中国组织工程研究 ›› 2011, Vol. 15 ›› Issue (4): 648-652.doi: 10.3969/j.issn.1673-8225.2011.04.018

• 数字化骨科 digital orthopedics • 上一篇    下一篇

义齿三维模型构建中海量点云数据模型的精简方法

王辅辅,苏智剑,张长禄,乔海峰   

  1. 郑州大学机械工程学院,河南省郑州市  450001
  • 收稿日期:2010-07-30 修回日期:2010-10-18 出版日期:2011-01-22 发布日期:2011-01-22
  • 通讯作者: 苏智剑,硕士生导师,教授,郑州大学机械工程学院,河南省郑州市450001 szj@zzu.edu.cn
  • 作者简介:王辅辅★,男,1986年生,河南省平顶山市人,汉族,郑州大学在读硕士,主要从事逆向工程、义齿CAD/CAM系统的研究。 wangfufu2004@sina.com

A reduction method for mass point cloud data in the three-dimensional denture construction

Wang Fu-fu, Su Zhi-jian, Zhang Chang-lu, Qiao Hai-feng   

  1. School of Mechanical Engineering, Zhengzhou University, Zhengzhou   450001, Henan Province, China
  • Received:2010-07-30 Revised:2010-10-18 Online:2011-01-22 Published:2011-01-22
  • Contact: Su Zhi-jian, Master’s supervisor, Professor, School of Mechanical Engineering, Zhengzhou University, Zhengzhou 450001, Henan Province, China szj@zzu.edu.cn
  • About author:Wang Fu-fu★, Master, School of Mechanical Engineering, Zhengzhou University, Zhengzhou 450001, Henan Province, China wangfufu2004@sina.com

摘要:

背景:义齿三维模型的构建始终是义齿计算机辅助设计与制造系统的核心,而构建的三维模型的精度与效率又与对海量的原始点云数据进行精简密切相连。现有的点云精简技术,并不能完全满足义齿处理的特殊要求。
目的:针对义齿的原始点云数据进行精简,以便以最少的点,实现最有效的表达。
方法:通过三维栅格法对海量的原始离散点云数据进行拓扑重建形成一个个栅格,然后在每个栅格内拟合出平面和二次曲面,并利用弦差法来评定哪些栅格内点需要保留,哪些栅格内点需要继续八叉树剖分,从而保留曲率较大处的点云及其曲率和法向量。
结果与结论:结果表明,该算法简单高效,所提出的点云精简算法适用于逆向工程中测量所得的散乱无序的点云数据,能够对大量密集数据进行直接而有效的精简,并且对曲率变化大且含有较多细节特征的区域保留更多的细节信息。提示通过3DSS-STD-Ⅱ型结构光三维扫描仪得到的义齿点云数据在λ=0.7, ε=0.000 3 mm,时的精简效果最好。

关键词: 义齿计算机辅助设计与制造系统, 三维栅格法, 弦差法, 数据精简, 点云

Abstract:

BACKGROUND: The construction of the three-dimensional denture model is always the core of the dental computer-aided design/computer-aided manufacture (CAD/CAM) systems; however, the precision and the efficiency of the three-dimensional model closely connected with the data reduction of the large amounts of original point data. The existing point cloud reduction technology cannot completely meet the special requirements of dental treatment.
OBJECTIVE: To efficiently reduce the original point cloud data for the dentures in order to achieve the best effect using the fewest points.
METHODS: The large amounts of original discrete point data were topologically reconstructed by the three-dimensional grid method and formed grids. The plane and quadric were fitted in each grid, and determined by chordal deviation method; grid points need to be retained. Then points in the larger curvature with their curvature and normal vector were retained by the octree subdivision method.
RESULTS AND CONCLUSION: The results showed that this algorithm is simple and efficient; the reduction algorithm method of point cloud is suitable for the scattered and disordered point cloud data were measured in reverse engineering. This method can directly and effectively reduce a large amount of intensive data, and can retain more details in the region of the larger curvature and contains more detailed features. It is indicated that the point cloud data for the dental prosthesis obtained by 3DSS-STD-Ⅱstructured light 3D scanner have the best effect of reduction at λ=0.7, ε=0.000 3 mm.

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