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Image segmentation by networks of spiking neurons.
Journal article

Image segmentation by networks of spiking neurons.

  • 2005-04-15
Published in:
  • Neural computation. - 2005
Action Potentials
Animals
Brain
Excitatory Postsynaptic Potentials
Humans
Models, Neurological
Nerve Net
Neural Networks, Computer
Neural Pathways
Neurons
Pattern Recognition, Visual
Synapses
Synaptic Transmission
Visual Pathways
English A network of leaky integrate-and-fire (IAF) neurons is proposed to segment gray-scale images. The network architecture with local competition between neurons that encode segment assignments of image blocks is motivated by a histogram clustering approach to image segmentation. Lateral excitatory connections between neighboring image sites yield a local smoothing of segments. The mean firing rate of class membership neurons encodes the image segmentation. A weight modification scheme is proposed that estimates segment-specific prototypical histograms. The robustness properties of the network implementation make it amenable to an analog VLSI realization. Results on synthetic and real-world images demonstrate the effectiveness of the architecture.
Language
  • English
Open access status
closed
Identifiers
Persistent URL
https://sonar.ch/global/documents/234145
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