关键词: 多源数据;融合;迭代最近点算法;拉普拉斯变形

Abstract: Accurately building 3D model by obtained data directly affects the subsequent design and manufacturing. Nowadays there are numerous ways of data acquisition, but modelling from single source of data can’t meet the demand. In order to solve the problem, a modelling method by multi-source data fusion is presented. A feature line extracting method based on heuristic search strategy is used to acquire the fusion region of fixed model. Iterative closest point registration algorithm is adopted to match the spatial position of two models. Using Laplace iterative deformation of the surface morphology, the fusion of two models is effectively achieved. CT data and optical 3D scanning model of lower jaw is adopted as data source. The experiment show that the technical route is stable and reliable and that no distortion in the fusion process. Final results reflect the real physical structure of object and 3D model has both high-precision surface and the internal structure.

Key words: multi-source data;fusion;iterative closest point;Laplace deformation