Chapter

Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence

Volume 5227 of the series Lecture Notes in Computer Science pp 76-83

Motion Detection Using Spiking Neural Network Model

  • QingXiang WuAffiliated withIntelligent Systems Research Centre, University of Ulster at Magee Campus, DerrySchool of School of Physics and OptoElectronic Technology, Fujian Normal University
  • , T. M. McGinnityAffiliated withIntelligent Systems Research Centre, University of Ulster at Magee Campus, Derry
  • , Liam MaguireAffiliated withIntelligent Systems Research Centre, University of Ulster at Magee Campus, Derry
  • , Jianyong CaiAffiliated withSchool of School of Physics and OptoElectronic Technology, Fujian Normal University
  • , G. D. Valderrama-GonzalezAffiliated withIntelligent Systems Research Centre, University of Ulster at Magee Campus, Derry

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Abstract

Inspired by the behaviour of the human visual system, a spiking neural network is proposed to detect moving objects in a visual image sequence. The structure and the properties of the network are detailed in this paper. Simulation results show that the network is able to perform motion detection for dynamic visual image sequence. Boundaries of moving objects are extracted from an active neuron group. Using the boundary, a moving object filter is created to take the moving objects from the grey image. The moving object images can be used to recognise moving objects. The moving tracks can be recorded for further analysis of behaviours of moving objects. It is promising to apply this approach to video processing domain and robotic visual systems.

Keywords

Motion detection spiking neural networks visual system