Accuracy Assessment on Point Cloud Dataset from Terrestrial Laser Scanner with Different Objects Surface Properties

Abstract

Terrestrial laser scanner is the instrument used for generating and receiving point cloud data from the ground either using tripod or handheld. This study focused on identifying the effect of different object surface properties in most standard building materials used towards the accuracy of point cloud captured using TLS that is important for guiding the observer before making measurement. Practically, all the captured data for each surface used the similar aspects in terms of resolution, quality, and point cloud distance using a single scan method. Next, all data processing were processed and computed using FARO Scene, ArcScene and AutoDesk Recap software that are capable to analyse through the reconstructed 3D model. It had been found that cement wall reacts better with the point clouds even the wood expected to give a good result as a few factors had given big impacts towards each of the object surfaces. The finding from this study had identified the reaction of the point clouds on each different object surfaces with various properties varies depending on the roughness, reflectivity strength, colors, textures and type of surfaces that became major indicator to determine accuracy of the distributions and arrangements of point clouds on each surface.