{"title":"Digital sieving-Matlab based 3-D image analysis","authors":"S. Tafesse , J.M.R. Fernlund , F. Bergholm","doi":"10.1016/j.enggeo.2012.04.001","DOIUrl":null,"url":null,"abstract":"<div><p>A new image analysis technique for determining the three-dimensional size and shape distribution of coarse particles has been developed. It entails acquiring a pair of images, one each of the maximum and minimum projected area of the particles. Glow-In-the-Dark beads were used to create luminous background, thus it is named the GID method. In this study the size and shape distribution of four coarse-grained samples, size varies from 2 to 20<!--> <!-->cm, have been analyzed. The size distribution of the samples obtained from the GID analysis is comparable to sieve analysis results, and has an extra advantage of being applicable in the field. The algorithm was developed in Matlab; therefore users could make some optimization in the program to meet their own needs as the program code is open source.</p></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"137 ","pages":"Pages 74-84"},"PeriodicalIF":6.9000,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.enggeo.2012.04.001","citationCount":"45","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Geology","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0013795212001408","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
引用次数: 45
Abstract
A new image analysis technique for determining the three-dimensional size and shape distribution of coarse particles has been developed. It entails acquiring a pair of images, one each of the maximum and minimum projected area of the particles. Glow-In-the-Dark beads were used to create luminous background, thus it is named the GID method. In this study the size and shape distribution of four coarse-grained samples, size varies from 2 to 20 cm, have been analyzed. The size distribution of the samples obtained from the GID analysis is comparable to sieve analysis results, and has an extra advantage of being applicable in the field. The algorithm was developed in Matlab; therefore users could make some optimization in the program to meet their own needs as the program code is open source.
期刊介绍：
Engineering Geology, an international interdisciplinary journal, serves as a bridge between earth sciences and engineering, focusing on geological and geotechnical engineering. It welcomes studies with relevance to engineering, environmental concerns, and safety, catering to engineering geologists with backgrounds in geology or civil/mining engineering. Topics include applied geomorphology, structural geology, geophysics, geochemistry, environmental geology, hydrogeology, land use planning, natural hazards, remote sensing, soil and rock mechanics, and applied geotechnical engineering. The journal provides a platform for research at the intersection of geology and engineering disciplines.
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