Development of a Workflow for Automatic Classification and Digitization of Road Objects Gathered with Mobile Mapping

Abstract: Mobile Mapping Systems gathers a lot of spatial data that can be used for inventory and analyses regarding road safety. The main purpose of this thesis is to propose a workflow for automatic classification and digitisation of objects in a point cloud gathered by a Mobile Mapping System.   The current method used for processing point clouds is performed manually which is cost-inefficient and time consuming due to the vast amount of data the point cloud contains.   Before defining the workflow, different software were reviewed for finding which ones to use for the classification. The software review showed that a combination of using Terrasolid and FME is suitable for performing the steps suggested in the classification and digitisation method.   The proposed workflow for performing automatic classification and digitisation is based on six different steps: Identify characteristics of the objects of interest, Filter the point cloud, Noise reduction, Identify objects, Digitise and Control. This method has been carried out on two examples, road signs and painted road lines. Attributes that have been used for classifying the objects involves intensity, colour value and spatial relations. The results showed that for digitising road signs, the method found 15 out of 16 signs (94%). For digitising the painted road lines, the results produced by the automatic function had an average misalignment of 3.8 centimetres in comparison to the initial point cloud. The thesis demonstrates that the carried out functions are less time demanding for the user, compared to the manual method carried out today.