1 November 1993 Object tracking by an optoelectronic inner product complex neural network
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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.
Abdul Ahad Sami Awwal, Abdul Ahad Sami Awwal, Gregory J. Power, 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 . Submission:

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