Earticle

초록

영어

Data registration is a common operation in object digitalization. This paper proposes an algorithm for registering point cloud data with such quadratic surfaces as planes and cylinders. In the proposed algorithm, the variation of neighboring points’ normal vectors are utilized to detect data that is located at the intersection of different quadratic surfaces, which is then deleted from the point clouds. Next, region segmentation is done on remaining point clouds through the growth algorithm, and feature descriptors are created for each detected quadratic surface. Finally, rough registration of data is achieved via matching of feature descriptors, and then fine registration is achieved by optimizing rough registration results through the ICP algorithm. Experimental results show that the algorithm is insensitive to outliers, has low requirements on the original poses of data and that its registration success rate is higher than that of the original ICP algorithm.

목차

Abstract
 1. Introduction
 2. Algorithm Steps
  2.1. Region Segmentation
  2.2. Quadratic Surface Fitting
  2.3. Creation and Matching of Feature Descriptors
  2.4. Rough Registration of Point Clouds Based on Quadratic Features
  2.5. ICP-Based Fine Registration
 3. Experiment and Analysis
 4. Conclusion
 References

키워드

저자

• Nie Jianhui [ School of Automation, Nanjing University of Posts and Telecommunications, Nanjing ]

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