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Vision Experiments with Neural Deformable Template Matching

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Abstract

This paper describes a neural network architecture that has been developed to perform deformation tolerant object recognition from grey-scale images. It uses a form of deformable template matching, generating new templates in a self-organising manner. The results demonstrate the network's ability to build classes when no suitable classes are available. The amount of deformation allowed within a class can be controlled to allow the network to be applied to a wide range of applications. Results are presented for a set of generated images which allow the effects of the selection of the major network parameters to be shown.

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Authors and Affiliations

  1. School of Electronic Engineering Sciende, University College of North Wales, Dean Street, LL57 2DG, Bangor Gwynedd, UK

    D.S. Banarse & A.W.G. Duller

Authors
  1. D.S. Banarse
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  2. A.W.G. Duller
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Banarse, D., Duller, A. Vision Experiments with Neural Deformable Template Matching. Neural Processing Letters 5, 41–49 (1997). https://doi.org/10.1023/A:1009661908220

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  • DOI: https://doi.org/10.1023/A:1009661908220

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