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Automatic searching method for characteristic points cloud band in three-dimensional scanning system

A 3D scanning and automatic search technology, applied in image data processing, instruments, calculations, etc., can solve the problems of time-consuming, no additional information conditions, time-consuming triangular meshing, etc., to achieve high operating efficiency, functional Powerful, time-complexity-reducing effects

Inactive Publication Date: 2007-03-14
SOUTHEAST UNIV
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Problems solved by technology

On the one hand, this method is time-consuming. On the other hand, when the surface bump changes drastically, there is no good rule for the positive and negative directions of the normal vector.
Other literatures have proposed algorithms for dividing surface point clouds into different components according to feature regions, but these algorithms require triangular meshing of point clouds in order to find feature regions, and triangular meshing is very time-consuming
There are also methods proposed in some literatures based on surface equations, which is difficult to do when only the original data is given without any other information

Method used

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  • Automatic searching method for characteristic points cloud band in three-dimensional scanning system
  • Automatic searching method for characteristic points cloud band in three-dimensional scanning system
  • Automatic searching method for characteristic points cloud band in three-dimensional scanning system

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Embodiment Construction

[0026] The specific implementation manner of the present invention will be further described below with reference to the accompanying drawings. The invention uses Windows NT on PC as the development platform, Visual C++ 6.0 as the development environment, and uses the new generation standard OpenGL integrated in the Visual C++ 3D graphic software interface for programming. It mainly includes the following steps:

[0027] 1) After filtering out the noise points, the normative distance γ of adjacent points (that is, the shortest distance between adjacent points under normal circumstances) is obtained, and then 25 times of γ is set as the side length of the small cube. In this way, when the scanning accuracy of the scanner changes (at this moment, the standard distance can be several times different), the algorithm is still applicable. Even if the scanning accuracy is greatly improved in the future, the algorithm does not need to be changed. After the spatial region is divided, ...

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Abstract

The automatic search method for discrete feature point cloud belt in 3D scanning system comprises: dividing the point cloud into cubic blocks every contained only one point; calculating the near one for every point to obtain its normal vector by LSM and the curvature; then, dividing whole cloud data to obtain the feature belt. This invention overcomes defect in prior art and has well effect.

Description

technical field [0001] The present invention mainly relates to a method for automatic calculation of discrete point feature point cloud bands in the process of building a point cloud model of a product by using a three-dimensional scanning system in reverse engineering. The invention belongs to the technical field of image three-dimensional information reconstruction. Background technique [0002] In reverse engineering, a very important research direction is to find the characteristic area of ​​the object. Finding the feature area of ​​an object from a large amount of scattered point cloud data is not only the direct premise of making a feature curve, but also filtering out miscellaneous points, combining point clouds, and generating a curved surface from points (according to the feature area, the entire free-form surface (the entire point) Cloud) is divided into different components (each point cloud), and multiple small pieces of surface are generated for each point clou...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 达飞鹏唐琦
Owner SOUTHEAST UNIV
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