Mesh surface reconstruction based on improved Kohonen neural network

To improve the efficiency of triangle mesh surface reconstruction in neural network, an improved Kohonen neural network is put forward, which combines Kohonen neural network and faintness clustering algorithm, and by which large scale scattered point clouds triangle mesh surface and vase surface reconstruction have been done. Characteristics comparison is carried out between the improved algorithm and general one, and the results show that the improved algorithm avoids repeat circulation in general algorithm, reduces calculation time, improves the efficiency and rate of the triangle mesh surface reconstruction. Simulation reconstruction result indicates that the improved arithmetic can realize sparse and dense triangle mesh surface reconstruction and data condensation under preconditions with primary data characteristics. The improved arithmetic has fast network convergence speed.