Colour image segmentation based on a spiking neural network model inspired by the visual system

Authors:
QingXiang Wu;T. M. McGinnity;Liam Maguire;G. D. Valderrama-Gonzalez;Patrick Dempster
Affiliations:
Intelligent Systems Research Centre, University of Ulster, Northern Ireland, UK;Intelligent Systems Research Centre, University of Ulster, Northern Ireland, UK;Intelligent Systems Research Centre, University of Ulster, Northern Ireland, UK;Intelligent Systems Research Centre, University of Ulster, Northern Ireland, UK;Intelligent Systems Research Centre, University of Ulster, Northern Ireland, UK
Venue:
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Year:
2010

Citing 4
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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.