Automatic 3D reconstruction of SEM images based on Nano-robotic manipulation and epipolar plane images

Abstract

This paper reports a new and general 3D reconstruction algorithm by using the light field reconstruction theory to effectively construct 3D SEM images in a large range. Firstly, a nano-robotic system was employed to automatically capture a group of SEM images along a linear path with a fixed step size, which allowed the 3D SEM images to be reconstructed beyond the field of view (FOV) of SEM. Then, the epipolar-plane images (EPI) were generated, and the depth image was reconstructed based on the specific linear structures emerging in EPI and the automatic depth estimation algorithm. After that, the depth image was stitched and the dense 3D point cloud was obtained by using the delaunay technology. Depth reconstruction with the proposed algorithm does not depend on the matching corresponding points technology. This means nearly all kinds of SEM samples, even those with a simple texture structure or an almost flat surface, can be reconstructed. In addition, the proposed method allows constructing the 3D images out of the FOV of SEM with the assistance of nanorobot. The performance of the proposed algorithm was tested using our self-built database with several microscopic samples. The results demonstrate that the proposed algorithm is general and effective and it is particularly suitable for reconstructing highly complex micro surfaces with a flat surface in a large range.

Keywords: Depth estimation; Epipolar-plane images; Light field; SEM surface reconstruction.