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Photogrammetry-based Texture Analysis of a Volcaniclastic Outcrop-peel: Low-cost Alternative to TLS and Automation Potentialities using Haar Wavelet and Spatial-Analysis Algorithms
Christopher Gomez(1*), Kyoko Kataoka(2), Aditya Saputra(3), Patrick Wassmer(4), Atsushi Urabe(5), Justin Morgenroth(6), Akira Kato(7)(1) Kobe University, Graduate School of Maritime Sciences, Higashinada-ku, Fukae-Minamimachi 5-1-1, 658-0022 Kobe City, Japan
(2) Niigata University, Research Institute for Natural Hazards & Disaster Recovery. 950-2181 Niigata-City, Nishi-ku, Ikarashi 2nochou 8050, Japan
(3)
(4)
(5) Niigata University, Research Institute for Natural Hazards & Disaster Recovery. 950-2181 Niigata-City, Nishi-ku, Ikarashi 2nochou 8050, Japan
(6)
(7)
(*) Corresponding Author
Abstract
Numerous progress has been made in the field of applied photogrammetry in the last decade, including the usage of close-range photogrammetry as a mean of conservation and record of outcrops. In the present contribution, we use the SfM-MVS method combined with a wavelet decomposition analysis of the surface, in order to relate it to morphological and surface roughness data. The results demonstrated that wavelet decomposition and RMS could provide a rapid insight on the location of coarser materials and individual outliers, while arithmetic surface roughness were more useful to detect units or layers that are similar on the outcrop. The method also emphasizes the fact that the automation of the process does not allows clear distinction between any artefact crack or surface change and that human supervision is still essential despite the original goal of automating the outcrop surface analysis.
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References
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