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A New Triangulation Method of Scattered Data Based on GCS

Zhang Dinghua

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Abstract

Triangulation of scattered data is a very important problem in reverse engineering research. Based on a kind of dynamic neural network——Growing Cell Structure(GCS), a new method of triangulation is presented in this paper, and some modification processes are also given in addition to constructing a triangle mesh with good shape. Compared with other triangulation methods, this method is relatively easy to realize and can dispose of noisy 3D data directly. The amount of vertexes in mesh can also be calculated with this method, so we can control the size of mesh in advance. Finally, a practical example is given to prove its effectiveness.

About this research paper

What this paper is about

Triangulation of scattered data is a very important problem in reverse engineering research. Based on a kind of dynamic neural network——Growing Cell Structure(GCS), a new method of triangulation is presented in this paper, and some modification processes are also given in addition to constructing a triangle mesh with good shape. Compared with other triangulation methods, this method is relatively easy to realize and can dispose of noisy 3D data directly. The amount of vertexes in mesh can also be calculated with this method, so we can control the size of mesh in advance. Finally, a practical example is given to prove its effectiveness.

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Available abstract

Triangulation of scattered data is a very important problem in reverse engineering research. Based on a kind of dynamic neural network——Growing Cell Structure(GCS), a new method of triangulation is presented in this paper, and some modification processes are also given in addition to constructing a triangle mesh with good shape. Compared with other triangulation methods, this method is relatively easy to realize and can dispose of noisy 3D data directly. The amount of vertexes in mesh can also be calculated with this method, so we can control the size of mesh in advance. Finally, a practical example is given to prove its effectiveness.

Key concepts: Triangulation, Dispose pattern, Computer science, Minimum-weight triangulation, Reverse engineering, Delaunay triangulation, Point set triangulation, Artificial neural network

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