基于桥梁点云特征的精简优化算法

Simplified optimization algorithm based on point cloud features of bridge

为了平衡桥梁工程中点云数据精简的质量与速度,提高数字信息模型的精度,提出一种面向桥梁特征的点云精简算法。该算法基于主成分分析(principal component analysis,PCA)法对点云坐标系进行自动修正,改进点云特征识别方式,采用层次化精简策略对特征进行分层级保留,最后再将点云数据融合。以精简效率和运行速度作为评价指标,与其他精简算法进行对比分析。结果表明,在较高精简率下,该算法可保留更多的桥梁细节特征,且精简质量更高。

A bridge feature-oriented point cloud reduction algorithm was proposed to balance the quality and speed of point cloud data reduction in bridge engineering as well as improving the accuracy of digital information model.Specifically,the algorithm was established based on principal component analysis(PCA),which could automatically modify the point cloud coordinate system,improve the point cloud feature recognition mode,adopt hierarchical reduction strategy to retain the features at different levels,and finally fuse the point cloud data.Evaluation indices,such as simplification efficiency and running speed,were adopted to compare and analyze the proposed algorithm with other existing simplification algorithms.The results indicate that the algorithm proposed herein can retain more detailed bridge features at higher reduction rates,thereby achieving higher reduction quality.