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Proceedings Paper

Artificial neural system with Lie germs for affine invariant pattern analysis
Author(s): Thomas R. Tsao
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Paper Abstract

A computational theory and neural architecture for affine invariant pattern analysis is presented. The orbit of an image pattern under the two dimensional affine transformation group is defined as an invariant pattern class. An analog neural dynamical system with Lie germs is able to compute the distance between the orbit of a given image pattern and a template. Any pattern that is affine reachable to the template (i.e., on the same affine orbit as the template) will have zero distance while others will have larger than zero distances. The key component of this neural system is a type of artificial neuron named Lie germs. Via their receptive fields, these neurons perform the function of the infinitesimal transforms of the affine Lie group on the Gabor representation domain. The responses of the Lie germs generate the vector field of the neural dynamical system tangent to the affine orbits and make the affine orbital motion of the neural dynamical system. A computer simulation of the artificial neural system is also presented.

Paper Details

Date Published: 6 April 1995
PDF: 11 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205190
Show Author Affiliations
Thomas R. Tsao, CompuSensor Technology Corp. (United States)

Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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