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Title

A Network of FitzHugh-Nagumo Oscillators for Object Segmentation

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Published in Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA'97). Honolulu (Hawaii, USA). 1997
Abstract This paper adresses the problem of modeling object segmentation in the visual cortex using oscillations. The proposed architecture is based on a network of locally connected FitzHugh-Nagumo oscillators which receive graded external input. We show the suitability of such a network to encode the stimulus since the amplitude of oscillations increases monotonically as a function of the input in the neighborhood of a bifurcation, while the frequency remains nearly constant. However, due to the diffusive effects of the Laplacian connectivity, the oscillators tend to be in phase even when they represent different objects. Therefore a desynchronization mechanism, which represents spatial information about the objects, is added. The overall dynamics are described and simulation results on real images are shown.
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Research group Computer Vision and Multimedia Laboratory
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LABBI, Abderrahim, MILANESE, Ruggero, BOSCH, Holger. A Network of FitzHugh-Nagumo Oscillators for Object Segmentation. In: Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA'97). Honolulu (Hawaii, USA). [s.l.] : [s.n.], 1997. https://archive-ouverte.unige.ch/unige:47814

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Deposited on : 2015-03-06

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