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

  • QingXiang Wu
  • T. M. McGinnity
  • Liam Maguire
  • G. D. Valderrama-Gonzalez
  • Patrick Dempster
Conference paper

DOI: 10.1007/978-3-642-14922-1_7

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6215)
Cite this paper as:
Wu Q., McGinnity T.M., Maguire L., Valderrama-Gonzalez G.D., Dempster P. (2010) Colour Image Segmentation Based on a Spiking Neural Network Model Inspired by the Visual System. In: Huang DS., Zhao Z., Bevilacqua V., Figueroa J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg

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 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • QingXiang Wu
    • 1
  • T. M. McGinnity
    • 1
  • Liam Maguire
    • 1
  • G. D. Valderrama-Gonzalez
    • 1
  • Patrick Dempster
    • 1
  1. 1.Intelligent Systems Research CentreUniversity of Ulster at Magee Campus, DerryNorthern IrelandUK

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