Automated Microstructure Analysis of Large Regions

Abstract

The mechanical and physical properties of materials are often related to grain size. To accurately measure grain size over a large region, it is imperative to acquire high-resolution image data for each of the grains and detect all of them. Although there is an existing technique, Electron Backscatter Diffraction (EBSD), that can achieve the objective, it is an expensive technique which requires a Scanning Electron Microscope (SEM). Therefore, it is beneficial to develop a less expensive technique that can use traditional and cheap equipment, such as an optical microscope. This thesis is dedicated to making an optical microscope automatically scan over a large region of a specimen and offer microstructural quantification including grain boundary identification, grain size number and grain size distribution. In addition, the maps of grain size and grain aspect ratio will be created to give users a better visualization. The feature of multiple zoom levels for the microstructure is also added for users to navigate through the large regions easily. Finally, software has been developed to help users identify “rare events” in microstructure, such as abnormal grains, and flag those rare events in the map for visual inspection