反求工程中的数据精简技术

发布时间：2018-04-02 14:30

本文选题：反求工程　切入点：曲率分析　出处：《现代制造工程》2017年04期

【摘要】：随着激光扫描技术的不断发展,数据获得的速度及数据采集的密度也得到逐步提高。与此同时,怎样处理这些大批量的数据点也将成为基于激光扫描测量造型的主要问题。如果直接对点云进行造型处理,大批量数据的存储和处理将成为不可突破的瓶颈,从点云到模型重建整个过程将变得难以控制。目前的多数算法以牺牲效率来换取精度,而适应性最小距离法正是一种平衡效率和精度的数据精简算法。实例证明了适应性最小距离法的有效性。
[Abstract]:With the development of laser scanning technology, the speed of data acquisition and the density of data acquisition are improved.At the same time, how to deal with these mass data points will also become a major problem based on laser scanning measurement modeling.If the point cloud is modeled directly, the storage and processing of large quantities of data will become the bottleneck that can not be broken through, and the whole process from point cloud to model reconstruction will become difficult to control.At present, most algorithms sacrifice efficiency for accuracy, and adaptive minimum distance method is a data reduction algorithm for balancing efficiency and precision.Examples show that the adaptive minimum distance method is effective.
【作者单位】：河南机电职业学院;郑州大学;
【分类号】：TN249;TP274

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