Object recognition within cluttered scenes employing a hybrid optical neural network filter

Ioannis I. Kypraios; Rupert C. D. Young; Philip M. Birch; Christopher R. Chatwin

doi:10.1117/1.1767194

1 August 2004 Object recognition within cluttered scenes employing a hybrid optical neural network filter

Ioannis I. Kypraios, Rupert C. D. Young, Philip M. Birch, Christopher R. Chatwin

Author Affiliations +

Optical Engineering, Vol. 43, Issue 8, (August 2004). https://doi.org/10.1117/1.1767194

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.

©(2004) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Ioannis I. Kypraios, Rupert C. D. Young, Philip M. Birch, and Christopher R. Chatwin "Object recognition within cluttered scenes employing a hybrid optical neural network filter," Optical Engineering 43(8), (1 August 2004). https://doi.org/10.1117/1.1767194

Published: 1 August 2004

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