Archives and Research

Technical Paper 38

Digital documentation, computer vision and machine learning for masonry surveying and maintenance

A cover page featuring a stone wall with some stones coloured in by a computer

There are 500,000 pre-1919 masonry buildings in Scotland, and they are under increasingly significant strain due to climate change. 

This report, in partnership with HES, the University of Edinburgh and Heriot-Watt University, explores different 3D surveying techniques and presents data processing solutions for both segmenting 3D point clouds and detecting and classifying visible defects of masonry walls.

  • Audiences:

    Researchers, Conservation and Heritage Enthusiasts
  • Date Published:

    28 April 2022
  • Publisher:

    Historic Environment Scotland
  • Publication Types:

    Technical Paper
  • Author(s):

    Dr Frédéric Bosché

    Senior lecturer in Construction Informatics in the School of Engineering, University of Edinburgh

    Dr Alan Forster

    Associate Professor within the Royal Academy of Engineering Centre of Excellence in Sustainable Urban Design, Heriot-Watt University.

    Dr Enrique Valero

    Research Associate in the School of Engineering, University of Edinburgh
  • Format(s):

  • Language:

  • Subjects:

    Climate Change