Moving object extraction using multi-tiered pulse-coupled neural network

Jun Chen*, Kosei Ishimura, Mitsuo Wada

*この研究の対応する著者

研究成果: Paper査読

3 被引用数 (Scopus)

抄録

A novel method for extraction of moving objects in an image sequence using multi-tiered Pulse-Coupled Neural Network (PCNN) is presented in this paper. PCNN is a biologically-inspired model which shows highly applicable in various image processing applications, including image segmentation, contour detection, etc. In order to adapt PCNN for moving object extraction, the multi-tiered PCNN model is proposed. This new PCNN model is called E-PCNN, since excitatory term and external linking are its two features. The architecture and algorithm of E-PCNN are presented in detail. It is shown that E-PCNN outweighs the commonly used inter-frame difference algorithm, having three main advantages: utilization of multiple color information, parameter robustness and robustness against noise.

本文言語English
ページ73-78
ページ数6
出版ステータスPublished - 2004 12 1
外部発表はい
イベントSICE Annual Conference 2004 - Sapporo, Japan
継続期間: 2004 8 42004 8 6

Conference

ConferenceSICE Annual Conference 2004
国/地域Japan
CitySapporo
Period04/8/404/8/6

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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