Geometric morphometry is a method used to analyse the morphological characteristics of research objects and has many applications in biological analysis. With the development of 3D digital technology, geometric morphometry is widely used on 3D models. The pottery samples were obtained from the Ganguya site (1850 and 1500 BCE) in Gansu Province. Three-dimensional models of the pottery were obtained by photogrammetry, and the outline curves of the pottery were extracted. The outline curves were converted into angles by a turning function, and four characteristic indices were extracted according to the features of the angle function curve. Two principal components were extracted, and the samples were divided into three categories by the K-means clustering algorithm. The characteristics and differences of the three categories were analysed. The turning function provides a new method for generating an outline in geometric morphometry and a new perspective for the study of pottery morphology.

Human gesture has the characteristics of intuitive, natural and informative, and is one of the most commonly used interaction methods. However, in most gesture interaction researches, the hand to be detected is facing detection camera, and experiment environment is ideal. There is no guarantee that these methods can achieve perfect detection results in practical applications. Therefore, gesture interaction in complex environments has high research and application value. This paper discusses hand segmentation and gesture contour extraction methods in complex environments and specific applications: First, according to the characteristics of depth map, an adaptive weighted median filtering method is selected to process depth data; then use depth information to construct background model which can reduce interference of noise and light changes, and combine RGB information and depth threshold segmentation to complete hand segmentation; finally, region grow method is used to extract precise gesture contour. This paper verifies the proposed method by using vehicle environment material, and obtains satisfactory segmentation and contour extraction results.

Pottery is an important material in archaeological studies, and the accurate classification of pottery shapes largely depends on the experience and knowledge of archaeologists. In this thesis, pottery taken from the Gansu-Zhanqi site is used for sampling. Three-dimensional (3D) models of the pottery were obtained using 3D scanning, and a computer-assisted pottery typology was studied through quantitative analysis and elliptic Fourier descriptor. This method, which can enhance and supplement the traditional methods of classifying pottery in archaeology and thereby enrich the parameters and breadth of pottery analysis, represents a new means for exploring and experimenting with objective classification and provides a new tool for traditional archaeological analysis methods.

Quantitative analysis is used to classify pottery ware. This type of analysis is auxiliary and supplementary with respect to traditional archaeology, in which the data used in quantitative analysis are manually measured. The manual approach is slow and inaccurate, and the data extracted for each analysed item do not meet unity standards. Adopting pottery unearthed at the Tianma-Qucun burial site as an example, this article introduces a method for obtaining data using three-dimensional scanning technology and computer programming. The method is fast and accurate, and the analysed data can be loaded in batches. This method overcomes the deficiencies of traditional manual measurement and significantly improves data extraction speed and accuracy. The extracted data are subjected to cluster analysis using multivariate statistical methods to classify the pottery ware. The results are compared with those of traditional typology classification, confirming the feasibility of the method. Thus, the described method represents a research approach.

The blast furnace from the Northern Song Dynasty at Kuangshan Village is the tallest blast furnace that remains from ancient China. Previous studies have assumed that the furnace had a closed mouth. In this paper, a three-dimensional (3D) model of the blast furnace is constructed using 3D laser scanning technology, and accurate profile data are obtained using software. It is shown that the furnace throat is smaller than had been previously thought and that the furnace mouth is of the open type. This new furnace profile constitutes a discovery in the history of iron-smelting technology.