Reconstruction of 3D Shapes from Contour Line Data using The Backpropagation Neural Networks (2)


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 4, No. 2, pp. 586-595, Feb. 1997
10.3745/KIPSTE.1997.4.2.586,   PDF Download:

Abstract

We propose a more improved algorithm which can reconstruct the better 3D terrains from contour line data using the fractals and the Neural Networks and which is an improvement based on that in [1,2,3] with the consideration on neighboring patch. We have learned the feature data in addition to reflect the characteristics of complicated topography, and have implemented on mountainous and flatness topography using the proposed learning pattern by the reduced average error. The results of implements represented that the mountainous topography is better than that of flatness on the similarity and the visuality.


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Cite this article
[IEEE Style]
K. S. Sun, K. D. Yoon, K. H. Jine, "Reconstruction of 3D Shapes from Contour Line Data using The Backpropagation Neural Networks (2)," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 4, no. 2, pp. 586-595, 1997. DOI: 10.3745/KIPSTE.1997.4.2.586.

[ACM Style]
Kim Su Sun, Kim Dong Yoon, and Kim Ha Jine. 1997. Reconstruction of 3D Shapes from Contour Line Data using The Backpropagation Neural Networks (2). The Transactions of the Korea Information Processing Society (1994 ~ 2000), 4, 2, (1997), 586-595. DOI: 10.3745/KIPSTE.1997.4.2.586.