1. A Study of Particle Recognition in Scanning Electron Microscope (SEM) Images Using MATLAB Erica De Jesus, Marisol Hernandez, Sreedevi Ande, PhD., Okan Caglayan, PhD.   University of the Incarnate Word/Department of Engineering / Undergraduate Students Broadway Street, San Antonio, Texas, 78209, United States
Abstract
The goal of this research is to provide an adaptive method to obtain the boundaries of nanoparticles in order to identify the void within a sample. The samples were obtained by using a scanning electron microscope (SEM). Four different types of cement that are available, both domestically and industrially are chosen for the study as the sample.
1. Introduction
This study presents a particle recognition technique by combining the characteristics of SEM images and the digital image processing in MATLAB programming environment. The algorithm was created through MATLAB’s image processing tool to improve and analyze the images provided by the SEM, enabling the algorithm to identify key features from the images displayed by the Scanning Electronic Microscopy (SEM).
2. SEM
Scanning Electron Microscope (SEM) provides detailed high resolution images of the sample by rastering a focused electron beam across the surface and detecting secondary or backscattered electron signal. With the cement samples, the SEM produced data such at elements contained within the cement. These elements were Aluminum, Calcium, Carbon, Iron, Oxygen, Silicon, and Sulfur.
3. MATLAB
An image segmentation algorithm was developed to identify the voids in the SEM images. We measured the areas of these voids by multiplying the number of pixels in length and width within the identified voids. These measurements were compared to the American Institute of Concrete standards to classify them to be structurally safe or not safe. Below are the SEM and MATLAB images of Type S, portland cement pastes and void measurement output given by MATLAB.
Fig. 1 Type S Paste void under SEM
Fig. 2 Type S Paste void under MATLAB
Fig. 3 Portland Paste void under SEM
Fig. 4 Portland Paste void under MATLAB
Fig. 7 Type N- void width
Fig. 5 Type N SEM output
Fig. 6 Type N- void length
Proceedings of the 2018 ASEE Gulf-Southwest Section Annual Conference The University of Texas at Austin
April 4-6, 2018