Buhmann JM Lange T Ramacher U 2005 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. https://sonar.ch/global/documents/234145 eng info:eu-repo/semantics/altIdentifier/doi/10.1162/0899766053491913 info:eu-repo/semantics/altIdentifier/pmid/15829098 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 Image segmentation by networks of spiking neurons. http://purl.org/coar/resource_type/c_6501