关键词:  , 曲面重构, B样条曲面, Kohonen神经网络, 自组织特征映射

Abstract: The approach to the freeform surface self-organizing reconstruction for the dense 3D scattered data was discussed.Based on the self-organizing feature map neural network,a rectangle mesh reconstruction approach and the training algorithm were developed.The inherent topologic relations between the scattered points on the surface were learned by the self-organizing feature map neural network.The weight vectors of the neurons on the output layer of the neural network were used to approximate the scattered data points.By this approach,not only to approximate the scattered data points and the surface which is reconstructed by this method can be as base surface for further process,but also the experiment indicates that by this approach,the reconstruction of the surface and the reduce of the dense scattered data points are combined into the same process.The computer simulation result shows that this method is effective.

Key words: surface reconstruction, B-spline surface, Kohonen neural network, Self-Organizing Feature Map(SOFM)