The Filtering and Streamline of Three-Dimensional Point-Cloud Data

Abstract:

Three-dimensional scanning device will scan a large number of three-dimensional data one time, which will inevitably mixed with some of the noise points, casusing the reconstructed surfaces and curves that is not smooth. At the same time a large number of three-dimensional data can lead to reconstructing surface slow down. This paper applied Wiener-filtering which is commonly used in the gray image de-noising and smoothing treatment to filtering three-dimensional point-cloud-data by replace the gray value of gray image with a z value of point-cloud-data, and the point-cloud-data which undulates strongly will be seen as noise point and removed. At the same time using octree algorithm to streamline the data, which can be guaranteed to retain local feature point cloud data while streamlining data.

• Periodical: Applied Mechanics and Materials (Volumes 511-512)
• Pages: 554-558
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.511-512.554
• Online since: February 2014
• Authors: Zheng Chang Zhang*
• Keywords: Octree, Point-Cloud-Data, Wiener-Filtering

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