signals.