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Mathematical Problems in Engineering
Volume 2013, Article ID 523729, 16 pages
Research Article

A New Skeleton Feature Extraction Method for Terrain Model Using Profile Recognition and Morphological Simplification

1School of Computer Science and Information Technology Northeast Normal University, Changchun 130117, China
2Key Laboratory of Intelligent Information Processing of Jilin Universities, Changchun 130117, China

Received 10 July 2013; Accepted 12 August 2013

Academic Editor: William Guo

Copyright © 2013 Huijie Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


It is always difficul to reserve rings and main truck lines in the real engineering of feature extraction for terrain model. In this paper, a new skeleton feature extraction method is proposed to solve these problems, which put forward a simplification algorithm based on morphological theory to eliminate the noise points of the target points produced by classical profile recognition. As well all know, noise point is the key factor to influence the accuracy and efficiency of feature extraction. Our method connected the optimized feature points subset after morphological simplification; therefore, the efficiency of ring process and pruning has been improved markedly, and the accuracy has been enhanced without the negative effect of noisy points. An outbranching concept is defined, and the related algorithms are proposed to extract sufficient long trucks, which is capable of being consistent with real terrain skeleton. All of algorithms are conducted on many real experimental data, including GTOPO30 and benchmark data provided by PPA to verify the performance and accuracy of our method. The results showed that our method precedes PPA as a whole.