Automatic 3D reconstruction of quasi-planar stereo Scanning Electron Microscopy (SEM) images

Three-dimensional reconstruction of highly complex microscopic samples using scanning electron microscopy and optical flow estimation

Scanning Electron Microscope (SEM) as one of the major research and industrial equipment for imaging of micro-scale samples and surfaces has gained extensive attention from its emerge. However, the acquired micrographs still remain two-dimensional (2D). In the current work a novel and highly accurate approach is proposed to recover the hidden third-dimension by use of multi-view image acquisition of the microscopic samples combined with pre/post-processing steps including sparse feature-based stereo rectification, nonlocal-based optical flow estimation for dense matching and finally depth estimation. Employing the proposed approach, three-dimensional (3D) reconstructions of highly complex microscopic samples were achieved to facilitate the interpretation of topology and geometry of surface/shape attributes of the samples. As a byproduct of the proposed approach, high-definition 3D printed models of the samples can be generated as a tangible means of physical understanding. Extensive comparisons with the state-of-the-art reveal the strength and superiority of the proposed method in uncovering the details of the highly complex microscopic samples.

Development of single-channel optical video stereomicroscopy

This study introduces a single-channel optical video stereomicroscope based on a transparent rotating deflector (TRD) for high-resolution and high-magnification stereomicroscopy. The existing stereomicroscopes have some limitations, such as limited resolution and magnification, fixed optical channel, and the necessity to use higher quality and higher cost optical channel components compared with the conventional optical microscopes. The goal of this study was to develop a method for improved stereo imaging and stereovision for optical microscopy. Here, we demonstrate the generation of stereo video images of left and right pairs by the refraction of light passing through a motorized TRD. We estimated the corresponding rotation angles for human stereovision and the required torque. In addition, we evaluated the image quality stability under the TRD rotation.