Earticle

초록

영어

This paper presents a fuzzy normal estimate for mass point clouds of irregular models in reconstruction. 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 kind of point clouds and the output of FIS can determine which part of tooth point clouds belong to. For different kinds point clouds, corresponding algorithm is given. Point clouds in the smooth area are estimated normal by PCA directly and ones in other regions of thin or sharp area are estimated by checker and attach points. This method is simpler than those complex methods used on the whole point clouds directly. The experiment results show that much time is saved and surface reconstruction is very fine than PCA and WLOP.

목차

Abstract
 1. Introduction
 2. FIS Applied in Normal Estimation of Mass Point Clouds
 3. Fuzzy Normal Estimate Method for Point Clouds of Irregular Model
  3.1. The Character of Irregular Model
  3.2. Description of Fuzzy Rules
  3.3. Normal Estimation Framework
 4. Experimental Results
 5. Conclusions
 Acknowledgment
 References

키워드

저자

• Liu Yan-ju [ Computing Center, Qiqihar University, Qiqihar, China ]
• Jiang Jin-gang [ College of Mechanical & Power Engineering, Harbin University of Science and Technology, Harbin, China ]
• Miao Feng-juan [ Communication and Electronic Engineering Institute, Qiqihar University, Qiqihar, China ]
• Tao Bai-rui [ Computing Center, Qiqihar University, Qiqihar, China ]
• Zhang Hong-lie [ College of Computer and Control Engineering, Qiqihar University, Qiqihar, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605