Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) Images

The microstructural evaluation of complex cementitious materials has been made possible by the microscopic imaging tools such as Scanning Electron Microscope (SEM) and X-Ray Microanalysis. Particularly, the application of concrete SEM imaging and digital image analysis have become common in the anal...

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Main Authors: Ahamad Mohd Sanusi S., Maizul Elly Nur Myaisara
Format: Article
Language:English
Published: Sciendo 2020-06-01
Series:Civil and Environmental Engineering Reports
Subjects:
Online Access:http://www.degruyter.com/view/j/ceer.2020.30.issue-2/ceer-2020-0020/ceer-2020-0020.xml?format=INT
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spelling doaj-6a16b771e39043b399e75f6428fe38bb2020-11-25T03:04:35ZengSciendoCivil and Environmental Engineering Reports2450-85942020-06-01302657910.2478/ceer-2020-0020ceer-2020-0020Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) ImagesAhamad Mohd Sanusi S.0Maizul Elly Nur Myaisara1School of Civil Engineering, Engineering Campus, Universiti SainsMalaysiaSchool of Civil Engineering, Engineering Campus, Universiti SainsMalaysiaThe microstructural evaluation of complex cementitious materials has been made possible by the microscopic imaging tools such as Scanning Electron Microscope (SEM) and X-Ray Microanalysis. Particularly, the application of concrete SEM imaging and digital image analysis have become common in the analysis and mapping of concrete technology. In this study, six samples of two-dimensional (2D) SEM images were spatially resampled to produce Geo-referenced SEM sample images. Subsequently, they were analyzed and the intensity histogram plot was produced to facilitate visual interpretation. The consecutive digital image analysis performed was the enhancement and noise removal process using two filtering methods i.e. median and adaptive box filter. The filtered resampled images, then undergone the unsupervised K-Means classification process to collectively separate each individual pixel corresponds to the spectral data. By spatial segmentation of K-Means algorithms, the cluster groups generated were carefully reviewed before proceeding to the final analysis. From the resulting data, the mapping of the spatial distribution of k-cluster and the quantification of micro-cracks (voids) were performed. The results of the SEM images (1st - 4th sample) showed a higher percentage of k-cluster data indicating a good correlation with the major elemental composition of EDX analysis, namely Oxide (O), Silicon (Si) and Carbon (C). Meanwhile, the subjective visual assessment of the image (5th and 6th sample) has confirmed the micro-crack developments on the concrete SEM images upon which the crack density was 3.02 % and 1.30 %, respectively.http://www.degruyter.com/view/j/ceer.2020.30.issue-2/ceer-2020-0020/ceer-2020-0020.xml?format=INTscanning electron microscopegeo-referenced imagedigital image analysisimage mapping
collection DOAJ
language English
format Article
sources DOAJ
author Ahamad Mohd Sanusi S.
Maizul Elly Nur Myaisara
spellingShingle Ahamad Mohd Sanusi S.
Maizul Elly Nur Myaisara
Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) Images
Civil and Environmental Engineering Reports
scanning electron microscope
geo-referenced image
digital image analysis
image mapping
author_facet Ahamad Mohd Sanusi S.
Maizul Elly Nur Myaisara
author_sort Ahamad Mohd Sanusi S.
title Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) Images
title_short Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) Images
title_full Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) Images
title_fullStr Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) Images
title_full_unstemmed Digital Analysis of Geo-Referenced Concrete Scanning Electron Microscope (SEM) Images
title_sort digital analysis of geo-referenced concrete scanning electron microscope (sem) images
publisher Sciendo
series Civil and Environmental Engineering Reports
issn 2450-8594
publishDate 2020-06-01
description The microstructural evaluation of complex cementitious materials has been made possible by the microscopic imaging tools such as Scanning Electron Microscope (SEM) and X-Ray Microanalysis. Particularly, the application of concrete SEM imaging and digital image analysis have become common in the analysis and mapping of concrete technology. In this study, six samples of two-dimensional (2D) SEM images were spatially resampled to produce Geo-referenced SEM sample images. Subsequently, they were analyzed and the intensity histogram plot was produced to facilitate visual interpretation. The consecutive digital image analysis performed was the enhancement and noise removal process using two filtering methods i.e. median and adaptive box filter. The filtered resampled images, then undergone the unsupervised K-Means classification process to collectively separate each individual pixel corresponds to the spectral data. By spatial segmentation of K-Means algorithms, the cluster groups generated were carefully reviewed before proceeding to the final analysis. From the resulting data, the mapping of the spatial distribution of k-cluster and the quantification of micro-cracks (voids) were performed. The results of the SEM images (1st - 4th sample) showed a higher percentage of k-cluster data indicating a good correlation with the major elemental composition of EDX analysis, namely Oxide (O), Silicon (Si) and Carbon (C). Meanwhile, the subjective visual assessment of the image (5th and 6th sample) has confirmed the micro-crack developments on the concrete SEM images upon which the crack density was 3.02 % and 1.30 %, respectively.
topic scanning electron microscope
geo-referenced image
digital image analysis
image mapping
url http://www.degruyter.com/view/j/ceer.2020.30.issue-2/ceer-2020-0020/ceer-2020-0020.xml?format=INT
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