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dc.contributor.authorChristie, Gordon A.en
dc.date.accessioned2014-03-14T21:36:30Zen
dc.date.available2014-03-14T21:36:30Zen
dc.date.issued2013-05-06en
dc.identifier.otheretd-05202013-124438en
dc.identifier.urihttp://hdl.handle.net/10919/42762en
dc.description.abstractThis thesis explores the use of computer vision to facilitate three different processes of a quarry's operation. The first is the blasting process. This is where operators determine where to drill in order to execute an efficient and safe blast. Having an operator manually determine the drilling angles and positions can lead to inefficient and dangerous blasts. By using two cameras, oriented vertically, and separated by a fixed baseline, Structure from Motion techniques can be used to create a scaled 3D model of a bench. This can then be analyzed to provide operators with borehole locations and drilling angles in relation to fixed reference targets. The second process explored is the crushing process, where the rocks pass through different crushers that reduce the rocks into smaller sizes. The crushed rocks are then dropped onto a moving conveyor belt. The maximum dimension of the rocks exiting the crushers should not exceed size thresholds that are specific to each crusher. This thesis presents a 2D vision system capable of estimating the size distribution of the rocks by attempting to segment the rocks in each image. The size distribution, based on the maximum dimension of each rock, is estimated by finding the maximum dimension in the image in pixels and converting that to inches. The third process of the quarry operations explored is where the final product is piled up to form stockpiles. For inventory purposes, operators often carry out a manual estimation of the size of a the stockpile. This thesis presents a vision system capable of providing a more accurate estimate for the size of the stockpile by using Structure from Motion techniques to create a 3D reconstruction. User interaction helps to find the points that are relevant to the stockpile in the resulting point cloud, which are then used to estimate the volume.en
dc.publisherVirginia Techen
dc.relation.haspartChristie_GA_2013.pdfen
dc.relation.haspartChristie_GA_T_2013_Copyright.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectComputer Visionen
dc.subjectRocksen
dc.subjectImage-based 3D Reconstruction Real-time Image Procen
dc.subjectImage Segmentationen
dc.titleComputer Vision for Quarry Applicationsen
dc.typeThesisen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.description.degreeMaster of Scienceen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelmastersen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.disciplineElectrical and Computer Engineeringen
dc.contributor.committeechairKochersberger, Kevin Bruceen
dc.contributor.committeememberAbbott, A. Lynnen
dc.contributor.committeememberParikh, Devien
dc.contributor.committeememberWestman, Erik Christianen
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05202013-124438/en
dc.date.sdate2013-05-20en
dc.date.rdate2013-06-11en
dc.date.adate2013-06-11en


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