A large dataset of synthetic SEM images of powder materials and their ground truth 3D structures

Brian L DeCost; Elizabeth A Holm

doi:10.1016/j.dib.2016.10.011

A large dataset of synthetic SEM images of powder materials and their ground truth 3D structures

Data Brief. 2016 Oct 22:9:727-731. doi: 10.1016/j.dib.2016.10.011. eCollection 2016 Dec.

Authors

Brian L DeCost¹, Elizabeth A Holm¹

Affiliation

¹ Department of Materials Science and Engineering, Carnegie Mellon University, USA.

Abstract

This data article presents a data set comprised of 2048 synthetic scanning electron microscope (SEM) images of powder materials and descriptions of the corresponding 3D structures that they represent. These images were created using open source rendering software, and the generating scripts are included with the data set. Eight particle size distributions are represented with 256 independent images from each. The particle size distributions are relatively similar to each other, so that the dataset offers a useful benchmark to assess the fidelity of image analysis techniques. The characteristics of the PSDs and the resulting images are described and analyzed in more detail in the research article "Characterizing powder materials using keypoint-based computer vision methods" (B.L. DeCost, E.A. Holm, 2016) [1]. These data are freely available in a Mendeley Data archive "A large dataset of synthetic SEM images of powder materials and their ground truth 3D structures" (B.L. DeCost, E.A. Holm, 2016) located at http://dx.doi.org/10.17632/tj4syyj9mr.1[2] for any academic, educational, or research purposes.

Keywords: Computational materials science; Computer vision; Image databases; Metal powder; Microstructural analysis.