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Optical Engineering

Object recognition within cluttered scenes employing a hybrid optical neural network filter
Author(s): Ioannis I. Kypraios; Rupert C. D. Young; Philip M. Birch; Christopher R. Chatwin
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Paper Abstract

We propose a hybrid filter, which we call the hybrid optical neural network (HONN) filter. This filter combines the optical implementation and shift invariance of correlator-type filters with the nonlinear superposition capabilities of artificial neural network methods. The filter demonstrates good performance in maintaining high-quality correlation responses and resistance to clutter to nontraining in-class images at orientations intermediate to the training set poses. We present the design and implementation of the HONN filter architecture and assess its object recognition performance in clutter.

Paper Details

Date Published: 1 August 2004
PDF: 12 pages
Opt. Eng. 43(8) doi: 10.1117/1.1767194
Published in: Optical Engineering Volume 43, Issue 8
Show Author Affiliations
Ioannis I. Kypraios, Univ. of Sussex (United Kingdom)
Rupert C. D. Young, Univ. of Sussex (United Kingdom)
Philip M. Birch, Univ. of Sussex (United Kingdom)
Christopher R. Chatwin, Univ. of Sussex (United Kingdom)

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