When a large number of stone tools need to be studied, a unique identification number is assigned to each stone tool to distinguish one from the others. Since most of the current methods of stone tool management are operated manually, identification information may be lost in the process of research. Therefore, a new system is required to provide the identification numbers automatically from actual stone tools. The previous study proposed an identification method that realizes matching using stone tool silhouettes and the ICP algorithm. However, it is difficult to identify stone tools if they are thick because the matching method is based on two-dimensional approach. According to Chida et al., the improvement of performance is achieved using D2 distribution to narrow down candidates as a preprocessing step for stone tool matching. This paper proposes a method that realizes matching including D2 distribution, which enables 3D comparison, with the methods of the previous study to achieve higher identification accuracy.
Haniwa were created for ritual use during the Kofun period and were buried with the dead as funerary offerings. Archaeologists visually observe haniwa and classify them based on archaeological findings, such as the characteristics they possess. Since observation is a subjective evaluation, an objective evaluation method is necessary for authenticity. For objective evaluation, Lu .et al.1 presented a previous research by using 3D point clouds of Haniwa. Unfortunately, Lu .et al.1 includes manual operation to extract target point sets.
Therefore, this paper describes a method to automate the process of extracting only the Haniwa’s face from point cloud data of the whole Haniwa body, as shown in Figure 1, which was used in the previous study.1
A method will be examined for automatically detecting protruding patterns on the surface of Jomon potteries using the Watershed method based on the curvature of three-dimensional measurement point clouds.
Haniwa were made for rituals during the Kofun period and were buried with the dead as funerary objects. By analyzing and classifying haniwa, archaeologists are trying to reveal information about their origins and evaluate their artistic values. Specifically, they observe haniwa carefully and classify them based on their characteristics and archaeological knowledge. Since observation is a subjective evaluation, an objective evaluation method is necessary to ensure authenticity. For objective evaluation, analysis based on digital data is effective. For example, 3D point clouds, which are digital data, can be easily obtained by photographic measurement. In [1 ], a 3D mesh is generated from a measured point cloud, and the haniwa face is analyzed based on the mesh. However, generating a mesh from a point cloud is time-consuming. In this paper, to evaluate the similarity of Haniwa faces, we investigate a method to extract the parts of Haniwa faces, such as eyes, mouth, and nose, directly from 3D point clouds.
The technique of dealing with point clouds can be applied in a wide range of fields. In archaeological and historical research, some of the methods are very useful to analyze three-dimensional features of point clouds obtained by three-dimensional measurement of artifacts excavated from ruins. Jomon potteries have various shapes depending on the areas and ages of production. In order to investigate the characteristics of the potteries, analysis methods of the rim parts and surface patterns are required. Generally, rubbing is a technique for copying patterns by applying ink to the paper placed on the surface of the pottery. This is a popular but manual method to copy the patterns of pottery surfaces. On the other hand, if the surface patterns of Jomon potteries can be extracted as digital 3D point clouds, the risk of breakage or soiling of potteries can be reduced. In addition, 3D coordinate point clouds have the advantage that they can be segmented for analyzing necessary parts. Photogrammetry can obtain a 3D coordinate point cloud without contact to an object. Photogrammetry is a technique that can obtain a three-dimensional point set from many photographs of an object taken from various angles and by calculating camera parameters. If earthenware is photographed, not only earthenware surfaces but also its inside and rim can be converted into 3D data at the same time. Introducing photogrammetry avoids manual creation and adjustment of 3D models of the earthenware. However, to use the measured point cloud in the later process such as pattern extraction, it is necessary to segment the surface, mouth rim edge, and inside. In this paper, we propose a method for segmenting an earthenware point cloud obtained by photogrammetry into outer and inner parts, an as an application, we examine a method for extracting the surface pattern in the segmented outer point cloud.
In this paper, we propose a method to estimate the height of nonadjacent pieces of earthenware. To estimate the height of a piece of earthenware without finding its adjacent pieces, a point cloud in the cross-section of the earthenware is obtained, and the obtained point cloud is approximated by an elliptic curve. An ellipse approximated from the cross-section of one piece is compared with an ellipse approximated from the cross- section of another piece, and the relative height of the pieces is estimated from the positions of the most similar ellipses.
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