Defect detection of historic structures in dark places based on the point cloud analysis by modified OptD method

Abstract

Data provided by Light Detection And Ranging (LiDAR) can be very useful, and their applications are very diverse. Information about the reflection, its intensity values of individual points give the possibility of a realistic visualization of the entire scanned object. This use of LiDAR is very important in improving safety and avoiding disasters. The use of LiDAR technology allows to 'look' and extract information about the structure of the object without the need for external lighting or daylight. In the paper the results of Terrestrial Laser Scanning (TLS) measurements conducted by means of the Leica C-10 scanner will be presented. The measurement will be performed in rooms without daylight: in the basement of the ruins of the medieval tower located in Dobre Miasto and in the basement of a century-old building located at the University of Warmia and Mazury in Olsztyn. Next, the obtained dataset of x, y, z and intensity will be processed using the Optimum Dataset (OptD) method. The application of the OptD allows to keep more points of interest area where surface is imperfect (e.g. cracks and cavities) and reduce more points of the low interest homogeneous surface (redundant information). The OptD algorithm was additionally modified by detecting and segmentation defects on a scale from 0 to 3 such as (0) harmless, (1) to the inventory, (2) requiring repair, (3) dangerous. The obtained survey results proved the high effectiveness of the modified OptD method in detection and segmentation wall defects.