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Study on Data Processing Algorithm of Complex Curve Based on Point Cloud Data

机译:基于点云数据的复杂曲线数据处理算法研究

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When fitting point cloud data, use polynomial curve fitting method is hard to obtain a better fitting effect. While by using segment curve fitting method, there are defects of unsatisfaction with the continuity and differentiability of a function at the place of segments. Therefore, based on the foundation of traditional least square method curve fitting, this paper propose to use Lagrange multiplier to implement point cloud data fairing processing. Through the inspection of practical data, the precision of this algorithm is higher, which meet the requirements of point cloud data's fairing and provide an effective mathematical algorithm for the fairing processing of point cloud data in reverse engineering.
机译:当配合点云数据时,使用多项式曲线拟合方法很难获得更好的拟合效果。虽然通过使用段曲线拟合方法,但是在段的函数的连续性和可分性时,存在缺陷。因此,基于传统最小二乘法曲线拟合的基础,本文建议使用拉格朗日乘数来实现点云数据整流处理。通过实际数据的检查,该算法的精度较高,这符合点云数据的整流量的要求,并为逆向工程中的点云数据的整理处理提供了有效的数学算法。

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