Object tracking by an optoelectronic inner product complex neural network

Abdul Ahad Sami Awwal; Gregory J. Power

doi:10.1117/12.148110

1 November 1993 Object tracking by an optoelectronic inner product complex neural network

Abdul Ahad Sami Awwal, Gregory J. Power

Author Affiliations +

Optical Engineering, Vol. 32, Issue 11, (November 1993). https://doi.org/10.1117/12.148110

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.

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Abdul Ahad Sami Awwal and Gregory J. Power "Object tracking by an optoelectronic inner product complex neural network," Optical Engineering 32(11), (1 November 1993). https://doi.org/10.1117/12.148110

Published: 1 November 1993

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