Earticle

초록

영어

With the reverse engineering development, the accuracy of system is more important in reconstruction, especially in non-contacting measurement. This paper provides a new method measuring the accuracy the point clouds, define a image probability and the point probability according to uncertainty data. The quantity of the uncertain point data is important to measuring the result of reconstruction. The prior data can be catch from the last measurement process, especially the edge data or characteristic points. Referring to prior data, basing on the Bayesian theory the more accuracy posterior data can be computed in this paper. We divided the point cloud into different areas, and organized the data with hierarchical tree-structure. According to the probability of one tree node, we adjust the area corresponding to the node. At last, by using the existing experimental equipment, we verify the measurement of point cloud accuracy algorithm. The depth data was obtained by a laser scanner---SICK LMS100. The depth data can be computed as point data with uncertainty. The result of the reconstruction deeply relies on the quality of prior data.

목차

Abstract
 1. Introduction
 2. The Basic Principle of Uncertain Point Measurement
 3. The Basic Principle of Reconstruction Algorithm
  3.1 Partition Algorithm ——KD-tree-alike
  3.2 The Edge-point Accurate Computing Algorithm
 4. Experiment and Analysis
  4.1 The Result of Experiment
  4.2 The Analysis of the Experiment
 5. Conclusion
 Acknowledgement
 Reference

키워드

저자

• Kun Zhang [ Yanshan University, Hebei University of Science & Technology ]
• Weihong Bi [ College of Information Science & Engineering, Yanshan University ]
• Xinghu Fu [ College of Information Science & Engineering, Yanshan University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605