Oscillatory neural network for adaptive dynamical image processing

We develop a biologically motivated oscillatory network model and related dynamical synchronization-based method of image segmentation. The first version of successive segmentation algorithm was based on coupling adaptation in the oscillatory network. New model developments, presented in the paper, include: 1) a modified version of single oscillator dynamics; 2) new network connectivity rule. These modifications permit to significantly improve the oscillatory method capabilities, providing image processing with significantly larger pixel array sizes and ensuring higher segmentation accuracy. In addition the improved network model allows to perform selective image segmentation tasks (extraction of prescribed subset of image fragments). New method capabilities have been demonstrated in computer experiments