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dc.contributor.authorChristie, Gordon A.en_US
dc.date.accessioned2014-03-14T21:36:30Z
dc.date.available2014-03-14T21:36:30Z
dc.date.issued2013-05-06en_US
dc.identifier.otheretd-05202013-124438en_US
dc.identifier.urihttp://hdl.handle.net/10919/42762
dc.description.abstractThis thesis explores the use of computer vision to facilitate three dierent processes of a quarry's operation. The rst is the blasting process. This is where operators determine where to drill in order to execute an ecient and safe blast. Having an operator manually determine the drilling angles and positions can lead to inecient and dangerous blasts. By using two cameras, oriented vertically, and separated by a xed 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 xed reference targets. The second process explored is the crushing process, where the rocks pass through dierent 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 specic 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 nding the maximum dimension in the image in pixels and converting that to inches. The third process of the quarry operations explored is where the nal 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 nd the points that are relevant to the stockpile in the resulting point cloud, which are then used to estimate the volume.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartChristie_GA_2013.pdfen_US
dc.relation.haspartChristie_GA_T_2013_Copyright.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectComputer Visionen_US
dc.subjectRocksen_US
dc.subjectImage-based 3D Reconstruction Real-time Image Procen_US
dc.subjectImage Segmentationen_US
dc.titleComputer Vision for Quarry Applicationsen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
dc.contributor.committeechairKochersberger, Kevin Bruceen_US
dc.contributor.committeememberAbbott, A. Lynnen_US
dc.contributor.committeememberParikh, Devien_US
dc.contributor.committeememberWestman, Eriken_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05202013-124438/en_US
dc.date.sdate2013-05-20en_US
dc.date.rdate2013-06-11
dc.date.adate2013-06-11en_US


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