Comparison inspection between ICT images & CAD model based on edge extracting by neural networks

被引：2
|
作者：
Zeng L. [1 ,2 ]
He H.-J. [1 ]
Zhang Z.-B. [1 ]
机构：
[1] College of Mathematics and Statistics, Chongqing University
[2] ICT Research Center, Key Laboratory of Optoelectronic Technology and System, Ministry of Education, Chongqing University
来源：
Guangxue Jingmi Gongcheng/Optics and Precision Engineering | 2011年 / 19卷 / 10期
关键词：
Comparison inspection; Computer Aided Design(CAD); Industrial Computed Tomography(CT); Iterative closest point; Neural network;
D O I：
10.3788/OPE.20111910.2533
中图分类号：
学科分类号：
摘要：
A method to analyze the manufacture error of a workpiece based on the comparison inspection between Industrial Computed Tomography (ICT) images and Computer Aided Design (CAD) model was discussed. Firstly, the edged surfaces of ICT images were extracted by the Cellular Neural Network (CNN) with adaptive templates and the data were fused in three directions to obtaine the complete 3D edge surfaces. Then, the Principal Component Analysis (PCA) with the method of minimum bounding box were combined to perform a rough registration, and Singular Value Decomposition and Iterative Closest Point (SVD-ICP) algorithm were used to realize the refined registration for the edged surface data and the CAD model. In experiment, the k-d tree was used to improve the calculation speed of searching for the closest point. The experimental results validate that the comparison inspection method is automatic, visualized and high-accuracy. By the improved comparison inspection method for ICT images and CAD model, the ICT technology can be used to analyze and improve the manufacturing process.
引用
收藏
页码：2533 / 2540
页数：7
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