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论文类型：期刊论文

发表时间：2014-04-15

发表刊物：Journal of Computational Information Systems

收录刊物：EI、Scopus

卷号：10

期号：8

页面范围：3503-3510

ISSN号：15539105

摘要：The detection of feature lines plays an important role in representing and understanding geometric features of 3D models. In this paper, a new method for extracting feature lines from unorganized noisy point clouds is presented. First, feature points closing to the potential feature lines are detected by using a multi-scale operator, namely, the difference of normals. Undesired points may be possibly regarded as feature points due to the noisy point clouds and can then be easily eliminated by simply checking the feature points density. Finally, the detected feature points are divided into small groups and each group is represented by a landmark. These landmarks consist of vertices of poly-lines representing feature lines. Experimental results show that the proposed method inherits the robustness of the multi-scale operator and can be used to deal with the unorganized noisy point clouds even with data missing. ? 2014 Binary Information Press.