Automated 3D Modeling and Analysis of Metallic Materials Using Multiple LC-SEM Images

The scanning electron microscope (SEM) has been successfully used as an analysis tool for micro scale materials in the last few decades [1]. Recently, the large chamber (LC) SEM at Y-12 has demonstrated useful results in the analysis of large specimens at nano scales. This paper summarizes the research efforts conducted by UT and Y-12 in applying state of art 3D computer vision techniques to LC-SEM imaging, particularly 3D reconstruction and modeling [2]. In such a way, two or more LC-SEM images taken under appropriate condition (for example, with small changes in tilt angle), combined with knowledge of the imaging process, can be used to infer the 3D structure of the specimen automatically.