A deep analysis of the image and video processing techniques using nanoscale quantum-dots cellular automata

Abstract

The advancement of small electrical components into the nanoscale range opens up opportunities for massively parallel computing systems. Quantum-dot Cellular Automata (QCA) is a potential novel nanoelectronics technique that fits image processing requirements well. QCA circuits are typically highly stable, quick, and utilize little energy. Because studies about QCA logic image processing are starting up, the suggested contribution will initiate a new line of inquiry in the real-time video and image processing domain. Noise reduction, face identification, feature extraction, segmentation, skeletonizing, thickening, thinning, object detection, form extraction, and tracking are all examples of image processing. This article describes how to use QCA technology for image processing in various ways. The fundamentals of image processing approaches and the function of QCA in them are covered. The findings demonstrate that a more effective layout based on QCA technology would reduce power consumption and computational complexity in the long run. We anticipate that this compendium will give readers an overview of the advances made in quantum image processing and pique their curiosity in doing a more complex investigation in the field.