Traditional visual fabric surveying has been shown to lack accuracy and objectivity, and be characterised by limited interoperability, with other methods significantly reducing productivity and hindering efficiency. Moving beyond established visual survey methods, the rapid evolution of reality capture technologies used for digital documentation, such as terrestrial laser scanning, is facilitating the acquisition of precise geometric and colour-related data that can more effectively support surveying, maintenance and repairworks. Reality capture data of this nature is subsequently processed,delivering meaningful information about individual masonry units that can be integrated into progressive building maintenance management systems (e.g. BIM-based). The present paper outlines the structure of an innovative tool for the semi-automated segmentation of 3D point clouds of rubble-constructed stone walls into individual masonry units and mortar regions. This tool has been developed as a plugin for the open source 3D data processing software ‘CloudCompare’. An algorithm based on the Continuous Wavelet Transform is employed for the automatic segmentation of the point cloud and shows high levels of accuracy. A manual segmentation functionality is also added to the tool to correct any error from the initial automated segmentation. The proposed tool has been tested and validated with 3D data from several walls of Linlithgow Palace, a historic building of national importance managed and maintained by Historic Environment Scotland(HES). The results are positive and demonstrate the ease of use and functionality of the tool in attaining better and faster survey outcomes.
|Publication status||Published - 2020|
|Event||Stone 2020 - , Germany|
Duration: 15 Sep 2020 → …
|Period||15/09/20 → …|