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Virginia Tech

Computer Vision for Quarry Applications

Abstract

dc:description.abstract

This 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.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Electrical and Computer Engineering
Department dc:contributor.department
Electrical and Computer Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Christie, Gordon A.
Chair dc:contributor.committeechair
  • Kochersberger, Kevin B.
Committee members dc:contributor.committeemember
  • Abbott, A. Lynn
  • Parikh, Devi
  • Westman, Erik C.

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
etd-05202013-124438
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/42762

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Christie, Gordon A.. Computer Vision for Quarry Applications. masters thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/42762