Chapter

Advanced Intelligent Computing Theories and Applications

Volume 6215 of the series Lecture Notes in Computer Science pp 49-57

Colour Image Segmentation Based on a Spiking Neural Network Model Inspired by the Visual System

  • QingXiang WuAffiliated withCarnegie Mellon UniversityIntelligent Systems Research Centre, University of Ulster at Magee Campus, Derry
  • , T. M. McGinnityAffiliated withCarnegie Mellon UniversityIntelligent Systems Research Centre, University of Ulster at Magee Campus, Derry
  • , Liam MaguireAffiliated withCarnegie Mellon UniversityIntelligent Systems Research Centre, University of Ulster at Magee Campus, Derry
  • , G. D. Valderrama-GonzalezAffiliated withCarnegie Mellon UniversityIntelligent Systems Research Centre, University of Ulster at Magee Campus, Derry
  • , Patrick DempsterAffiliated withCarnegie Mellon UniversityIntelligent Systems Research Centre, University of Ulster at Magee Campus, Derry

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Abstract

The human visual system demonstrates powerful image processing functionalities. Inspired by the visual system, a spiking neural network is proposed to segment visual images. The network is constructed in the two parts. The first part is a spiking neural network which is composed of photon receptors, cone and rod cells, and ON/OFF ganglion cells. Colour features can be extracted and passed through different ON/OFF pathways. The second part is a BP neural network which is trained to recognize the colour features and segment the visual image. The network has been successfully applied to segment leukocytes from blood smeared images.

Keywords

Spiking neural networks image segmentation visual system visual image