Oscillatory network with self-organized dynamical connections for synchronization-based image segmentation |
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Authors: | Kuzmina Margarita Manykin Eduard Surina Irina |
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Institution: | Keldysh Institute of Applied Mathematics RAS, Miusskaya Sq. 4, 125047 Moscow, Russia. kuzmina@spp.keldysh.ru |
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Abstract: | An oscillatory network of columnar architecture located in 3D spatial lattice was recently designed by the authors as oscillatory model of the brain visual cortex. Single network oscillator is a relaxational neural oscillator with internal dynamics tunable by visual image characteristics - local brightness and elementary bar orientation. It is able to demonstrate either activity state (stable undamped oscillations) or "silence" (quickly damped oscillations). Self-organized nonlocal dynamical connections of oscillators depend on oscillator activity levels and orientations of cortical receptive fields. Network performance consists in transfer into a state of clusterized synchronization. At current stage grey-level image segmentation tasks are carried out by 2D oscillatory network, obtained as a limit version of the source model. Due to supplemented network coupling strength control the 2D reduced network provides synchronization-based image segmentation. New results on segmentation of brightness and texture images presented in the paper demonstrate accurate network performance and informative visualization of segmentation results, inherent in the model. |
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