The classification of ceramic archaeological fragments is based on shape, dimensions, decorations, technological elements, color and material. Nowadays, all of these features are still recognized and analyzed by a skilled operator. It follows that the resulting characterization of shape and sizes of archaeological fragments is poorly reproducible and repeatable. With a view to overcome these limitations, a computer-based methodology, able to extract automatically several quantitative information from high-density discrete geometric models acquired by the laser scanning of archaeological fragments, was proposed. In this paper, the set of quantitative information obtainable is furtherly broadened, by including the segmentation of some types of morphological features, the identification of the fragment shape type, the evaluation of the longitudinal profile and the estimation of a larger set of dimensional features. Finally, a new 3D information framework is proposed to store the large variety of quantitative information extracted.

A 3D information framework for automated archaeological pottery archival

Di Angelo L.;Di Stefano P.;Guardiani E.;Morabito A. E.
2019

Abstract

The classification of ceramic archaeological fragments is based on shape, dimensions, decorations, technological elements, color and material. Nowadays, all of these features are still recognized and analyzed by a skilled operator. It follows that the resulting characterization of shape and sizes of archaeological fragments is poorly reproducible and repeatable. With a view to overcome these limitations, a computer-based methodology, able to extract automatically several quantitative information from high-density discrete geometric models acquired by the laser scanning of archaeological fragments, was proposed. In this paper, the set of quantitative information obtainable is furtherly broadened, by including the segmentation of some types of morphological features, the identification of the fragment shape type, the evaluation of the longitudinal profile and the estimation of a larger set of dimensional features. Finally, a new 3D information framework is proposed to store the large variety of quantitative information extracted.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/144967
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