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

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Wu, Qingxiang, McGinnity, TM, Maguire, Liam, Valderrama, German and Dempster, Patrick (2010) Colour Image Segmentation Based on a Spiking Neural Network Model Inspired by the Visual System. In: international conference on Intelligent Computing (ICIC2010), Changsha, China. Springer-Verlag. 8 pp. [Conference contribution]

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

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.

Item Type:Conference contribution (Lecture)
Keywords:Spiking neural networks, image segmentation, visual system, visual image
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:20364
Deposited By:Dr Qingxiang Wu
Deposited On:28 Oct 2011 10:00
Last Modified:28 Oct 2011 10:00

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