Type of Document Master's Thesis Author Christie, Gordon A URN etd-05202013-124438 Title Computer Vision for Quarry Applications Degree Master of Science Department Electrical and Computer Engineering Advisory Committee
Advisor Name Title Kevin Kochersberger Committee Chair A. Lynn Abbott Committee Member Devi Parikh Committee Member Erik Westman Committee Member Keywords
- Computer Vision
- Image-based 3D Reconstruction Real-time Image Proc
- Image Segmentation
Date of Defense 2013-05-06 Availability restricted 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
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.
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