The application of 3D laser scanning in the mining industry is increasing progressively over the
years. This presents an opportunity to visualize and analyze the underground world and potentially
save countless man- hours and exposure to safety incidents.
This thesis envisions to detect the “Edges of the Rocks” in the 3D point cloud collected via scanner,
although edge detection in point cloud is considered as a difficult but meaningful problem.
As a solution to noisy and unorganized 3D point cloud, a new method, EdgeScan method, has been
proposed and implemented to detect fast and accurate edges from the 3D point cloud for real time
systems. EdgeScan method is aimed to make use of 2D edge processing techniques to represent
the edge characteristics in 3D point cloud with better accuracy. A comparisons of EdgeScan
method with other common edge detection methods for 3D point cloud is administered, eventually,
results suggest that the stated EdgeScan method furnishes a better speed and accuracy especially
for large dataset in real time systems.Master of Science (MSc) in Computational Science
