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Optical Engineering

Object tracking by an optoelectronic inner product complex neural network
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Paper Abstract

A complex associative memory model based on a neural network architecture is proposed for tracking three-dimensional objects in a dynamic environment. The storage representation of the complex associative memory model is based on an efficient amplitude-modulated phase-only matched filter. The input to the memory is derived from the discrete Fourier transform of the edge coordinates of the to-be-recognized moving object, where the edges are obtained through motion-based segmentation of the image scene. An adaptive threshold is used during the decision-making process to indicate a match or identify a mismatch. Computer simulation on real-world data proves the effectiveness of the proposed model. The proposed scheme is readily amenable to optoelectronic implementation.

Paper Details

Date Published: 1 November 1993
PDF: 6 pages
Opt. Eng. 32(11) doi: 10.1117/12.148110
Published in: Optical Engineering Volume 32, Issue 11
Show Author Affiliations
Abdul Ahad Sami Awwal, Wright State Univ. (United States)
Gregory J. Power, U.S. Air Force (United States)

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