The subject of this study is a group of ninety stucco fragments from the Herculaneum Archeological Park, which were part of the decoration of the Tetrapylon’s barrel vault located in the Decumanus Maximus. The archaeologist Amedeo Maiuri, former superintendent of the site, had been displaying them in a cabinet within a nearby domus, as part of his project of an open air museum, while other parts of the stucco decoration were repositioned in situ, with large lacunas. Our project’s aim has been to develop a new exhibition solution, pursuing an accurate recovery of the overall volume of the decoration, meeting the requirements of reversibility and stability of conservation-restoration treatments, while allowing further updates through new findings. Considering the wide range of methods at our disposal, the most effective technical support in matching the fragments, and acquiring accurately the shape has shown to be the 3D scanning and modeling.
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This paper presents a new effective and robust approach to noise reduction in a three-dimensional data measurement algorithm. In the literature, there are numerous algorithms for noise reduction. The proposed filter class is based on the nonparametric estimation of the density probability function in a sliding filter sphere. The main idea of the applied algorithm depends is to maximize the distance between points in the three-dimensional space the nearest neighbors in sliding 3D sphere.
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