Fast image drift compensation in scanning electron microscope using image registration

Abstract

Abstract-Scanning Electron Microscope (SEM) image acquisition is mostly affected by the time varying motion of pixel positions in the consecutive images, a phenomenon called drift. In order to perform accurate measurements using SEM, it is necessary to compensate this drift in advance. Most of the existing drift compensation methods were developed using the image correlation technique. In this paper, we present an image registration-based drift compensation method, where the correction on the distorted image is performed by computing the homography, using the keypoint correspondences between the images. Four keypoint detection algorithms have been used for this work. The obtained experimental results demonstrate the method's performance and efficiency in comparison with the correlation technique.

CLEMSite, a software for automated phenotypic screens using light microscopy and FIB-SEM

“…Note that the surface of the resin block is an inverted imprint of the surface of the gridded culture dish. Due to topological variations in the sample surface, SEM lens distortions and thermal drift 27,28 , the accuracy of this computed global transformation can vary between areas of the sample with an error of 12 ± 7 µm , ( N = 3 experiments). To increase the targeting accuracy, a local transformation delineates the third and final targeting refinement.…”

Automated Robotic Manipulation of Individual Colloidal Particles Using Vision-Based Control

“…4) Image acquisition in the SEM is affected by the timevarying motion of pixels in consecutive images, called drift. This can be due to thermal expansion, contraction of microscope components or electrostatic charges [45]. 5) Electron beam induced sticking effects complicate handling of objects within the lower micrometer range.…”

Robust, Fiducial-Free Drift Correction for Super-resolution Imaging

“…Drift occurs in all varieties of microscopy, for example, scanning electron microscopy (SEM) 1,6 , scanning (electron) tunneling microscopy (STM) 7,8 , and scanning probe microscopy 9 among others. Here, we are concerned with super-resolution microscopy of blinking fluorescent particles in which the images are taken over many movie frames [10][11][12][13] .…”

“…Some researchers have suggested tracking image features, for example, the center of mass of a cell-like object 17 . Several techniques involve identifying and extracting image features, then matching them for global correspondence 6 , using clusters of those features 2 , or their nearest (feature) neighbors 8 in order to deduce the drift. These techniques work best with non-pointlike features 6 .…”