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Image Segmentation by Networks of Spiking Neurons

jbuhmann{at}inf.ethz.ch, Swiss Federal Institute of Technology, CH-8092 Zurich, Switzerland

Tilman Lange

langet{at}inf.ethz.ch, Swiss Federal Institute of Technology, CH-8092 Zurich, Switzerland

Ulrich Ramacher

Ulrich.Ramacher{at}infineon.com, Infineon Technologies, D-81739 München, Germany

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.