Automatic segmentation of road overpasses and detection of mortar efflorescence using mobile LiDAR data

This manuscript presents a novel method to automatize the efflorescence detection process in road overpasses using the geometric and radiometric informations from mobile LiDAR data. The study is performed over three main groups of algorithms. First, a data reduction algorithm based on the point cloud normalization, radial and vegetation filters is implemented. A second group of segmentation and classification algorithms uses the incidence angle derived by the LiDAR sensors to separate overpasses from pavement data. Finally, an algorithm to classify efflorescence considering its reflectivity lower than the surrounding granite is developed. The experimental results demonstrate the effectiveness of the method, using field data from the New Bridge of Ourense (Spain).