  Synchronization of coupled oscillators is observed at multiple levels of
neural systems, and has been shown to play an important function in visual
perception. We propose a computing system based on locally coupled oscillator
networks for image segmentation. The system can serve as the preprocessing
front-end of an image processing pipeline where the common frequencies of
clusters of oscillators reflect the segmentation results. To demonstrate the
feasibility of our design, the system is simulated and tested on a human face
image dataset and its performance is compared with traditional intensity
threshold based algorithms. Our system shows both better performance and higher
noise tolerance than traditional methods.
