Moving Object Extraction Using Multi-Tiered Pulse-Coupled Neural Network

Jun Chen; Kosei Ishimura; Mitsuo Wada

doi:10.11499/sicep.2004.0_3_5

SICE Annual Conference 2004

DOI https://doi.org/10.11499/sicep.2004.0_3_5

Conference information

Host: The Society of Instrument and Control Engineers

Co-host: The IEEE Industrial Electronics Society, The IEEE Robotics and Automation Society, The IEEE Control Systems Society, The IEEE Systems, Man and Cybernetics Society, The Instrumentation, Systems, and Automation Society

Moving Object Extraction Using Multi-Tiered Pulse-Coupled Neural Network

*Jun Chen, Kosei Ishimura, Mitsuo Wada

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CONFERENCE PROCEEDINGS FREE ACCESS

Pages 3

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Abstract

This paper presents a novel method for moving object extraction using multi-tiered Pulse-Coupled Neural Network (PCNN). The multi-tiered PCNN model is called E-PCNN, since excitatory term and external linking are its two features. It is shown that E-PCNN outweighs the commonly used inter-frame difference algorithm, having three main advantages: utilizing multiple color information, parameter robustness and against noise.

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