The Technology Research Based on Least Square Method for Extracting Quadric Surface

Abstract:

In this paper, the discrete point cloud data is directly used to extract quadric surface, with the single type of the point cloud data, the surface is firstly recognized. And then, according to different types of quadric surface, using the geometric parameter equation, the technology of extracting quadric surface can be achieved based on least square method. The results of the study show that: For normal data or less noisy data, the accuracy of calculation of linear least square method is the highest. For the nonlinear square method, on the other hand, the calculation precision is the lowest. However, the computational efficiency of the nonlinear least square method is higher than the linear least square method. The least square laws are more sensitive to noise data. With the increasing of the increased noise data, the extraction accuracy of the results will be affected by certain influence, but its computation efficiency is higher. Research results to practical engineering application of least square method to extract the quadratic surface have certain guiding significance.

• Periodical: Applied Mechanics and Materials (Volumes 220-223)
• Pages: 2342-2345
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.220-223.2342
• Online since: November 2012
• Authors: Y. W. Chen, H. X. Zhang, W. Y. Zhang
• Keywords: Extract, Least-Square Method (LSM), Quadric Surface, Surface Recognition

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