Toward Fast Calibration of Global Drift in Scanning Electron Microscopes with Respect to Time and Magnification

It is a well-known fact that scanning electron microscopic (SEM) image acquisition is mainly affected by nonlinearities and instabilities of the column and probe-specimen interaction; in turn, producing a shift in the image points with respect to many parameters and time, in particular. Even though this drift is comparatively less in modern SEMs, it is still an important factor to consider in most of the SEM-based applications. In this airticle, a simple and real-time method is proposed to estimate the global drift from a set of target images using image phase correlation, and to model its evolution by using the recursive equations of time and magnification. Based on the developed model, it is opted to use a Kalman filter in real time for accurate estimation and removal of the drift from the images. The developed method is tested using the images from a tungsten filament gun SEM (Jeol JSM 820) and a field effect gun SEM (FEI Quanta 200). The derived results show the effectiveness of the developed algorithm and also demonstrates its ability to be used in robotics as well as in material characterization under SEM.