Vision Experiments with Neural Deformable Template Matching

Authors:
D. S. Banarse;A. W. G. Duller
Affiliations:
School of Electronic Engineering Sciende, University College of North Wales, Dean Street, LL57 2DG Bangor Gwynedd, UK. E-mail:andy@sees.bangor.ac.uk;School of Electronic Engineering Sciende, University College of North Wales, Dean Street, LL57 2DG Bangor Gwynedd, UK. E-mail:andy@sees.bangor.ac.uk
Venue:
Neural Processing Letters
Year:
1997

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Abstract

This paper describes a neural network architecture that has beendeveloped to perform deformation tolerant object recognition fromgrey-scale images. It uses a form ofdeformable template matching, generating new templates in aself-organising manner. The results demonstrate the network‘s ability to buildclasses when no suitable classes are available. The amount ofdeformation allowed within a class can be controlled to allow thenetwork to be applied to a wide range of applications. Results arepresented for a set of generated images which allow the effects of theselection of the major network parameters to be shown.