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2019 | OriginalPaper | Buchkapitel

Historic Digital Survey: Reality Capture and Automatic Data Processing for the Interpretation and Analysis of Historic Architectural Rubble Masonry

verfasst von : Enrique Valero, Frédéric Bosché, Alan Forster, Ewan Hyslop

Erschienen in: Structural Analysis of Historical Constructions

Verlag: Springer International Publishing

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Abstract

Detailed segmentation for the analysis of rubble masonry substrates is complex due to the lack of uniformity in size, geometry, coursing, bonding, and materials composition and texture of the individual stones. State-of-the-art technologies, such as Terrestrial Laser Scanning (TLS) or photogrammetry, deliver precise geometrical and coloured data that can be processed by means of innovative techniques to segment and label these masonry units. The automatic segmentation of individual stones supports further analysis of rubble masonry via several parameters related to their geometry and face colour. These can be utilized for deciphering architectural construction methods and changes in materials, as well as being employed for practical maintenance and repair operations. This paper presents a new strategy for investigating historic masonry substrates, especially from the perspective of data processing methods supporting the automated segmentation and labelling of rubble stone walls. In particular, an innovative method based on the Continuous Wavelet Transform (CWT) is proposed for the automatic segmentation of rubble stone walls, which subsequently enables the automated analysis of the individual stones and mortar regions. Different experiments have been conducted on two significant Cultural Heritage (CH) buildings in Scotland, with the results clearly demonstrating the potential of the proposed method for historic interpretation and analysis.

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Metadaten
Titel
Historic Digital Survey: Reality Capture and Automatic Data Processing for the Interpretation and Analysis of Historic Architectural Rubble Masonry
verfasst von
Enrique Valero
Frédéric Bosché
Alan Forster
Ewan Hyslop
Copyright-Jahr
2019
Verlag
Springer International Publishing
DOI
https://doi.org/10.1007/978-3-319-99441-3_41