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Biologically Inspired Edge Detection using Spiking Neural Networks and Hexagonal Images

Clogenson, M, Kerr, D, McGinnity, TM, Coleman, SA and Wu, Qingxiang (2011) Biologically Inspired Edge Detection using Spiking Neural Networks and Hexagonal Images. In: International Conference on Neural Computation Theory and Applications, Paris, France. SciTePress. 1000 pp. [Conference contribution]

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DOI: 10.5220/0003682103810384

Abstract

Inspired by the structure and behaviour of the human visual system, we extend existing work using spiking neural networks for edge detection with a biologically plausible hexagonal pixel arrangement. Standard digital images are converted into a hexagonal pixel representation before being processed with a spiking neural network with scalable hexagonally shaped receptive fields. The performance is compared with different sized receptive fields implemented on standard rectangular images. Results illustrate that using hexagonal-shaped receptive fields provides improved performance over a range of scales compared with standard rectangular shaped receptive fields and images.

Item Type:Conference contribution (Paper)
Keywords:Spiking neural network, Edge detection, Multi-scale hexagonal receptive fields
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 > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:20775
Deposited By: Dr Dermot Kerr
Deposited On:17 Jan 2012 14:44
Last Modified:09 Dec 2015 11:01

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