Abstract

ABSTRACT Masonry construction is ubiquitous and is most typically employed for the construction of fundamental structural architectural elements. It is thus extremely important in architectural conservation, and visual survey, recording and documentation often start with such primary elements. Recording has, however, traditionally been a laborious manual process yielding variable and subjective outcomes. This situation is exacerbated by the need to involve experts to interpret the recorded data, which further increases costs. Recent and ongoing advances in digital reality capture and computer vision afford notable advantages in extracting value from point cloud data with benefits to conservative repair, maintenance, and wider architectural intervention. In this paper, we build on our previous research by the authors and present bespoke algorithms brought together as a ‘digital toolkit’ to automatically segment point clouds into individual masonry units and further characterisation of each unit to support architectural interpretation. The use of this digital toolkit is illustrated using a wall section of Linlithgow Palace (Scotland, UK) as a case study, but it must be emphasised that this form of construction typifies innumerable buildings globally. The toolkit has shown to facilitate rapid and systematic identification of change in masonry construction styles, sizes and geometry, and, when used in conjunction with traditional survey evaluation, it meaningfully assists interpretative capabilities. This combined approach is termed ‘digitally assisted analytical recording’ and it offers the promise of yielding more cost-effective, accurate survey for interpretation.

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