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Fuzzy Classification Strategy for the Hole of Incomplete Mass Point Clouds of Irregular Model

초록

영어

This paper presents fuzzy classification strategy for the hole-filling that can classify the incomplete mass point clouds and improve the precision. The irregular model is complex object that some part is smooth and some parts are irregular including sharp features. Therefore, we put kNN and curvature of mass point clouds to fuzzy inference system to divide the type of the hole of mass point clouds and the output of FIS can determine which part of point clouds belong to. For different kind holes, corresponding algorithm is given. Point clouds in the smooth area are reconstructed by implicit directly and ones in other regions of thin or sharp area are reconstructed by attach points. This method is simpler than those complex methods used on the whole point clouds directly. The experiment results show that classification can save much time and surface reconstruction is very fine.

목차

Abstract
 1. Introduction
 2. Storage of Mass Point Clouds
 3. Characters of Mass Point Clouds
 4. Fuzzy Classification Strategy
  4.1. Fuzzy Inference
  4.2. Description of Fuzzy Rules
 5. Experimental Results
 6. Conclusions
 References

저자정보

  • Liu Yan-zhong Communication and Electronic Engineering Institute, Qiqihar University, Qiqihar, China
  • LiuYan-ju Computing Center, Qiqihar University, Qiqihar, China
  • Li Cheng Communication and Electronic Engineering Institute, Qiqihar University, Qiqihar, China
  • Zhang Hong-lie Communication and Electronic Engineering Institute, Qiqihar University, Qiqihar, China

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