The dimensional characterisation of pottery is usually necessary to typify finds and also to recognise sherds pertaining to the same object. With the aim of reducing the uncertainties that typically affect the measurement carried out by the approach traditionally performed by archaeologists, we propose a new automatic method for dimensional characterisation of pottery fragments. The method, starting from a 3D-scanned high point density model, takes advantages from the preventive segmentation and recognition of its significant geometric features; the corresponding characteristic dimensions are evaluated by dedicated procedures. The dimensions measured are also those typically evaluated by archaeologists. In order to quantify the performances of the proposed method, a comparison of its repeatability and reproducibility is made with respect to the traditional manual approach. The proposed method, tested in some real critical cases, demonstrates better performances and lower uncertainties with respect to the traditional approaches.

Automatic dimensional characterisation of pottery

Di Angelo, Luca;Di Stefano, Paolo
;
PANE, CATERINA
2017

Abstract

The dimensional characterisation of pottery is usually necessary to typify finds and also to recognise sherds pertaining to the same object. With the aim of reducing the uncertainties that typically affect the measurement carried out by the approach traditionally performed by archaeologists, we propose a new automatic method for dimensional characterisation of pottery fragments. The method, starting from a 3D-scanned high point density model, takes advantages from the preventive segmentation and recognition of its significant geometric features; the corresponding characteristic dimensions are evaluated by dedicated procedures. The dimensions measured are also those typically evaluated by archaeologists. In order to quantify the performances of the proposed method, a comparison of its repeatability and reproducibility is made with respect to the traditional manual approach. The proposed method, tested in some real critical cases, demonstrates better performances and lower uncertainties with respect to the traditional approaches.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/120965
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