Image Processing Using Coupled Oscillators

Open Access
Ranade, Rohit Rajiv
Graduate Program:
Electrical Engineering
Master of Science
Document Type:
Master Thesis
Date of Defense:
December 04, 2013
Committee Members:
  • Vijaykrishnan Narayanan, Thesis Advisor
  • Kenneth Jenkins, Thesis Advisor
  • oscillators
  • image processing
  • kuramoto model
The observation of oscillatory activity in neurons and synchronization in ensembles of neurons has led to research efforts focused on exploring these oscillations and their application in image processing. At the same time, the emergence of many new nano-scale technologies has opened up novel avenues in computation methodologies, through the rethinking of the traditional Boolean paradigm, to explore their potential application in non-Boolean computation. Along with this, many recent hardware architectures have allowed acceleration through the use of multiple components to perform dedicated tasks. The use of neuromorphic architectures consisting of coupled oscillator arrays using emerging devices based on the observation of synchrony in the brain, to produce computational hardware with better energy efficiency as compared to traditional CMOS architectures for image processing tasks can now be explored. In this thesis, a theoretical framework for a network of oscillators which are coupled to each other is explored and its application towards image processing tasks, namely, edge detection, image segmentation, image recognition and motion estimation is demonstrated. This network is not restricted to any particular device, but instead, provides a generic foundation.