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Abstract:
The miniature structured-light sensor outputs a 3D image as a triangular mesh. The mesh was uploaded into software tools that calculated the strike and dip of each triangle, and stereonets. Results from the stereonets of specific areas showed that the strikes and dips derived from images were within 10° of the Brunton compass measurements. Twenty geological hand samples were ordered from smoothest to roughest by 10 people using their sense of touch. The samples were then imaged by a laser digitizer. As the surface became increasingly rougher, the standard deviation of the distance of individual points from the image to a best-fit plane calculated using principal component analysis (PCA) increased. Lidar data from the Canadian Wollastonite mine was uploaded into a program that separates point cloud data into cubes and calculated the PCA of each cube. Visual inspection showed that rough areas are either protruding or receding.