Computer Vision for Quarry Applications

Abstract

This 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.