  Quantitative analysis methods based on the usage of a scanning electron
microscope (SEM), such as energy dispersive x-ray spectroscopy, often require
specimens to have a flat surface oriented normal to the electron beam. In-situ
procedures for putting microscopic flat surfaces into this orientation
generally rely on stereoscopic methods that measure the change in surface
vector projections when the surface is tilted by some known angle. Although
these methods have been used in the past, there is no detailed statistical
analysis of the uncertainties involved in such methods, which leaves an
uncertainty in how precisely a specimen can be oriented. Here, we present a
first principles derivation of a specimen orientation method and apply our
method to a flat sample to demonstrate it. Unlike previous works, we develop a
computer vision program using the Scale Invariant Feature Transform to automate
and expedite the process of making measurements on our SEM images, thus
enabling a detailed statistical analysis of the method with a large sample
size. We find that our specimen orientation method is able to orient flat
surfaces with high precision and can further provide insight into errors
involved in the standard SEM rotation and tilt operations.

Mesoscale and Nanoscale Physics