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Title

Gray-level object segmentation with a network of FitzHugh-Nagumo oscillators

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Published in Proceedings of the International Workshop on Artificial and Natural Neural Networks (IWANN'97), Lanzarote, Canary Islands: Springer-Verlag. 1997
Collection Lecture Notes in Computer Science
Abstract In this paper we adopt a temporal coding approach to neuronal modeling of the visual cortex, using oscillations. We propose a hierarchy of three processing modules corresponding to different levels of representation. The first layer encodes the input image (stimulus) into an array of units, while the second layer consists of a network of FitzHugh-Nagumo oscillators. The dynamical behaviour of the coupled oscillators is rigorously investigated and a stimulus-driven synchronization theorem is derived. However, this module reveals itself insufficient to correctly encode and segregate different objects when they have similar gray-levels in the input image. Therefore, a third layer connected in a feedback loop with the oscillators is added. This ensures synchronization (resp. desynchronization) of neuron ensembles representing the same (resp. a different) object. Simulation results are presented using synthetic as well as real and noisy gray-level images.
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Research group Computer Vision and Multimedia Laboratory
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LABBI, Abderrahim, MILANESE, Ruggero, BOSCH, Holger. Gray-level object segmentation with a network of FitzHugh-Nagumo oscillators. In: Proceedings of the International Workshop on Artificial and Natural Neural Networks (IWANN'97), Lanzarote, Canary Islands. [s.l.] : Springer-Verlag, 1997. (Lecture Notes in Computer Science) https://archive-ouverte.unige.ch/unige:47813

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Deposited on : 2015-03-06

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