Contour Detection by Synchronization of Integrate-and-Fire Neurons
Identifieur interne : 008805 ( Main/Merge ); précédent : 008804; suivant : 008806Contour Detection by Synchronization of Integrate-and-Fire Neurons
Auteurs : Etienne Hugues ; Florent Guilleux ; Olivier RochelSource :
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Abstract
We present a biologically inspired spiking neural network which is able to detect contours in grey level images by synchronization of neurons. This network is made of integrate-and-fire neurons, spaced on a triangular network, whose oriented receptive field is constructed by a wavelet which specifically detects edges. The neurons are excitatorily and locally connected between receptive fields that tend to detect the same contour. A contour, if its width is not too large, activates a chain of neurons, with some heterogeneity in the inputs. The capacity of a chain to synchronize with respect to such heterogeneity is studied. Synchronization on a contour is found to be possible for a sufficiently large width.
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<author><name sortKey="Guilleux, Florent" sort="Guilleux, Florent" uniqKey="Guilleux F" first="Florent" last="Guilleux">Florent Guilleux</name>
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<author><name sortKey="Rochel, Olivier" sort="Rochel, Olivier" uniqKey="Rochel O" first="Olivier" last="Rochel">Olivier Rochel</name>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>contour detection</term>
<term>integrate-and-fire</term>
<term>neural network</term>
<term>orientation selectivity</term>
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<term>synchronization</term>
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<front><div type="abstract" xml:lang="en" wicri:score="2842">We present a biologically inspired spiking neural network which is able to detect contours in grey level images by synchronization of neurons. This network is made of integrate-and-fire neurons, spaced on a triangular network, whose oriented receptive field is constructed by a wavelet which specifically detects edges. The neurons are excitatorily and locally connected between receptive fields that tend to detect the same contour. A contour, if its width is not too large, activates a chain of neurons, with some heterogeneity in the inputs. The capacity of a chain to synchronize with respect to such heterogeneity is studied. Synchronization on a contour is found to be possible for a sufficiently large width.</div>
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