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Assessment of statistical agreement of three techniques for the study of cut marks: 3D digital microscope, laser scanning confocal microscopy and micro‐photogrammetry
Author(s) -
MATÉGONZÁLEZ MIGUEL ÁNGEL,
ARAMENDI JULIA,
YRAVEDRA JOSÉ,
BLASCO RUTH,
ROSELL JORDI,
GONZÁLEZAGUILERA DIEGO,
DOMÍNGUEZRODRIGO MANUEL
Publication year - 2017
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12575
Subject(s) - photogrammetry , laser scanning , confocal , confocal laser scanning microscopy , microscope , identification (biology) , microscopy , computer science , artificial intelligence , materials science , optics , computer vision , geology , laser , physics , biomedical engineering , engineering , biology , botany
Summary In the last few years, the study of cut marks on bone surfaces has become fundamental for the interpretation of prehistoric butchery practices. Due to the difficulties in the correct identification of cut marks, many criteria for their description and classification have been suggested. Different techniques, such as three‐dimensional digital microscope (3D DM), laser scanning confocal microscopy (LSCM) and micro‐photogrammetry (M‐PG) have been recently applied to the study of cut marks. Although the 3D DM and LSCM microscopic techniques are the most commonly used for the 3D identification of cut marks, M‐PG has also proved to be very efficient and a low‐cost method. M‐PG is a noninvasive technique that allows the study of the cortical surface without any previous preparation of the samples, and that generates high‐resolution models. Despite the current application of microscopic and micro‐photogrammetric techniques to taphonomy, their reliability has never been tested. In this paper, we compare 3D DM, LSCM and M‐PG in order to assess their resolution and results. In this study, we analyse 26 experimental cut marks generated with a metal knife. The quantitative and qualitative information registered is analysed by means of standard multivariate statistics and geometric morphometrics to assess the similarities and differences obtained with the different methodologies.