Algorithms for Extraction of Nanowires Attributes From Optical Section Microscopy Images

Abstract

Optical tweezers have emerged as a unique tool for micro and nanomanipulation. In an optical tweezers-based assembly cell, components are usually suspended in a fluidic medium and undergo constant random Brownian motion. Automated assembly using optical tweezers requires online monitoring of components in the assembly workspace. Nanowires are very important building blocks for constructing nanoscale devices. This paper presents algorithms for estimating length, location, and orientation of nanowires in the workspace using images obtained by optical section microscopy. The images are first segmented to locate general areas of interest which are then analyzed to determine discrete nanowire parameters. We use image gradient based techniques as well as feature extraction techniques to identify parameters of nanowire image patterns. These parameters are then used to estimate length, location, and orientation of nanowires.