In this paper, a new method for axis detection of discrete thin-walled axially symmetric surfaces is presented. This method is based on the property of thin-walled axially symmetric surfaces that the minimum path of a point on the external wall to the internal wall is on a straight line passing through the axis. This working principle, since it does not require the evaluation of differential geometrical properties, makes the method robust to noise. The proposed method has been applied in a very critical application area: axially symmetric archaeological pottery fragments, for which the evaluation of the axis is complex because of manufacturing error and of modification of the surface properties due to the action of time and weather. The trueness of the proposed method is compared with those of the five methods presented in the literature in the analysis of real sherds of various dimensions and conditions. The proposed method demonstrates greater robustness than these methods and is shown to be promising to improve the number of sherds that can be successfully analyzed.
Axis estimation of thin-walled axially symmetric solids
Angelo, Luca Di;Stefano, Paolo Di
2018-01-01
Abstract
In this paper, a new method for axis detection of discrete thin-walled axially symmetric surfaces is presented. This method is based on the property of thin-walled axially symmetric surfaces that the minimum path of a point on the external wall to the internal wall is on a straight line passing through the axis. This working principle, since it does not require the evaluation of differential geometrical properties, makes the method robust to noise. The proposed method has been applied in a very critical application area: axially symmetric archaeological pottery fragments, for which the evaluation of the axis is complex because of manufacturing error and of modification of the surface properties due to the action of time and weather. The trueness of the proposed method is compared with those of the five methods presented in the literature in the analysis of real sherds of various dimensions and conditions. The proposed method demonstrates greater robustness than these methods and is shown to be promising to improve the number of sherds that can be successfully analyzed.Pubblicazioni consigliate
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