DocumentCode :
1632710
Title :
Moving object extraction using multi-tiered pulse-coupled neural network
Author :
Chen, Jun ; Ishimura, Kosei ; Wada, Mitsuo
Author_Institution :
Div. of Synergetic Inf. Sci., Hokkaido Univ., Sapporo, Japan
Volume :
3
fYear :
2004
Firstpage :
2843
Abstract :
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.
Keywords :
feature extraction; image motion analysis; image sequences; neural nets; object detection; E-PCNN architecture; image processing; image sequence; multiple color information; multitiered pulse-coupled neural network; noise robustness; object extraction; parameter robustness; robust motion detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE 2004 Annual Conference
Conference_Location :
Sapporo
Print_ISBN :
4-907764-22-7
Type :
conf
Filename :
1491939
Link To Document :
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