Earticle

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

키워드

저자

• 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 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605